U.S. patent application number 13/731027 was filed with the patent office on 2013-08-22 for electricity grid data analytics as a moduled service for production, delivery, and distribution of power as a dynamic demand response within a renewable energy-based electricity grid infrastructure.
The applicant listed for this patent is Spyros James LAZARIS. Invention is credited to Spyros James LAZARIS.
Application Number | 20130218355 13/731027 |
Document ID | / |
Family ID | 63447039 |
Filed Date | 2013-08-22 |
United States Patent
Application |
20130218355 |
Kind Code |
A1 |
LAZARIS; Spyros James |
August 22, 2013 |
ELECTRICITY GRID DATA ANALYTICS AS A MODULED SERVICE FOR
PRODUCTION, DELIVERY, AND DISTRIBUTION OF POWER AS A DYNAMIC DEMAND
RESPONSE WITHIN A RENEWABLE ENERGY-BASED ELECTRICITY GRID
INFRASTRUCTURE
Abstract
A renewable energy-based electricity grid infrastructure
utilizes distributed data analytics to enable modeling and delivery
of an appropriate, time-sensitive, dynamic demand response from
multiple renewable energy components to an intelligent power
distribution network. Data processing resources are identified and
aggregated within a distributed computing infrastructure to provide
dynamic demand response as a service of a dedicated grid data
analytics module. Aggregation of processing resources for grid data
analytics also enables the electricity grid infrastructure to
virtually, optimally and adaptively make decisions about power
production, distribution, and consumption so that a demand response
is a moduled service of the electricity grid infrastructure, and
enables distributed energy generation from multiple renewable
energy resources that is responsive to various types of grid demand
situations, such as customer demand, direct current-specific
demand, and security issues, and so that power production is
substantially balanced with power consumption.
Inventors: |
LAZARIS; Spyros James;
(Upland, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
LAZARIS; Spyros James |
Upland |
CA |
US |
|
|
Family ID: |
63447039 |
Appl. No.: |
13/731027 |
Filed: |
December 30, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13398735 |
Feb 16, 2012 |
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13731027 |
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13398738 |
Feb 16, 2012 |
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13398735 |
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13398744 |
Feb 16, 2012 |
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13398738 |
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Current U.S.
Class: |
700/291 ;
706/15 |
Current CPC
Class: |
Y04S 50/16 20180501;
G06F 30/20 20200101; H02J 13/00002 20200101; H02J 3/381 20130101;
H02J 2300/24 20200101; G06Q 50/06 20130101; H02J 3/382 20130101;
H02J 13/00034 20200101; H02J 2300/28 20200101; Y02B 70/3225
20130101; Y04S 10/50 20130101; Y04S 50/00 20130101; Y02E 10/46
20130101; Y04S 10/123 20130101; Y02E 10/56 20130101; Y02E 10/76
20130101; H02J 2300/20 20200101; Y02E 40/70 20130101; H02J 3/386
20130101; H02J 3/14 20130101; G05B 19/02 20130101; G06Q 30/0605
20130101; H02J 3/383 20130101; H02J 13/0096 20130101; H02J 2300/22
20200101; Y04S 10/30 20130101; G05B 15/02 20130101; Y02E 60/00
20130101; Y04S 50/10 20130101; F03G 6/00 20130101; Y04S 20/222
20130101 |
Class at
Publication: |
700/291 ;
706/15 |
International
Class: |
G05B 19/02 20060101
G05B019/02 |
Claims
1. A method of processing data for determination and delivery of a
demand response within a renewable energy-based electricity grid
infrastructure, comprising: aggregating data defining a power
requirement over a specified power of time of one or more
microgrids among a plurality of microgrids forming an intelligent
power distribution network, each microgrid capable of being
separately decoupled and separately generating and communicating
data defining the power requirement, and additional input data for
a plurality of mathematical modeling functions, from across a
shared, secure and privately-hosted computing environment forming a
distributed computing infrastructure in which the data defining the
power requirement and the additional input data are stored;
assigning a plurality of computing resources within the shared,
secure and privately-hosted computing environment to perform the
plurality of mathematical modeling functions on aggregated data
defining the power requirement and the additional input data within
a dedicated demand response service of the shared, secure and
privately-hosted computing environment, the assigning the plurality
of computing resources including integrating the plurality of
computing resources so that the dedicated demand response service
is configured with at least one processor and at least one memory
module for performing the plurality of mathematical modeling
functions embodied by one or more program instructions, the
plurality of computing resources aggregated to form a real-time
grid data analytics module of data processing functions for
performing the dedicated demand response service within the shared,
secure and privately-hosted computing environment to provide a
dynamic demand response to the power requirement, the real-time
grid data analytics module configured to execute the program
instructions to continuously determine the dynamic demand response
to the power requirement with at least one of modeling commodity
pricing of available renewable energy resources utilized among
multiple renewable energy resource components configured at a
common installation site, modeling meteorological conditions at the
common installation site, modeling power usage patterns of the one
or more microgrids in the intelligent power distribution network,
modeling a power production capacity of the multiple renewable
energy resource components configured at a common installation
site, and modeling a load capacity of a power transmission system
coupling the plurality of renewable energy resource components and
the intelligent distribution network, the real-time grid data
analytics module outputting one or more resulting data sets
defining a plurality of instructions for the dynamic demand
response to the power requirement; and configuring the dynamic
demand response to the power requirement from the one or more
resulting data sets, the dynamic demand response embodied as input
data from the plurality of instructions for optimizing an efficient
power production capacity and an efficient transmission load
capacity to deliver the dynamic demand response from the multiple
renewable energy resource components to the intelligent power
distribution network.
2. The method of claim 1, wherein the multiple renewable energy
resource components are configured on a multi-resource offshore
renewable energy installation and include at least two of a wind
component comprising at least one wind turbine, a photovoltaic
component comprising at least one photovoltaic module, a
hydrokinetic component comprising at least one of a surface wave
turbine, an oscillating column, and an undersea wave turbine, and a
solar thermal energy component comprising at least one
high-temperature solar thermal collector.
3. The method of claim 1, wherein the plurality of computing
resources comprise at least one artificial neural network capable
of heuristically modeling the data defining the power requirement
and the additional input data within the grid data analytics
module.
4. The method of claim 1, wherein the configuring the dynamic
demand response further comprises communicating with one or more
components in the multiple renewable energy resource components and
the power transmission system to deliver the dynamic demand
response to the one or more microgrids, the dynamic demand response
comprising at least one instruction to the multiple renewable
energy resource components to produce power for transmission to the
intelligent power distribution network and at least one instruction
to the transmission power system to transmit power from the
plurality of renewable energy resource components to the
intelligent power distribution network.
5. The method of claim 1, wherein the configuring the dynamic
demand response further comprises communicating with one or more
components in the multiple renewable energy resource components and
the power transmission system to deliver the dynamic demand
response to the one or more microgrids, the dynamic demand response
comprising at least one instruction to the multiple renewable
energy resource components to produce power for transmission to
each decoupled microgrid requiring power and at least one
instruction to the power transmission system to separately transmit
power to each decoupled microgrid requiring power.
6. The method of claim 1, further comprising receiving data
indicative of a request for at least one of a delivery of power to
specific decoupled microgrids in the one or more microgrids, a
delivery of power in direct current form only to a specific
decoupled microgrid, and a delivery of power in at least one
specified amount from one or more components in the multiple
renewable energy resource components.
7. The method of claim 1, wherein the integrating a plurality of
computing resources within the shared, secure and privately-hosted
computing environment to perform the plurality of mathematical
modeling functions on the aggregated data defining the power
requirement further comprises modeling weather conditions over the
specified period of time at a deep-ocean location of a
multi-resource offshore renewable energy installation site hosting
the multiple renewable energy resource components to predict most
favorable weather conditions and least favorable weather conditions
for optimal operation of a specific renewable energy resource
component, modeling future trends in energy commodity prices over
the specified period of time to predict most favorable commodity
pricing and least favorable commodity pricing to develop a range of
commodity pricing for optimal operation of a specific renewable
energy resource component, and modeling the power production
capacity of the multiple renewable energy resource components by
assessing an operational availability of each specific renewable
energy resource component.
8. The method of claim 1, wherein the integrating a plurality of
computing resources within the shared, secure and privately-hosted
computing environment to perform the plurality of mathematical
modeling functions on the aggregated data defining the power
requirement further comprises modeling the load capacity of the
power transmission system by communicating with at least one
transmission control system to monitor a power output circuit of
each renewable energy resource component and an output of each
voltage source converter in a system of voltage source converters
so that a combined power output of the multi-resource offshore
renewable energy installation is within the load capacity of the
high voltage direct current transmission system to ensure a stable
power transmission link between the multi-resource offshore
renewable energy installation and the intelligent power
distribution network.
9. The method of claim 1, wherein the shared, secure and
privately-hosted computing environment is configured to maximize
data protection and minimize disruption of the delivery of a
dynamic demand response from a loss of data.
10. A method of aggregating distributed processing resources for
modeling and delivering a demand response as a service within a
renewable energy-based electricity infrastructure, comprising:
determining a data processing requirement for modeling a dynamic
demand response to data representative of a power requirement over
a specified power of time of one or more microgrids among a
plurality of microgrids forming an intelligent power distribution
network, each microgrid capable of being separately decoupled and
separately generating and communicating data defining the power
requirement, the data representative of the power requirement
communicated by the one or more microgrids and disparately and
remotely stored within a shared, secure and privately-hosted
computing environment forming a distributed computing
infrastructure, the data processing requirement to be accessed in a
distributed fashion to execute a plurality of mathematical modeling
functions embodied to form a dedicated grid data analytics module
as a dedicated demand response service that ensures data privacy
and data security within an energy management system of the
renewable energy-based electricity grid infrastructure; identifying
available data processing resources comprising at least one
processor component, one or more memory modules, and program
instructions for performing the plurality of mathematical modeling
functions to meet the data processing requirement from within the
shared, secure and privately-hosted computing environment forming
the distributed computing infrastructure; isolating and aggregating
the identified available data processing resources so that the at
least one processor component, the one or more memory modules, and
the program instructions identified for the data processing
requirement form the dedicated grid analytics module configured to
execute the program instructions to disparately model the data
defining the power requirement in the dedicated demand response
service for modeling and delivery of the dynamic demand response;
applying the data defining the power requirement in the specific
grid analytics module to continuously model the dynamic demand
response to the power requirement with at least one of modeling
commodity pricing of available renewable energy resources utilized
among multiple renewable energy resource components configured at a
common installation site, modeling meteorological conditions at the
common installation site, modeling power usage patterns of the one
or more microgrids in the intelligent power distribution network,
modeling a power production capacity of the multiple renewable
energy resource components configured at the common installation
site, and modeling a load capacity of a power transmission system
coupling the multiple renewable energy resource components and the
intelligent distribution network to generate a set of output data
defining a plurality of instructions for the dynamic demand
response to the power requirement; and communicating the set of
output data defining the plurality of instructions to a
transmission module and to a power generation module among the
energy management system for delivery of the dynamic demand
response as a distributed energy generation to the one or more
microgrids.
11. The method of claim 10, further comprising requesting and
receiving the additional input data from additional computing
networks to perform the mathematical modeling functions, the data
being requested and received from at least one external computing
network, the at least one external computing network including at
least one of a commodity trading platform capable of communicating
data relative to a forecast of variable purchase price ranges and
variable selling price ranges for each renewable energy resource at
the common installation site over the specific period of time, a
weather satellite network capable of communicating data relative to
a forecast meteorological conditions for each renewable energy
resource at the common installation site over the specific period
of time, a plurality of renewable energy component control systems
capable of communicating data relative to an operational capacity
of the multiple renewable energy components, and a plurality of
transmission control systems capable of communicating data relative
to an operational capacity of a high-voltage direct current
transmission network.
12. The method of claim 10, wherein the identified available data
processing resources comprise at least one artificial neural
network capable of heuristically modeling the dynamic demand
response in the dedicated grid analytics module.
13. The method of claim 10, further comprising continuously
performing checks of the dynamic demand response to ensure proper
minimization of an error rate with a plurality of additional
mathematical modeling functions performed on the data defining the
power requirement and the additional input data within the
dedicated grid analytics module.
14. The method of claim 10, further comprising receiving data
indicative of a request for at least one of a delivery of power to
specific decoupled microgrids in the one or more microgrids, a
delivery of power in direct current form only to a specific
decoupled microgrid, and a delivery of power in at least one
specified amount from one or more components in the multiple
renewable energy resource components.
15. The method of claim 10, wherein the applying the data defining
the power requirement in the specific grid analytics module to
continuously model the dynamic demand response to the power
requirement further comprises modeling weather conditions over the
specified period of time at a deep-ocean location of a
multi-resource offshore renewable energy installation site hosting
the multiple renewable energy resource components to predict most
favorable weather conditions and least favorable weather conditions
for optimal operation of a specific renewable energy resource
component, modeling future trends in energy commodity prices over
the specified period of time to predict most favorable commodity
pricing and least favorable commodity pricing to develop a range of
commodity pricing for optimal operation of a specific renewable
energy resource component, and modeling the power production
capacity of the multiple renewable energy resource components by
assessing an operational availability of each specific renewable
energy resource component.
16. An energy management system comprising: a plurality of memory
modules operably coupled to a plurality of processors, the
plurality of memory modules and the plurality of processors capable
of being accessed in a distributed fashion within a plurality of
remote interconnected computing networks in a shared, secure and
privately-hosted computing environment forming a distributed
computing infrastructure in which data defining a power requirement
of an intelligent power distribution network is disparately stored
and processed; one or more program instructions accessible by the
plurality of memory modules, the plurality of processors being
operable to execute the one or more program instructions, the one
or more program instructions configured to perform a plurality of
mathematical modeling functions on aggregated data defining the
power requirement and additional input data within a dedicated
demand response service of the shared, secure and privately-hosted
computing environment, the plurality of processors, plurality of
memory modules, and program instructions forming a plurality of
dedicated computing resources aggregated within the distributed
computing infrastructure to form a real-time grid data analytics
module of data processing functions for performing the dedicated
demand response service within the shared, secure and
privately-hosted computing environment to provide a dynamic demand
response to the power requirement in a renewable energy-based
electricity grid infrastructure; the real-time grid data analytics
module configured to execute the program instructions to
continuously determine a dynamic demand response to the power
requirement over the specific period of time with at least one of
modeling commodity pricing of available renewable energy resources
among multiple renewable energy resource components configured at a
common installation site, modeling meteorological conditions at the
common installation site, modeling power usage patterns of the one
or more microgrids in the intelligent power distribution network,
modeling a power production capacity of the multiple of renewable
energy resource components configured at the common installation
site, and modeling a load capacity of a power transmission system
coupling the plurality of renewable energy resource components and
the intelligent distribution network; and one or more resulting
data sets defining a plurality of instructions for the dynamic
demand response to the power requirement, generated by the
real-time grid data analytics module as an output of the dedicated
dynamic demand response service, the output configuring to embody
the dynamic demand response to the power requirement in the
plurality of instructions for optimizing an efficient power
production capacity and an efficient transmission load capacity to
deliver the dynamic demand response to the intelligent power
distribution network in a distributed energy generation of power
from the multiple renewable energy resource components.
17. The energy management system of claim 16, wherein the data
defining the power requirement is communicated from a power
distribution module communicatively couple with a plurality of
microgrids, each microgrid capable of being separately decoupled
and separately generating and communicating data defining the power
requirement over the specific period of time.
18. The energy management system of claim 16, wherein the grid data
analytics module performs each dedicated dynamic demand response
service within at least one artificial neural network that includes
the plurality of processors, at least one memory module, and
program instructions, the program instructions configured to
heuristically model the dynamic demand response within the at least
artificial neural network.
19. The energy management system of claim 16, wherein the real-time
grid data analytics module is configured to execute the program
instructions to models weather conditions over the specified period
of time at a deep-ocean location of a multi-resource offshore
renewable energy installation site hosting the multiple renewable
energy resource components to predict most favorable weather
conditions and least favorable weather conditions for optimal
operation of a specific renewable energy resource component, models
future trends in energy commodity prices over the specified period
of time to predict most favorable commodity pricing and least
favorable commodity pricing to develop a range of commodity pricing
for optimal operation of a specific renewable energy resource
component, and models the power production capacity of the multiple
renewable energy resource components by assessing an operational
availability of each specific renewable energy resource
component.
20. The energy management system of claim 16, wherein the shared,
secure and privately-hosted computing environment is configured to
maximize data protection and minimize disruption of the delivery of
a dynamic demand response from a loss of data.
Description
CROSS REFERENCE TO RELATED PATENT APPLICATIONS
[0001] To the fullest extent provided by law, the present
non-provisional patent application is a continuation of, and claims
priority to and the full benefit of the following U.S.
non-provisional utility patent applications: Ser. No. 13/398,735,
filed Feb. 16, 2012; Ser. No. 13/398,738, filed Feb. 16, 2012; and
Ser. No. 13/398,744, filed Feb. 16, 2012.
STATEMENT REGARDING FEDERALLY-SPONSORED RESEARCH OR DEVELOPMENT
[0002] Not applicable.
FIELD OF THE INVENTION
[0003] The present invention relates to renewable energy resources.
Specifically, the present invention relates to systems, methods,
and apparatuses for supplying the power needs of an intelligent
electricity grid from an entirely-renewable energy resource
platform.
BACKGROUND OF THE INVENTION
[0004] As the interest in power generated from renewable energy
resources rapidly increases, increasing attention is being focused
systems and methods in which such power is produced, transmitted,
delivered, and consumed. Despite technological advances in
developing renewable energy resources and in electricity grids,
current energy infrastructure suffers from many limitations that
need rapid improvement as demand for such power increases, and grid
security importance and regulatory requirements for use of "green"
resources become more prominent.
[0005] Power derived from renewable energy such as solar, wind,
wave, and solar thermal resources are becoming increasingly relied
upon, but each includes several limitations that impede them from
becoming widespread, low-cost, efficient, and continually viable
sources of electricity. Each is inherently unreliable, owing to
factors such as changes in the time of day and variations in
weather conditions that mean that maximized performance of
components for each resource is very difficult to manage. Combining
any of these together proves even more difficult to manage the
inherent inefficiencies involved in operating devices and
components to meet energy demand.
[0006] Power derived from renewable energy sources is generated
both on land and at sea. Offshore energy installations present many
complicated challenges. The majority of all offshore energy
installations are primarily devoted to carbon-based, non-renewable
resources, but each of solar power, wind power, wave, and solar
thermal-based power can be and are generated from offshore
installations. However, implementing offshore installations are
extremely challenging, time-consuming, expensive, and
environmentally sensitive. Many issues must addressed by the energy
provider wishing to use an offshore base for generating power of
any kind. Just a few examples of issues that present significant
challenges include storage of power, its transmission to the
onshore power grid, providing power to the offshore installation
itself, maintenance, distance from the electricity grid, and
exposure to weather elements. Additionally, building a large-scale
multi-resource platform or installation is very expensive and often
has a large environmental impact footprint, making such an
installation a questionable investment. All of these issues can
reduce the attractiveness of constructing and operating such an
installation.
[0007] Storage issues are a particularly challenging problem
attendant to transferring power generated offshore to the onshore
electricity grid. The electricity grid itself contains limited
inherent facility for storing electrical energy. Power must be
generated constantly to meet uncertain demand, which often results
in over-generation (and hence wasted energy) and sometimes results
in under-generation (and hence power failures). Additionally, there
is limited facility for storing electrical energy at the point of
generation, particularly in the case of offshore installations
where available space must be maximized and cost and environmental
issues are major considerations.
[0008] Nonetheless, requirements for buying power generated from
"clean" or "green" renewable resources are rapidly increasing.
Enhanced ecological and environmental awareness, and a desire to
reduce energy dependency on carbon-based fossil fuels and to
decrease availability and price concerns resulting from exposure to
geopolitical concerns, has lead many governments to implement
regulations that either dictate or impose limits on the amount of
power produced and consumed that is generated from carbon-based or
otherwise non-renewable energy sources. Because of this, there is a
strong and continually developing need for efficient and
cost-effective power generated from renewable energy resources.
[0009] Furthermore, despite these challenges and many others in the
existing technology concerning power from renewable resources,
there exists a strong need for improved systems and methods of
producing, transmitting, distributing and delivering energy so that
the needs of power customers can be satisfied from renewable energy
sources. There is also a strong and increasing need for clean,
reliable, efficient sources of power that are not dependent on
geopolitical issues and which maximize the availability of
renewable resources to deliver power in real-time as needed and
instructed by "smart" electricity grids. There is further a need
for an energy management network capable of integrating data from
multiple sources that influence the amount of such power available
to be generated and required for delivery to customers of
electricity grids. Additionally, there exists a strong need in the
art for a platform that is capable of efficiently-provided power
from multiple renewable energy resources that minimize many of the
challenges facing energy providers, as well as for electricity grid
infrastructure that is capable of meeting electricity demand
substantially from renewable energy resources, maintaining grid
infrastructure integrity against increasing public security
concerns, and maximizing operational efficiency and capacity to
reduce the costs associated with the many inherent inefficiencies
with renewable energy resources.
[0010] It is accordingly one object of the present invention to
provide a renewable energy resource management system and method of
managing power distribution from a renewable resource provider to
an intelligent power distribution network, that addresses many of
the problems and challenges facing the buyers and sellers of power
derived from renewable energy resources such as wind, solar, wave,
and solar thermal energy, and with generating, transmitting and
distributing power to meet the capacity of a developing,
sophisticated, and intelligent electricity grid infrastructure. It
is a further object of the present invention to provide a
multi-resource renewable energy installation and method of
operation that addresses problems and challenges with generating
power from renewable energy resources in an efficient and
cost-effective manner to meet the substantially increasing demand,
need, and requirement for power from such resources. It is yet
another object of the present invention to provide an improved
electricity grid infrastructure, and methods of operating and
automating the same, that address the problems and challenges
associated with meeting electricity demand substantially from
renewable energy resources, maintaining grid infrastructure
security, and maximizing operational efficiency and capacity to
meet real-time power demands of grid customers.
[0011] It will be apparent to those of skill in the art that one
would be not be motivated to combine existing art, and one would
not consider it reasonable to try to combine existing art, to
arrive at the teachings of the present invention. There are many
reasons why existing technology teaches against the disclosures of
the present invention. For example, there are inherent market
biases favoring the use of existing, non-renewable energy
resources. Existing energy production infrastructure strongly
favors the use of non-renewable energy resources, and the costs of
generating power from renewable energy resources are far higher,
despite the availability of and ease with which wind, solar, wave,
and solar thermal energy can be obtained. Additionally, energy
commodity prices and weather conditions fluctuate widely, making it
very difficult and often prohibitively expensive to efficiently
generate, transmit, and distribute power derived from renewable
energy resources. These fluctuations, and the inherent
inefficiencies resulting from them in utilizing renewable
resources, make it difficult for providers to justify investing in
the infrastructure needed to develop, transmit, and distribute
power from renewable energy resources. This includes investing in
and building offshore installations, whether dedicated to a single
renewable resource or hosting multiple components that generate
power from several different renewable resources in the same
location. It will therefore be readily apparent based on all of the
above that it would not be obvious to combine any of the teachings
of the prior art to arrive at the specific technological advances
discussed herein.
BRIEF SUMMARY OF THE INVENTION
[0012] The present invention discloses, in one aspect thereof, an
energy management system that presents an operational
infrastructure for managing the generation, transmission, delivery,
and distribution of power to "smart" electricity topologies derived
from multiple renewable energy resources. The infrastructure is
fully network-connected in a distributed computing environment, and
enables utilities and providers to respond to peak demand loads
more effectively and efficiently, balance power production with
power consumption, and supply power consumers entirely from
multiple renewable resources.
[0013] In another aspect of the present invention, a multi-resource
renewable energy installation provides the ability to efficiently
produce power from multiple renewable energy resources in a single
location. The multi-resource renewable energy installation is a
fully network-connected, distributed platform for producing power
from multiple renewable energy resources and maintaining an
efficient operational capacity of each such resource to transmit
and deliver real-time power demands of customers that balances
power production to consumption to minimize both supply and
demand-side power storage requirements.
[0014] In a further aspect, the present invention discloses an
innovative electricity grid infrastructure that enables robust and
dynamic multi-directional communications and automated
decision-making systems to provide electricity grid operators with
multiple capabilities to efficiently generate, transmit, deliver
and distribute power. The electricity grid infrastructure enables
both supply and demand-side improvements in responding to peak
demand loads, balancing and maintaining power production with power
consumption to minimize grid storage requirements, re-configuring
assets for power production and re-routing power for consumption as
needed, and supplying power demand entirely from multiple renewable
energy resources.
[0015] Together, the aspects of the present invention provide
significant improvements and advances in systems and methods in
which power is produced, transmitted, delivered and distributed.
The present invention therefore incorporates and integrates
concepts in producing power from renewable, non carbon-based energy
resources, transmitting and distributing power to increasingly
interconnected and intelligent electricity grids, and delivering
power to end consumers, as discussed herein.
[0016] In one embodiment of the present invention, a renewable
energy resource management system comprises a distributed computing
infrastructure configured to integrate a plurality of modules over
one or more interconnected computing networks to efficiently manage
a delivery of power generated by a multi-resource offshore
renewable energy installation having a plurality of renewable
energy resource components and capable of generating power from
multiple renewable energy resources to an intelligent power
distribution network composed of a plurality of microgrids each
capable of being separately decoupled from the intelligent power
distribution network for distribution of power thereto, the
plurality of modules at least including a power generation module,
a power distribution module, a power settlement module, and a power
settlement module. The power distribution module having a load
control component configured to forecast a power requirement of the
intelligent power distribution network over a specific period of
time, based on a continuing assessment of a power demand of each
power user of each microgrid in the plurality of microgrids that is
communicated to the load control component and to manage a power
delivery to each microgrid in the plurality of microgrids
responsive to the power demand, and having a renewable energy
resource pricing and conditions component to continually assess a
renewable resource commodity price for each renewable energy
resource of the multiple renewable energy resources over the
specific period of time to forecast a variable purchase price range
at which each renewable energy resource is to be purchased and to
assess a renewable energy resource purchasing condition required of
the intelligent power distribution network as determined by one or
more of a regulatory requirement and a contractual requirement, and
having a communications component configured to communicate to the
power settlement module at least the power requirement of the
intelligent power distribution network, the variable purchase price
range at which each renewable energy resource is to be purchased,
and the renewable energy resource purchasing condition.
[0017] The power generation module having a renewable resource
efficiency component configured to continually assess the renewable
resource commodity price for each renewable energy resource of the
multiple renewable energy resources over the specific period of
time to forecast a variable selling price range at which each
renewable energy resource is to be sold and to generate a
meteorological conditions forecast for each renewable energy
resource of the multiple renewable energy resources for the
specific period of time, and having a renewable resource control
component configured to continually assess an operative
availability and forecast an available power capacity of each
renewable energy resource component at the multi-resource offshore
renewable energy installation, relative to at least the variable
selling price range at which each renewable energy resource is to
be sold and the meteorological conditions forecast for each
renewable energy resource, to meet the power requirement for the
specific period of time, and a communications component configured
to communicate to the power settlement module the available power
capacity of each renewable energy resource component, for the
specific period of time, the variable selling price range at which
each renewable energy resource is to be sold, and the
meteorological conditions forecast, and the power settlement module
having a transaction resolution component configured to resolve a
final price at which each renewable energy resource will be
purchased by the intelligent power distribution network from the
multi-resource offshore renewable energy installation for the
specific period of time and a production, transmission, and
delivery component configure to arrange a power transfer from the
multi-resource offshore renewable energy installation over a
high-voltage direct current transmission system for distribution by
the load control component to each microgrid in the intelligent
power distribution network by communicating, through a
communications component, instructions to the power generation
module to produce power and to the power transmission module to
transmit power. the power transmission module having one or
components configured to initiate the power transfer responsive to
instructions from the power settlement module, operate a plurality
of voltage source converters coupled to power output circuits of
each renewable energy resource component that provide a
substantially constant voltage level for connection to a common
direct current bus in the high voltage direct current transmission
system, and monitor the power output circuits and voltage source
converters to ensure that the power requirement is being satisfied.
The offshore multi-resource renewable energy installation including
a wind component comprising at least one wind turbine, a
photovoltaic component comprising at least one photovoltaic module,
a hydrokinetic component comprising at least one of a surface wave
turbine, an oscillating column, and an undersea wave turbine, and a
solar thermal energy component comprising at least one
high-temperature solar thermal collector, each of the wind
component, the photovoltaic component, the hydrokinetic component,
and the solar thermal energy component having a separate renewable
energy resource component control system coupled thereto to
independently and variably operate each of the at least one wind
turbine, the at least one photovoltaic module, the at least one of
a surface wave turbine, an oscillating column, and an undersea wave
turbine, and the at least one high-temperature solar thermal
collector responsive to instructions from the power generation
module to generate a specific amount of power balanced with the
power requirement of the intelligent power distribution network for
the specific period of time, that maximizes an efficient
operational capacity of each renewable energy resource component
generating the power requirement, and minimizes both a power
storage requirement at the multi-resource offshore renewable energy
installation and a power storage requirement at a receiving
location of the intelligent power distribution network.
[0018] In another embodiment of the present invention, a renewable
energy resource management system comprises an intelligent power
distribution network segregated into one or more microgrids each
separately coupled to the intelligent power distribution network so
that each is capable of being decoupled to provide power separately
thereto as needed, and each configured to distribute power to a
segment of customers of the intelligent power distribution network
in response to a power requirement of each segment of customers for
a specific period of time determined and communicated by a
microgrid control system managing each microgrid. The embodiment
also includes a load management module capable of communicating
with the intelligent power distribution network and an offshore
multi-resource renewable energy installation in a distributed
computing infrastructure in which a transfer of power from the
offshore renewable resource installation to the intelligent power
distribution network that satisfies only the power requirement as
needed by each microgrid and maximizes an efficient utilization of
each renewable energy resource component in a plurality of
renewable resource components available at the offshore
multi-resource renewable energy installation is settled, so that a
storage requirement of power generated at the offshore renewable
energy resource installation and a storage requirement of power
delivered to a receiving location prior to transmission to the
intelligent power distribution network is maintained at a minimum
amount, the efficient utilization of each renewable resource
component determined, for the specific amount of time, by a
meteorological condition forecasted for each resource at the
offshore multi-resource renewable energy installation as determined
by communicating with a first external network, a commodity
purchase price forecasted for each resource as determined by
communicating with a second external network, and a resource
availability forecasted for each resource as determined by
communication with a component control system managing each
renewable energy resource component. The plurality of renewable
resource components available at the offshore multi-resource
renewable energy installation include a wind component, a
photovoltaic component, a hydrokinetic component, and a solar
thermal collection component, each renewable resource component
operable to generate power from one or more output circuits coupled
to a plurality of voltage source converters and a common direct
current bus over which a combined power output that includes a
rectified alternating power output portion and a direct current
power output is provided for transmission to the intelligent power
distribution network over a sub-sea high voltage direct current
transmission link.
[0019] In another embodiment, the present invention discloses a
method of managing power distribution from a renewable energy
resource provider to an intelligent power distribution network. The
method comprises communicating with an intelligent power
distribution network to determine, over a specific period of time,
a power requirement of customers represented by a plurality of
microgrids each separately coupled to the intelligent power
distribution network and each continuously communicating a power
demand for the customers represented, and to determine a purchase
price range at which the power requirement will be purchased, the
price range calculated from a first commodity pricing forecast of
each renewable energy resource at a multi-resource offshore
renewable energy installation site, and to determine contractual
and regulatory requirements of each microgrid relative to the
purchase of power produced from one or more of the renewable energy
resources. The method also comprises communicating with components
representing each renewable energy resource at the offshore
multi-resource renewable energy installation to determine, for the
specific period of time, an efficient use of the components
representing each renewable energy resource including a wind
component, a photovoltaic component, a hydrokinetic component, and
a solar thermal collection component, based upon a forecast of
meteorological conditions relative to each renewable energy
resource at the multi-resource offshore renewable energy
installation site, a selling price range at which the power
produced will be sold, the selling price range calculated from a
second commodity pricing forecast of each renewable energy resource
at the offshore multi-resource renewable energy installation site,
and availability of power produced from one or more of the
renewable energy resources based upon operating conditions at the
offshore multi-resource renewable energy installation. The method
also includes settling a transfer of the power requirement to the
intelligent power distribution network from the multi-resource
offshore renewable energy installation and instructing the
multi-resource offshore renewable energy installation to produce a
specific amount of power from each of the wind component, a
photovoltaic component, a hydrokinetic component, and a solar
thermal collection component, each component having one or more
power output circuits coupled to a plurality of voltage source
converters and a common direct current bus over which a combined
power output that includes a rectified alternating current power
output portion and a direct current power output is provided for
transmission of the power requirement to the intelligent power
distribution network over a high-voltage direct current
transmission system.
[0020] Other embodiments, features and advantages of the present
invention will become apparent from the following description of
the embodiments, taken together with the accompanying drawings,
which illustrate, by way of example, the principles of the
invention.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0021] The accompanying drawings, which are incorporated in and
constitute a part of this specification, illustrate several
embodiments of the invention and together with the description,
serve to explain the principles of the invention.
[0022] FIG. 1 is a system diagram of a renewable resource energy
management system according to one embodiment of the present
invention;
[0023] FIG. 2A is a conceptual diagram of components in a power
distribution module in a renewable resource energy management
system;
[0024] FIG. 2B is a conceptual diagram of components in a power
generation module in a renewable resource energy management
system;
[0025] FIG. 2C is a conceptual diagram of components in a power
settlement module in a renewable resource energy management
system;
[0026] FIG. 2D is a conceptual diagram of components in a power
transmission module in a renewable resource energy management
system;
[0027] FIG. 3 is a system diagram of an electricity grid
infrastructure according to another embodiment of the present
invention;
[0028] FIG. 4 is a system diagram of a multi-resource offshore
renewable energy installation according to another embodiment of
the present invention;
[0029] FIG. 5 is a diagram of power output circuits from a
multi-resource offshore renewable energy installation connected to
a power transmission system according to the present invention;
[0030] FIG. 6 is a perspective plan view of a multi-resource
offshore renewable energy installation and electricity grid
infrastructure according to one embodiment of the present
invention; and
[0031] FIG. 7 is a top plan view of a multi-resource offshore
renewable energy installation and electricity grid infrastructure
according to one embodiment of the present invention.
DETAILED DESCRIPTION OF THE INVENTION
[0032] In the following description of the present invention
reference is made to the accompanying figures which form a part
thereof, and in which is shown, by way of illustration, exemplary
embodiments illustrating the principles of the present invention
and how it is practiced. Other embodiments will be utilized to
practice the present invention and structural and functional
changes will be made thereto without departing from the scope of
the present invention.
[0033] The present invention discloses an energy management system
and method for power transmission to an intelligent electricity
grid from a multi-resource renewable energy platform, an offshore
multi-resource renewable energy installation and method of
maximizing its operational capacity, and a renewable energy-based
electricity grid infrastructure and method of its operation and
automation. Each of these embodiments achieves one or more of the
objectives of the present invention.
[0034] These include, but are not limited to, reducing costs of
producing power from renewable energy resources; maximizing
efficient operational capacity of multiple sources of power from
renewable energy in the same location; adapting power production to
power consumption to balance power loads and minimize or eliminate
the need for large-scale, expensive power storage components;
reducing dependency on non-renewable energy resources by
introducing large-scale power production to meet power demands
entirely from renewable resources; addressing and enhancing a
growing need for power grid infrastructure security, stability, and
reliability; providing power for future direct current-specific
electricity grids and different sources of power to different power
consumers as needed; enhancing electricity grid infrastructure
automation, optimization, risk and outage management, self-checking
and self-healing; and integrating distributed grid and cloud
computing into the broader infrastructure for producing,
transmitting, distributing, and delivery power.
[0035] The present invention also provides a framework within which
a consistent flow of power can be delivered as needed while
minimizing the impact of fluctuations that results in peaks and
valleys. The present invention also allows power from renewable
energy resources to be bought and sold at the low cost and high
profit by aggregating multiple variables to make sure
power-producing assets operate efficiently. Within this framework,
available power-producing assets do not need to all be operated at
the same time or at the same speed, and power is produced from
substantially the most efficient available assets.
[0036] FIG. 1 is a system diagram of a renewable resource energy
management system 100 according to one embodiment of the present
invention. The renewable energy resource management system 100 is
configured to, in one aspect, arrange a power transaction between a
buyer and a seller of power. The "buyer" is an intelligent power
distribution network 102, which may comprise a portion of one or
more electricity grids, each of which is composed of a plurality of
microgrids 108. Each microgrid 108 serves a plurality of power
customers 112 who are at least communicatively coupled thereto. The
"seller" is one or more multi-resource offshore renewable energy
installations 104 at least comprising several renewable energy
resource components 116 capable of generating power from multiple
sources of renewable energy 114. Many multi-resource offshore
renewable energy installations 104 may be coupled together and
included with the scope of the present invention, so that for
example ultra-large offshore energy "farms" can be connected
together to meet the power needs of the intelligent power
distribution network 102 or electricity grid infrastructure
300.
[0037] Each renewable energy resource component 116 comprises of a
plurality of apparatuses and systems which perform the work
necessary to produce power. Each of these renewable energy resource
components 116, and each apparatus and system therein, are
separately controllable and are independently and variably operable
to provide a power requirement 144 as determined and instructed by
the intelligent power distribution network 102.
[0038] The renewable resource energy management system 100 provides
a "network of networks" approach to electricity grid architecture
with distributed master control capabilities and a wide-area
communications infrastructure that integrates electricity grid
automation and optimization concepts with balancing power
production to power consumption and maximizing efficiency of power
production from renewable energy resources. The renewable resource
energy management system 100 is hosted within a distributed
computing infrastructure 150 which includes one or more multiple
interconnected computing networks 152. System of modules and
control systems within the present invention that manage and
process data flow, communicate, and provide the necessary input and
output signals to perform the various functions discussed herein
are resident within this distributed computing infrastructure 150,
which may be thought as incorporating cloud and/or grid computing
principles to provide the operating environment for the present
invention.
[0039] The renewable resource energy management system 100 includes
a modular load management system having plurality of modules each
responsible for one or more functional aspects of the present
invention. These include a power distribution module 200
responsible for managing the intelligent power distribution network
102 through a plurality of components, such as a load control
component 202, a renewable energy resource pricing and conditions
component 204, and a communications component 206. A power
generation module 208 is responsible for managing the
multi-resource offshore renewable energy installation 104, and also
includes a plurality of components, such as a renewable resource
efficiency component 210, a renewable resource control component
212, and a communications component 216. A power settlement module
218 is responsible for managing actions and communications between
the intelligent power distribution network 102, the multi-resource
offshore renewable energy installation 104, and a transmission
system 106, one such action being to arrange a transfer of power
from the multi-resource offshore renewable energy installation 104
to the intelligent power distribution network 102. The power
settlement module 218 includes a transaction resolution component
220, a power production, transmission and delivery component 222,
and a communications component 224. The plurality of modules
further includes a power transmission module 226, responsible for
managing the transfer of the power requirement 144 to the
intelligent power distribution network 102. The power transmission
module 226 also includes several components, such as a voltage
source converter component 220, a transmission control component
228, and a communications component 234.
[0040] At least because of the distributed nature of its master
control capabilities, the renewable energy resource management
system 100 is capable of modular scalability so that many other
modules performing various functions may be added and integrated to
"plug in" through the distributed computing infrastructure 150.
Examples of modules that could be supported by the scalability of
the present invention include, but are not limited to, data storage
modules capable of accumulating large amounts of data inherent in
such systems, and billing modules providing applications such as
calculation of the complex charges and credits associated with
time-sensitive purchases and sales of power from renewable energy.
It is therefore contemplated that any number of modules, performing
functions of any type, from high-level system to
specifically-designed tasks, may be integrated into the renewable
energy resource management system 100.
[0041] Communications components 206, 216, 224, and 234 are
configured to communicate data within the renewable resource energy
management system 100 and the distributed computing infrastructure
150 using high-capacity wireless broadband networks that enable
high-speed multi-directional Internet protocol communications.
Wireless broadband networks may be of any technical type, such as
for example standards-based technologies like WiMAX, within which
various computing networks are capable of operating, such as field
area networks and SCADA systems. Frequency spectrums for wireless
broadband communications may be licensed or unlicensed in the
present invention. In one embodiment, the privately-hosted and
shared distributed computing infrastructure 150 may utilize one or
more licensed, private spectrums as one means of enhancing
communications security in the present invention.
[0042] The intelligent power distribution network 102 includes the
plurality of microgrids 108, each of which are responsible for one
or more activities, including communicating with power customers
112 coupled thereto. Each microgrid 108 has at least one controller
and a microgrid control system 110, which models data flow between
each microgrid 108 and each of its power customers 112, with each
device, meter, or other apparatus or system coupled to each power
customer 112 capable of predicting and/or determining customer 112
power usage and needs. Examples of such devices include "smart"
power meters which have resident controllers capable of analyzing
and communicating each customer's patterns to microgrids 108 and/or
microgrid control systems 110.
[0043] FIG. 2A is a conceptual diagram of components in a power
distribution module 200 according to the present invention. The
power distribution module 200 is a series of processes performed
across one or more processors within the renewable resource energy
management system 100 and is responsible for various
distribution-side functions. The load control component 202 of the
power distribution module 200 is configured to perform multiple
functions within the distributed computing infrastructure 150. One
such function is to forecast a power requirement 144 of the
intelligent power distribution network 102 over any specific or
given period of time. This is performed at least in part by
continually assessing power demand 146 of all microgrids 108
forming the intelligent power distribution network 102, through
communications with each device, apparatus, or controller coupled
to each power customer 112, and components of each microgrid 108.
The load control component 202 may perform this continual
assessment in a number of ways, such as by requesting data from
controllers configured to determine multiple data sets from each
apparatus, device or customer 112. This may also be performed by
requesting data from each microgrid 108 via its microgrid control
system 110.
[0044] The load control component 202, and each microgrid 108 and
microgrid control system 110, are capable of bi-directional
communications with each device, apparatus, or customer 112 to
perform "push" capabilities to send instructions thereto to perform
one or more tasks. This may be the case where the load control
component 202 and microgrid 108 wish to add or remove devices,
apparatuses, or customers 112. This may also be the case where the
load control component 202 and microgrid 108 have a need to suspend
operation of a particular device, apparatus or customer 112 for a
specific reason. One example of this is a customer 112 who is a
semiconductor manufacturing plant requiring a specific level of
power--where the load control component 202 and/or microgrid 108
sense a voltage spike is about to occur with that customer 112,
power delivery can be re-routed so that the voltage spike is
avoided and systems coupled to the semiconductor plant are not
damaged. It is therefore contemplated that the load control
component 202 and/or each microgrid 108 and microgrid control
system 110 are fully capable of pushing signals to devices,
apparatuses, and customers to perform specific tasks within the
power distribution module 200.
[0045] The power demand 146 is comprised of multiple variables
which form an overall picture of the power needs of each customer
112 over a specific period of time. The multiple variables are
influenced by the type of power customer 112 and any particular
power needs it may have, its history of power usage, and issues
like contractual or regulatory requirements, where applicable, that
impose certain limitations on what kind of power can be consumed,
and when. Power need may therefore be derived from an aggregation
of data reflecting different usage components, such as alternating
current, direct current, or both, a usage type, such as for example
a semiconductor manufacturing or a plant or a high-security public
infrastructure building, and any fluctuation tolerance over the
specific period of time at issue which may influence load
variances, such as where the number and type of devices requiring
power changes over the specific period of time. It is to be
understood that many variables exist and many different examples
may be used to explain that power needs may be derived from complex
modeling of various systems.
[0046] The load control component 202 is also configured to manage
a delivery of the power requirement 144 to each microgrid 108 in
response to the continuing assessment of power demand 146 of each
microgrid. This is performed in conjunction with communications
with critical distribution-side delivery infrastructure such as
receiving locations, transformers, sub-stations, and the like that
serve as power intake points from the transmission system 106.
[0047] Based on the power need of each customer 112, the load
control component aggregates the power demand 146 of each microgrid
to arrive at the forecasted power requirement 144 that will
eventually be distributed for delivery across the entire
intelligent power distribution network 102 over the specific period
of time. The power requirement 144 will be both communicated to the
power settlement module 218 to arrange the transfer of power from
the multi-resource offshore renewable energy installation 104, and
to orchestrate, together with each microgrid 108, distribution of
the power network across the intelligent power distribution network
102.
[0048] The power requirement 144 is the result of mathematical
modeling of several factors, including multiple variables that
comprise the power need of each customer 112, and other factors
affecting the broader intelligent power distribution network 102,
such as higher-level electricity grid and microgrid topology that
influence usage type (alternating or direct current), usage
transmission distance to account for losses, and any fluctuation
tolerance, as well as other variables as noted herein, such as
regulatory and contractual requirements for using energy derived
from particular sources determined by another component of the
power distribution module 200. In this way, the modeling used to
arrive at the power requirement 144 permits scalability of the
present invention by incorporating input data from the both the
microgrid 108 level and the power customer 112 level, allowing
seamless integration of lower-level customers 112, additional
microgrids 108, and multiple large-scale electricity grids serving
large geographic areas as needed.
[0049] The load control component 202 is therefore responsible for
responding to peak demand loads through communications with each
microgrid 108 and/or each microgrid control system 110, as well as
managing and monitoring load distribution across the entire
intelligent power distribution network 102. This load control
framework enables many other critical grid infrastructure functions
attendant to load distribution, such as faster service restoration
in the event of outages or security issues, automatic re-routing of
power as needed, and generally ensuring a resilient, flexible grid
infrastructure.
[0050] The power distribution module 200 also includes a renewable
energy resource pricing and conditions component 204, which is
responsible for a different function of the power distribution
module 200--determining a commodity price range at which power from
each renewable energy resource 114 is to be purchased. In addition
to generating the forecasted power requirement 144, the power
distribution module 200 also provides the power settlement module
218 with this commodity price range.
[0051] Energy from renewable resources is a commodity often traded
between buyers and sellers on commodities markets and exchanges,
and commodity prices for each of the renewable energy resources 114
from which power is produced at the multi-resource offshore
renewable energy installation 104 vary widely over time for a
variety of reasons, such as for example weather conditions.
Therefore, in order to facilitate a cost-effective purchase price
for the power requirement 144 to service the intelligent power
distribution network 102, the renewable energy resource pricing and
conditions component 204 performs an assessment of commodity price
data for each renewable resource 114 available for providing the
power requirement 144 and forecasts a commodity purchase price
range at which each renewable energy resource 114 will be
purchased.
[0052] Additionally, power customers 112, and the intelligent power
distribution network 102 itself, may have certain purchasing
conditions related to contractual and regulatory requirements
obligating them to purchase energy from particular renewable energy
resources at particular times and in particular quantities, such as
for example commodity price signals, or other conditions such as
tariffs. These purchasing conditions may impose additional
constraints on the amount and purchase price of each renewable
energy resource 114. Purchasing conditions data may be available
from a variety of sources--such as from an external database
maintaining such requirements, or any other internal or external
source. Regardless, the renewable energy resource pricing and
conditions component 160 is responsible for accumulating this
information and incorporating it into models for purchases of power
relative to each renewable energy resource 114.
[0053] The renewable energy resource pricing and conditions
component 204 performs one or more processes to model the commodity
price data for each renewable energy resource 114 and account for
any purchasing conditions, and arrives at the forecasted commodity
purchase price range at which reach renewable resource will be
purchased for the specific period of time. The renewable energy
resource pricing and conditions component 204 may also take into
account meteorological conditions in the area where the
multi-resource offshore renewable resource installation 120 is
located in arriving at this forecast. The forecasted commodity
purchase price range is then communicated, via the communications
component 206, to the power settlement module 218.
[0054] In order to access at least commodity price data and
meteorological data, the renewable energy resource pricing and
conditions component 204 communicates with one or more external
computing networks 154 that are outside the distributed computing
infrastructure 150. In the case of commodity prices for each
renewable energy resource 114, the renewable energy resource
pricing and conditions component 204 may access one or more energy
commodity trading platforms 160 to determine the purchase price
range for each renewable energy resource 114 for the specific
period of time. The owner or operator of one or more electricity
grids and/or microgrids 108 coupled to the intelligent power
distribution network 102 may also buy, sell, or trade, financial
instruments allowing the power distribution module 200 to hedge, or
control, exposure to price fluctuations in the commodity price data
for each renewable energy resource 114. Similarly the renewable
energy resource pricing and conditions component 204 may access one
or more meteorological weather platform or site 162, and one or
more purchasing conditions database 164. Regardless, the power
distribution module 200 is to be understood to include the
capability to communicate with one or more external computing
networks 154 to accomplish forecasts of commodity price data,
meteorological conditions, and where applicable, include purchasing
conditions from contractual and regulatory requirements of each
microgrid 108 and/or power customer 112 in those forecasts.
[0055] The communications component 206 is at least responsible for
communicating data to the power settlement module 218, within the
power distribution module 200, and with the one or more external
computing networks 154. The data to be communicated to the power
settlement module 218 includes the power requirement 144, the
commodity purchase price range at which the power requirement 144
will be purchased for each renewable energy resource 114 available
at the multi-resource offshore renewable energy installation 104,
and any purchasing condition relative to the purchase of power from
renewable energy resources 114. The communications component 160
includes one or more processes and circuit elements configured to
aggregate various data inputs and transmit the resulting aggregated
data incorporating the power requirement 144, the commodity
purchase price range, and any purchasing condition within the
distributed computing infrastructure 150. The communications
component 206 therefore incorporates logic elements to ensure
incoming data from the load control component 202 and the renewable
energy resource pricing and conditions component 204 is in a form
that can be utilized by the power settlement module 218 to settle a
transfer of the power requirement 144 in accordance with the
present invention.
[0056] FIG. 2B is a conceptual diagram of components in a power
generation module 208 according to the present invention. The power
generation module 208 is a series of processes performed across one
or more processors within the renewable resource energy management
system 100 and is responsible for various production-side functions
governing operations in the multi-resource offshore renewable
energy installation 104. The power generation module 208 includes a
renewable resource efficiency component 210, a renewable resource
control component 212, and a communications component 216.
[0057] The renewable resource efficiency component 210 is
configured to perform multiple tasks. One such task is to
continually assess commodity prices for each renewable energy
resource 114, and forecast a commodity selling price range for each
renewable energy resource 114. Further, the renewable resource
efficiency component 210 continually assesses, and forecasts,
meteorological conditions at the location of the multi-resource
offshore renewable energy installation 104 to help determine the
ability of each renewable resource component 116 to operate over
the specific period of time. This meteorological conditions
forecast is also incorporated into the commodity price selling
range. Both the commodity price selling range and the
meteorological conditions forecasts are determined relative to the
specific period of time, which is communicated from the power
settlement module 218 via the communications component 216.
[0058] As with the power distribution module 200, in order to
access commodity price data and meteorological conditions data, the
renewable energy resource efficiency component 210 must communicate
with one or more external computing networks 154 that are outside
the framework of the distributed computing infrastructure 150. The
communications component 224 facilitate the use of the one or more
external computing networks 154 that allow the renewable resource
efficiency component 210 to access the one or more energy commodity
trading platforms 160, the one or more meteorological weather
platform or site 162, and the one or more purchasing conditions
database 164 to accomplish forecasts of commodity price data and
meteorological conditions. It is also possible that the operator of
the multi-resource offshore renewable energy installation 104 may
buy, sell, or trade, financial instruments allowing the power
generation module 208 to hedge, or control, exposure to price
fluctuations in the commodity price data for each renewable energy
resource 114 over the specific period of time.
[0059] The renewable energy resource control component 212 is
configured to continually assess an operational availability and
power capacity 148 of each renewable energy resource component 116
at the multi-resource offshore renewable energy installation 104.
This is performed through renewable energy resource control systems
214 each at least controlling one of the renewable energy resource
components 116. It is further contemplated that each apparatus
within each renewable energy resource component 116 may also have a
dedicated control sub-system controlling the specific apparatus and
responsive to output data from the renewable resource control
system 214.
[0060] Each apparatus in each renewable energy resource component
116 has a controller coupled thereto capable at least of operating
the apparatus to produce power, and to provide input data to either
or both of the control sub-system for the apparatus and the
renewable resource control system 214 responsible for the
respective renewable energy resource component 116. The renewable
energy resource control system 214 receives input data from each
controller of each apparatus and/or each control sub-system to
model the overall operational availability and power capacity 148
of each renewable energy resource component 116.
[0061] The renewable energy resource control component 212 uses
output signals from each renewable energy resource control system
214 to forecast a power production capacity 148 of each renewable
energy resource component 116 over the specific period of time. The
specific period of time is communicated from the power settlement
module 218 via the communications component 216. This power
production capacity 148 forecast is a function of at least the
operational availability of each renewable energy resource
component 116 as indicated in output signals of the renewable
energy resource control systems 214, and may also modulate those
signals with the forecasted meteorological conditions and commodity
pricing data relative to each renewable energy resource 114 at the
multi-resource offshore renewable energy installation 120 that are
communicated from the renewable resource efficiency component 210.
Therefore the power production capacity 148 reflects the
operational availability and a predicted level of operational
efficiency of each renewable energy resource component over the
specific period of time.
[0062] The renewable energy resource control component 212 also
receives incoming instructions from the power settlement module 218
following resolution of a transaction, to produce power responsive
to the power requirement 144 and the commodity prices of a
transaction settled therein. Either of the power settlement module
218 or the renewable energy resource control component 212 may
further determine the specific proportions or amount of power from
each renewable energy resource component to be produced for the
specific period of time. The renewable energy resource control
component 212 therefore is capable of determining an operational
efficiency level of power production capacity for each renewable
energy resource component 116 in response to instructions from the
power settlement module 118 and reflective of multiple variables,
such as the forecasted meteorological conditions and commodity
price data, as well as the power requirement 144 over the specific
period of time. Regardless, the renewable energy resource control
systems 214 then begin operating each apparatus as determined by
either the power generation module 208 or the power settlement
module 218. Power will therefore be produced from an efficient
combination of renewable energy resources that satisfies the power
requirement 144 and balances power production with the power to be
consumed by the intelligent power distribution network for the
specific period of time.
[0063] The communications component 216 is at least responsible for
communicating data to the power settlement module 218, within the
power generation module 208, and with the one or more external
computing networks 154. The data to be communicated to the power
settlement module 218 at least includes the power generating
capacity 148 of component 116, the commodity selling price range at
which the power requirement 144 will be sold for each renewable
energy resource 114 available at the multi-resource offshore
renewable energy installation 104, and the meteorological
conditions forecast. The meteorological conditions forecast may be
included regardless of whether it is represented within the
forecasted power capacity 148 of each renewable energy resource
component 116.
[0064] The communications component 216 is comprised of one or more
processes and circuit elements configured to aggregate and transmit
the data to be communicated to the power settlement module 218,
which incorporates the level of operation, the commodity selling
price range, and the meteorological conditions forecast, within the
distributed computing infrastructure 150. The communications
component 216 therefore also includes logic elements to ensure
incoming data from the renewable resource efficiency component 210
and the renewable resource control component 212 is in a form that
can be utilized by the power settlement module 218 to settle a
transfer of the power requirement 144 in accordance with the
present invention. The communications component 216 is also
responsible for communicating information from the power settlement
module 218 to the renewable resource control component 212 for
further input data to the renewable energy resource control systems
214.
[0065] It should be noted that the operator of the multi-resource
offshore renewable energy installation 104 may also have renewable
energy selling conditions relative to providing power from certain
renewable energy resources 114. It is therefore contemplated that
the renewable resource efficiency component 210 will be responsible
for assessing this information, and the communications component
216 will be responsible for integrating it into data communicated
to the power settlement module 218.
[0066] FIG. 2C is a conceptual diagram of components in a power
settlement module 218 according to the present invention. A power
settlement module 218 is another series of processes performed
across one or more processors within the renewable resource energy
management system 100 and is responsible for various global
functions, such as settling the sale and purchase of power
generated from each renewable energy resource 114 and arranging a
transfer of power from the multi-resource offshore renewable energy
installation 104 to the intelligent power distribution network 102
via the transmission system 106. The power settlement module 218
includes a transaction resolution component 220, a power
production, transmission and delivery component 222, and a
communications component 224. Within these components, the power
settlement module 218 communicates data to all of the power
distribution module 200, the power generation module 208, and the
power transmission module 226 regarding the transfer of power
requirement 144.
[0067] The transaction resolution component 220 at least performs
the function of comparing the commodity selling and purchase price
ranges from each of the power distribution module 200 and the power
generation module 208 and resolving a final price for power to be
generated from each renewable energy resource 114 for the specific
period of time to satisfy the power requirement 144. The final
price is communicated to both the power distribution module 200 and
the power generation module 208.
[0068] The transaction resolution component 220 also determines the
amount of power to be produced for each component 116 within the
power capacity 148 and relative to the power requirement 144 and
final price for power to be produced from each renewable energy
resource 114. The amount of power is contemplated to be expressed
in ranges of amounts that represent proposed levels of operation
for each component 116. This is communicated to the power
production transmission and delivery component 222, which generates
signals to the power generation module 208 to begin producing power
from the renewable resource components 116, to the power
distribution module 200 to begin preparing to deliver power to each
microgrid 108, and to the power transmission module 226 to begin
preparing for transmission.
[0069] The power settlement module 218 therefore communicates, via
the communications component 224, signals to the power generation
module 208 the amount of power to be generated from each of the
renewable energy resource components 116, responsive to which
renewable energy resources 114 have been purchased and in what
amounts the respective components 116 are to generate power. Each
renewable resource component control system 214 takes these signals
as input data to further determine which specific apparatus is to
generate power, and instructs each controller and/or sub-control
system in each specific apparatus to be used to operate. In this
manner, each renewable energy resource component 116, and indeed
each apparatus therein, can be independently and variably
controlled to produce the desired power requirement 144.
[0070] The power settlement module 218 also includes performs the
function of communicating start and stop instructions in one or
more signals to the power transmission module 226. These
instructions serve to prepare the power transmission module 226 and
its components and transmission control system 220 to prepare to
transmit the power being generated by the renewable energy resource
components 116.
[0071] FIG. 2D is a conceptual diagram of components in a power
transmission module 226 according to the present invention. The
power transmission module 226 is a series of processes performed
across one or more processors within the renewable resource energy
management system 100 and is responsible for various
transmission-side functions governing the transmission system 106
over which the power requirement 144 is to be sent. The
transmission system 106 is a high voltage direct current (HVDC)
system that includes a common direct current bus to which a system
of voltage source converters (VSCs) 156 and each power output
circuit 142 of each apparatus is coupled. The power transmission
module 226 includes a transmission control component 228, which
receives signals from the power settlement module 218 via a
communications component 234 as input data instructive of several
processes to be performed in the transmission of the power
requirement 144. The transmission control component 228 includes a
transmission control system 230 which performs system check
functions such as monitoring the power outputs of each apparatus
for any over-production or under-production of power and suggesting
adjustments to the renewable energy resource control systems 214,
and also ensures that power production matches the capacity of the
HVDC transmission system 106. The transmission control component
228 also is responsible for beginning and ending power transmission
over the specific period of time.
[0072] The power transmission module 226 includes a voltage source
converter (VSC) component 232 configured to operate and monitor the
system of voltage source converters 156 coupled to the power output
circuits 142 of each apparatus in the renewable energy resource
components 116. The VSC component 232 helps to ensure that each
apparatus and each renewable energy resource component 116 produces
the desired output by adjusting the voltage step-up, voltage
step-down, and rectification components of the system of voltage
source converters 156 in response to signals communicated from the
power settlement module 218 and also from output data of the
transmission control component 228.
[0073] The power transmission module 226 also includes a
communications component 234 which includes one or more processes
and circuit elements configured to manage communications and
operations within, to and from the power transmission module 226.
This includes receiving and processing data from the power
settlement module 218 to activate the system of voltage source
converters 156 through the VSC converter component 232, and
providing input data for the transmission control system 230 and
initiating starts and stops in the HVDC transmission system 106
through the transmission control component 228.
[0074] The present invention includes at least three types of
control systems--the microgrid control systems 110, the renewable
energy resource control systems 214, and the transmission control
systems 230. Each of the microgrid control systems 110, the
renewable energy resource control systems 214, and the transmission
control system 230 operate within the distribute computing
infrastructure 150 to receive input data from various sources as
discussed herein, mathematically model physical systems to be
analyzed, and produce specific output signals that help to operate
the renewable energy resource management system 100 to generate the
power requirement 144 over the specific period of time to achieve
one or more objectives of the present invention.
[0075] Each microgrid control system 110 is responsible, in
conjunction with the load control component 202, for controlling
each microgrid 108 and each power customer 112 coupled to each
microgrid. Because of the decoupled nature of each microgrid 108,
there must be a dedicated system capable of performing one or more
control functions, such as assessing the power demand 146 of each
microgrid 108, managing power delivery to each customer 112 of the
microgrid 108, decoupling each microgrid 108 to assume control over
distribution and delivery where the need arises, and determining
and pushing instructions to each device, meter, or customer 112 if
needed. Each microgrid control system 110 receives as input data
signals from multiple sources and models several different systems
to produce output signals to perform these functions.
[0076] To determine power demand 146, for example, each microgrid
control system 110 receives input data from the one or more power
customers 112 coupled to each microgrid 108. This input data may be
generated and communicated by customers 112 themselves, by
microgrid controllers operable to collect usage data, and by one or
more devices having controllers thereon and coupled to each
customer 112. The usage data may be requested by the microgrid
control system 230 or communicated automatically via communications
component 206.
[0077] Collectively, this usage data reflects many different
variables, such as customer type, importance level, specific
requirements, usage history, usage type, any fluctuation tolerance,
and a number and type of devices used by each customer 112. The
microgrid control system 110 performs system modeling with these
variables for its microgrid 108 and generates an output signal to
the load control component 202 indicative of, for the specific
period of time, the power demand 146 for that microgrid 108.
[0078] Each microgrid control system also receives input data in
signals from the load control component 202 that includes the
amount of power to be delivered to the intelligent power
distribution network 102 and compositions that power delivery will
have with regard to renewable energy resources 114, such as for
example alternating current or direct current. The microgrid
control systems 110 perform system modeling of this data to
determine a most appropriate distribution across the customers 112
coupled to each microgrid 108, and generates output signals that
instruct one or more infrastructure components such as receiving
stations, substations, transformers, and other such components how
and where to distribute and delivery power to microgrids 108 and
customers 112.
[0079] This has particular import in the case of decoupling of
microgrids 108. Each microgrid control system 110 is responsible
for decoupling each microgrid 108 as the need arises. In this
embodiment, the microgrid control system 110 receives input data in
a signal from the load control component 202 to decouple and
continue to distribute and deliver power to one or more of the
microgrids 108 as directed. Similar to above, the microgrid control
system 110 analyzes this input signal with the modeled system of
the decoupled microgrid 108, and determines a most appropriate
distribution across customers 112 who are to continue receiving
power.
[0080] Each renewable energy resource control system 214 is
responsible for controlling each respective renewable energy
resource component 116 to which they belong. Each renewable energy
resource control system 214 receives input signals from on-board
controllers in each apparatus, comprised of data representing one
or more operational power capacity characteristics, such as for
example the type of apparatus, the time of day, recent performance
history, current operating condition, upcoming scheduled
maintenance, current weather conditions, and any other variable
effecting operability and availability. The renewable energy
resource control system 214 uses the input data to create a system
model of how each apparatus will perform over the specific period
of time, and generates an output signal for the renewable resource
control component 212 to generate a power capacity 148
forecast.
[0081] In the reverse direction, each renewable energy resource
control system 214 receives an input signal comprised of data
representing instructions from renewable energy resource control
component 212 for operation of each renewable energy resource
component 116. The renewable energy resource control system 214
responsible for each component 116 then models each component 116
with the input data to determine output characteristics regarding
operating each component, such as which apparatus(es) to operate to
generate power, at what speed and capacity, for how much time, and
in what combination. This information is contained within output
signals generated for each component 116 and each controller in
each apparatus.
[0082] The transmission control system 230 performs a system of
checks to ensure proper functioning of both the power outputs of
each renewable energy resource component 116 and the HVDC
transmission system 106. The transmission control system 230
receives input data in signals from the power output circuits 142
of each apparatus or each renewable energy resource component 116
or both, prior to connection with the system of voltage source
converters 156. The transmission control system 230 compares this
data with information from both the power generation module 208 and
the power settlement module 218 regarding the known power
requirement 144 to determine whether or not power is being
under-produced or over-produced. One of two outcomes are decided
upon--in the case of a match, the transmission control system 230
does nothing and continues onto the next system check. In the event
of a power over or under-production, the transmission control
system 230 generates an output signal to one or more of the
renewable energy resource control systems 214 to adjust power
output up or down. In this way, the transmission control system 230
acts as a feedback loop to one or more of the renewable energy
resource control systems 214.
[0083] The transmission control system 230 also receives input
signals from the output circuits of each voltage source converter
156 after voltage has been stepped or down in response to signals
from the VSC component 232. The transmission control system 230
models the voltage source converter 156 output data with known
tolerance characteristics of either or both of the power
requirement 144 and the HVDC transmission system 106, and
determines whether or not voltage levels are within expected
tolerances. If they are, the transmission control system 230 does
nothing and continues with the further system checks. If they are
outside expected tolerances, the transmission control system 106
generates an output signal to the VSC component 232 to adjust
voltage step and voltage step down where needed in the voltage
source converter system 156.
[0084] The transmission control system 230 further receives data in
input signals relative to the power output from the common direct
current bus 158, and models this data with known load
characteristics of the HVDC transmission system 106. This modeling
is performed to ensure the power output being transmitted, either
in terms of total capacity or voltage levels, does not exceed the
load capacity of the HVDC transmission system 106. If there is a
mismatch where load capacity will be exceeded, an output signal is
generated either to one or more of the renewable energy resource
control systems 214 or to the VSC component 232 to make appropriate
adjustments as discussed above. The transmission control system 230
may also generate an output signal activating a power feedback loop
to remove excess capacity from the HVDC transmission system 106.
The power feedback loop may route excess capacity to storage in a
temporary battery or to an installation sub-station configured to
provide power to the one or more of the renewable energy resource
components 116 or to another component area of the multi-resource
offshore renewable energy installation 104.
[0085] FIG. 3 is a system diagram of an electricity grid
infrastructure 300 according to another embodiment of the present
invention. The electricity grid infrastructure 300 comprises an
intelligent power distribution network 102 as part of a renewable
energy-based electricity grid that comprises of one or more
microgrids 108 each having a power customer 112 coupled thereto, a
multi-resource offshore renewable energy installation 104, an HVDC
transmission system 106, and in one aspect, a distributed
management system 302 configured to perform one or more functions
such as settling a transaction in which power consumption is
substantially balanced to power production.
[0086] Use of the term "intelligent power distribution network"
herein implies that portion of the electricity "grid" which
consumes power delivered from any number of sources. Conventional
electricity or power "grids" are interconnected networks configured
to deliver electricity from suppliers to consumers, or in other
words, from sellers to buyers. Typical grids include generating
components that produce electricity, transmission components that
carry electricity from supplier to receiving locations, and
distribution components that carry out activities necessary to
ensure that electricity is delivered in the form needed to
consumers. Current electricity grid infrastructure is aging and in
substantial need of improvement to keep up with a myriad of issues
such as increased power demand, instability from fluctuations in
power flow, sophisticated end-use technologies, and escalating
security concerns.
[0087] The electricity generation portion of a typical grid
topology includes generating plants, which act as sellers, that
connect to the transmission portion to move power across distances.
The transmission portion connects the sellers with buyers, which
are wholesale customers such as companies or municipalities
responsible for distribution of power to consumers, to transfer
power. Distribution of power involves many different technologies,
such as for example substations, transformers, and power lines that
ultimately deliver power to end users.
[0088] One type of electricity grid is a "smart" grid which is
capable of predicting behavior of power consumers to achieve policy
objectives such as enhancing infrastructure stability, reducing
peak demand, and managing overall energy consumption and
infrastructure performance. Smart electricity grids do this by
attempting to increase automation and communication between the
various infrastructure components.
[0089] An intelligent power distribution network 102 of an
electricity grid infrastructure 300 according to the present
invention may be thought of in a number of ways. It may be
comprised of one or more electricity grids, and also as (or instead
as) composed of one or more smaller micro-electricity grids, or
microgrids 108. Microgrids 108 may represent many different aspects
of the overall consumptive framework of the intelligent power
distribution network 102. For example, microgrids 108 may be
configured to represent different customers or consumers 112 of
power which is delivered to the overall intelligent power
distribution network 102, such as different types of consumers,
consumers in different geographical locations, consumers with
specific and similar power needs, consumers for whom delivery of
power is a public security issue, etc.
[0090] The term "microgrid" is usually understood to mean a subset
of an area within a utility grid, and most often, areas embedded in
local or small-scale electricity environments, such as buildings or
neighborhoods. The term is also often used to refer to micro-site
generation of power particular resources, such as solar panels
mounted on buildings.
[0091] Microgrids 108 as contemplated by the present invention are
expanded to be areas not necessarily limited by geographical
region. Instead, microgrids 108 according to the present invention,
while remaining subsets of the larger utility grid, may be separate
systems that are coupled to, and capable of being decoupled from,
the larger utility grid so that power can be separately delivered
thereto. Microgrids 108 may also be allocated for any type of power
consumer 112, in any location, and relative to any reason for
segregating the broader utility grid into smaller microgrids
108.
[0092] It is to be understood that regardless of the embodiment
referenced, the present invention contemplates that the one or more
smaller microgrids 108 which comprise the intelligent power
distribution network 102 are separately configured so as to be
decoupleable from the intelligent power distribution network 102 as
the need arises. Such a decoupling could be performed for many
different reasons as discussed herein. Microgrids 108 may also be
comprised of one or more sub-microgrids that are configured to
communicate power needs of specific things that comprise the
broader microgrid 108 to which they are a part. The present
invention also contemplates that microgrids 108 can be formed,
dissolved, and reconfigured at any time by one or more of the
modules and microgrid control systems 110 disclosed herein.
[0093] Microgrids 108 therefore have utility in a variety of ways
within the present invention. In addition to ensuring that a
real-time power requirement 144 is discerned and supplied over a
specific time period, other utilities include ensuring grid
infrastructure security and providing specific types of power to
different microgrids 108 that need such specialized service.
Examples of this are microgrids representing semiconductor-based
facilities that specifically requires direct current-based power,
and microgrids representing specific components of the intelligent
power distribution network itself, such as receiving locations 236,
substations, relays, and transformers. Regardless, each microgrid
108 is connected through at least one computing network 152 to
perform the variety of task as discussed herein. For example, a
microgrid 108 representing a residential neighborhood would be
configured to communicate, using one or more interconnected
computing networks 152, the neighborhood's power needs, based on
signals received from and/or sent to one or more devices capable of
reading, calculating, and predicting the real-time power needs of
each resident of the neighborhood.
[0094] One example of an intelligent power distribution network 102
is an electricity grid that is responsible for supplying power to
the entire western United States. Such an intelligent power
distribution network 102 would be comprised of many microgrids 108
that represent each sub-region, state, or city in that geographical
area, and within that, microgrids 108 that represent specific types
of power consumers 112. Each of these microgrids 108 would be
separately coupled to the intelligent power distribution network
102 so that power requirement 144 for each would be delivered
according to the load control component 202 and a respective
microgrid control system 110. In this embodiment, the distributed
load management system 302 of the electricity grid infrastructure
300 is responsible coordinating a power delivery to each microgrid
108 together with the microgrid control system 110 in an amount
that satisfies real-time needs.
[0095] Infrastructure security is easily facilitated by the
microgrid 108 framework according to the present invention. A
microgrid 108 may be representative of key public infrastructure
installations, such as for example ports, military sites, water
installations such as reservoirs and dams, high-speed rail lines,
canals, metro systems, other power generation facilities,
manufacturing and production facilities, etc. By allowing for the
immediate decoupling of a microgrid 108 in the event of security
issue with the overall intelligent power distribution network 102
or to another microgrid 108, power can be continually supplied to a
particular microgrid 108, and its represented customers 112 who
need power to keep public services smoothly operating in the event
of such a security issue.
[0096] The power distribution module 200, and the distributed load
management system 302, together with each microgrid 108 and with
each microgrid control system 11, coordinate and carry out any
decoupling as the need arises. It is therefore to be understood
that electricity grid topology according to the present invention
is integrated to support such an interconnected and coupled
framework that is at the same time capable of being fragmented in
real time to deliver power separately to specific microgrids 108
should the need arise
[0097] The present invention further contemplates that because
power is generated and transmitted entirely in direct current form
by the HVDC transmission system 106, it is possible for power to be
supplied to microgrids 108 requiring direct current directly
without having to process and transform incoming power at a
receiving location 236. This can be done, for example, in a
situation where the receiving location itself is under a security
threat. Microgrids 108 can be configured, via the power
distribution module 200, distributed load management system 302,
and microgrid control systems 110, to operate entirely on direct
current that can be supplied directly by the multi-resource
offshore renewable energy installation 104.
[0098] The present invention also further contemplates that an
intelligent power distribution network 102, and microgrids 108, may
be configured to either run entirely on direct current, or to be
able to easily switch from requiring alternating current to
requiring direct current as the need arises at receiving locations
236 or substations serving particular microgrids 108. For example,
in a security situation where the power transformation at the main
network-level receiving location 236 from direct current to
alternating current has been disabled, power can be delivered to
key microgrids 108 directly in direct current. It is contemplated
that a microgrid 108 may have the ability to switch its represented
customers 112 to a direct current model, either permanently or
temporarily, in such a situation.
[0099] Accordingly, electricity grid infrastructure 300 according
to the present invention is to be configured so that microgrids 108
can be quickly decoupled from the main intelligent power
distribution network 102 and supplied with direct current power via
the HVDC transmission system 106 in the event of an incident
requiring such a decoupling and continued supply of uninterrupted
power. In this way, the electricity grid infrastructure 300 is a
flexibly topology that is capable of expanding and contracting and
that supports resiliency and stability when problems that threaten
the supply of power arise.
[0100] As the world becomes increasingly dependent on non-renewable
and carbon-based energy resources, and substantial supply, price,
and geopolitical stability problems attendant thereto proliferate,
it is apparent that there is a strong need for a system and method
of providing power generated entirely from renewable energy
resources 114. In another embodiment of the present invention, a
multi-resource offshore renewable energy installation 104 and
method of operation provide an intelligent power distribution
network 102 with all of its power needs from one source that
generates energy from multiple renewable energy resources 114.
[0101] FIG. 4 is a system diagram of a multi-resource offshore
renewable energy installation 104. The multi-resource offshore
renewable energy installation 104 is an apparatus or series of
apparatuses that includes multiple renewable energy resource
components 116 for generating power that are each derived from a
particular renewable energy resource 114. The multi-resource
offshore renewable energy installation 104 is contemplated to be a
deep-ocean, marine installation at sites located far from land,
typically in the range of greater than 50 km from the nearest
onshore intelligent power distribution network 102. However, it is
within the scope of the present invention that such a
multi-resource offshore renewable installation 104 could be a
marine installation located near to the shore and also on
freshwater bodies such as lakes and rivers, whether naturally
occurring or man-made.
[0102] The multiple renewable energy resource components 116
include a wind component 118 deriving power from wind energy, a
solar component 122 deriving power from solar energy, a
hydrokinetic component 128 deriving power from wave and tidal
current energy, and a solar thermal component 136 deriving power
from the process of heating ocean water using solar thermal energy.
The present invention may also include an ocean thermal energy
conversion component 140. Each of the wind component 118, the solar
component 122, the hydrokinetic component 128, the solar thermal
component 136, and the ocean thermal energy conversion component
140 include an array of apparatuses each coupled to a respective
renewable energy resource control system 214.
[0103] In accordance with other aspects and embodiments of the
present invention, the multi-resource renewable energy installation
120 is configured so that a maximum efficient operational
power-generating capacity of each apparatus, and each renewable
energy resource component 116, is achieved. The multi-resource
offshore renewable energy installation 104 is therefore intended to
present a solution to the problem of inefficiencies that are
naturally present in renewable resource components 116 generating
power from resources such as wind, solar, hydrokinetic, and solar
thermal energy.
[0104] The present invention contemplates that there are numerous
ways in which components capable of generating power from multiple
renewable energy resources 114 can be configured on such
multi-resource offshore renewable energy installation 104. For
example, the installation may be a large-scale energy farm with
hundreds or thousands of apparatuses working to generate power.
Each of the components 116 may be configured in any number of ways
in such a large-scale energy farm to generate power and take
advantage of fluctuations in weather conditions. The multi-resource
offshore renewable energy installation 104 is therefore completely
scalable from an ultra-high capacity multi-megawatt or gigawatt
installation to serve large-scale power consumers 112, to a medium
to low-capacity installation to serve power consumers 112 with
smaller demand. FIG. 6 and FIG. 7 show overall perspective and top
plan views of embodiments of the multi-resource renewable energy
installation 104.
[0105] The multi-resource offshore renewable energy installation
104 may be both permanent and temporary and have both permanent and
temporary components 116 as portions thereof to achieve the
scalability contemplated herein. It may be entirely fixed so that
it anchors to the ocean floor and is therefore a permanent
installation. It may also be a floating structure, in whole or in
part, with temporary anchoring mechanisms and with some or all of
the components 116 being movable to other locations as needed. It
may further be a combination of permanent and temporary components,
for example in a configuration in which power transmission
components are in fixed portion while power generating components
116 are temporary components that can "dock," as in the case of one
or more barges having components installed thereupon, to the
permanent components or to other mobile components. Regardless of
possible configuration, the present invention considerably reduces
construction and operating costs by implementing technologies that
substantially reduce the possibility of lasting environmental
damage. With the present invention, there is no need to drill for
non-renewable carbon-based resources that may pollute environment
as such an installation site.
[0106] Costs can be further minimized due to the ability to
maximize operational power-generating capacity. In the present
invention, power production is substantially balanced with power
consumption, so that only an amount of power required is produced
over the specific period of time, at least in part because the
renewable energy resource control systems 214, responsive to
signals regarding settled transactions, can variably and separably
operate each apparatus within each component 116. Therefore,
present invention may not require large, expensive, and
environmentally damaging power storage components at either the
multi-resource offshore renewable energy installation 102 or the
intelligent power distribution network 102.
[0107] The multi-resource offshore renewable energy installation
104 may be a purpose-built semi-submersible production platform
that is a floating vessel capable of supporting the renewable
energy resource components 116 in multiple configurations in deep
water and other harsh offshore environments. This provides a mobile
yet stable operational platform needed to produce power at the
multi-resource offshore renewable energy installation 104 and that
is capable of being deployed in different locations, regardless of
whether each of the renewable energy resource components 116 are
permanently part of the multi-resource offshore renewable energy
installation 104 or removably and/or temporarily coupled thereto,
such as for example on separate pontoons or barges.
[0108] Stability in such a mobile semi-submersible platform
according to this embodiment results from, when in an operational
position, a hull structure being submerged at a deep draft so that
the multi-resource offshore renewable energy installation 104 is
less susceptible to wave loadings. Operational components of the
semi-submersible platform remain well above the ocean surface. The
mobile semi-submersible production platform acquires buoyancy from
ballasted components below the surface, and one or more support
columns connecting the operational components and the ballasted
components. Other anchoring components may also be utilized for
further stability of the mobile semi-submersible platform.
[0109] Draft can be adjusted by deballasting the below-surface
components so that the mobile semi-submersible production platform
becomes a surface vessel capable of deployment to a different
location. In this regard, a mobile semi-submersible production
platform as described may be transportable using a heavy-lift
installation transport vessel. Such a heavy-lift installation
transport vessel is able to move all or part of the installation
104 by ballasting itself to submerge a majority of its structure,
maneuvering beneath the multi-resource offshore renewable energy
installation 104, and then deballasting to lift up all or part of
the multi-resource offshore renewable energy installation 104 as
cargo.
[0110] In a further embodiment, where each of the renewable energy
resource components 116 are separately coupled to form the
multi-resource offshore renewable energy installation 104, the
installation 104 may also comprise one or more offshore support
vessels that perform various roles, such as operational activities,
transmission system support, and emergency support. Each such
vessel may be separately mobile so that the multi-resource offshore
renewable energy installation 104 is composed of many
interchangeable parts. Each renewable energy resource component 116
may itself be embodied on a mobile semi-submersible platform as
well. Therefore, the entire multi-resource offshore renewable
energy installation 104 can be thought of as a being deployable in
any configuration necessary to meet the objectives of the present
invention.
[0111] Offshore support vessels such as a transmission system
support vessel may be a key consideration for engineers and
planners in the mobile aspect of the semi-submersible production
platform that forms all or part of a multi-resource offshore
renewable energy installation 104. Transmission system support is a
consideration in order to ensure that regardless of where the
multi-resource offshore renewable energy installation 104 and/or
the multiple renewable energy resource components 116 are deployed,
access to the high voltage direct current transmission system 106
is available to transfer power to the intelligent power
distribution network 102. In one embodiment, vessels such as those
providing transmission system support may provide node-based
transmission cables for easy and remote access to a main undersea
transmission line, particularly where the multi-resource offshore
renewable energy installation 104 is mobile semi-submersible
production platform. The present invention therefore contemplates
that the multi-resource offshore renewable energy installation 104
may include a main operational platform, semi-submersible or
otherwise, where multiple mobile semi-submersible production
platforms connect to a main transmission line supported by such
offshore support vessels. Such a configuration permits the
multi-resource offshore renewable energy installation 104 to
include multiple mobile semi-submersible production platforms
supporting renewable energy resource components 116 that may be
spread out over hundreds of kilometers and connected by
transmission cables that are branches of the node at the main
operational platform.
[0112] The multi-resource offshore renewable energy installation
104 includes a solar component 118 for generating power from solar
energy. Components generating power from solar energy are known as
photovoltaics, which convert solar rays into electricity using
panels, or modules, composed of solar cells containing a
photovoltaic material. The present invention contemplates that the
solar energy component 118 is comprised of many such photovoltaic
modules 124 mounted on one or more mounting systems 126. Mounting
systems 126 may be either tracking or fixed mounting systems and
photovoltaic modules 124 may be mounted in any configuration
thereon, such as for example in portrait configuration or landscape
configuration, or any combination thereof.
[0113] The present invention contemplates that at least one of the
circuits connecting an array of photovoltaic modules 124, the
tracking mounting systems 126, and individual photovoltaic modules
124 include one or more controllers capable of sending input data
in signals to a renewable energy resource control system 214, as
well as capable of receiving signals therefrom. These controllers
are capable of moving or tilting an angle of inclination of each
array of photovoltaic modules 124 on a tracking mounting system 126
operable at the multi-resource offshore renewable energy
installation 104 in response to an output signal of a renewable
energy resource control system 214.
[0114] Therefore, one or more renewable resource control systems
214 are configured to control the photovoltaic modules 124 and
tracker mounting systems 126 and communicate with controllers
coupled to each to maximize operational capacity of the solar
component 118. Where control systems 214 operate to generate
responses in the photovoltaic modules 124 directly, it is
contemplated that control over specific photovoltaic modules and in
arrays of photovoltaic modules 124 as a whole are both within the
scope of the present invention. The controllers in each
photovoltaic module or in each array of photovoltaic modules 124
are configured, in one aspect, to communicate at least a real-time
operational ability and power capacity 148 of each photovoltaic
module or array of photovoltaic modules 124 and real-time sunlight
availability conditions, and in another aspect, to respond to
output signals generated by the control system 214 to perform a
host of actions, such as for example controlling power output
circuits 142 in response to instruction from the power settlement
module 218. Similarly, controllers in each tracking mounting system
126 are configured, in one aspect to, communicate at least a
real-time operational availability of each tracking mounting system
126 and real-time sunlight availability conditions, and in another
aspect, to respond to output signals generated by the control
system 214 to perform actions such as adjusting the angle of
inclination, or switching power generation circuits on or off where
multiple photovoltaic modules 124 are connected together
thereon.
[0115] Photovoltaic modules 124 are solid state devices that
typically generate a power output as direct current electricity.
Because of this, the power output of each array of photovoltaic
modules 124 can be provided directly to the system of voltage
source converters 156 and the common direct current bus 158 in the
HVDC transmission system 106, eliminating the need for further
components such as inverters to convert from one current form to
another. The HVDC transmission system 106 must still account for
variances in both the voltage output of each photovoltaic module or
array of photovoltaic modules 124 and with power outputs of other
components 116, depending on the output configuration, and
therefore the transmission control system 230 monitors the power
output of each as discussed here. The transmission control system
230 may act as feedback for the renewable energy resource control
system 214 where power output needs to be adjusted to ensure common
voltage levels across the common direct current bus 158, may
therefore generate an output signal to adjust one or more
components of the solar component 118 accordingly. The transmission
control system 230 may also monitor and instruct the system of
voltage source converters 156 to either step up the output voltage
or step down the output voltage as needed to ensure a uniform
voltage level across the common direct current bus 156. Regardless,
the present invention ensures that the power output is properly
monitored and adjusted for transmission, distribution and
delivery.
[0116] The present invention further contemplates that in this
manner, as with other renewable energy resource components 116,
both the power generation module 208, the renewable energy resource
control systems 214, transmission control system 230, and the
voltage source converters 156 allow for very flexible operation of
photovoltaic modules 124 to arrive at a proper power production
capacity that satisfies the power requirement 144 over the specific
period of time, as other systemic objectives such as transmission
system stability.
[0117] This flexibility allows for substantial design freedom in
selecting components. Solar cells forming photovoltaic modules 122
may be made of any material suitable for installation in deep-ocean
conditions so that the photovoltaic modules 122 are able to
maintain operating capacity in potentially difficult weather
conditions far from shore. Materials typically must have
characteristics matched to the spectrum of available light at the
installation site, but it is contemplated that where a large number
of photovoltaic modules 124 are installed at the multi-resource
offshore renewable energy installation 104, many different types of
photovoltaic modules may be combined and utilized to achieve
optimal efficiency.
[0118] In one embodiment, materials such as nanocrystalline silicon
in which the photovoltaic materials embedded with nanonparticles
may have particular utility in installations such as those
disclosed herein, where weather conditions make maintenance a
significant challenge. Nanoparticles may be further embedded with
components such as microcontrollers which are capable of
communicating certain operating conditions to the renewable
resource control system 214 responsible for the photovoltaic module
124, array of photovoltaic modules 124, and tracking mounting
system 126 having photovoltaic modules 124 installed thereon. Use
of photovoltaic modules 124 fabricated of materials of this type
may increase the ability to assess real-time operational
availability and real-time weather conditions, and increase overall
durability of the solar component 118.
[0119] Photovoltaic modules 124 and mounting systems 126 may be
either fixed or permanent components of the multi-resource offshore
renewable energy installation 104, or temporarily coupled thereto
so as to be mobile and deployable to different locations or as
needed. Regardless, an array of photovoltaic modules 124 may also
be part of a floating installation of renewable resource components
116, or a fixed installation with support that is permanently
anchored to the seabed. Floating installations do not require
permanent anchoring mechanisms and can be positioned, for example,
on pontoon-based supports or on barges, reducing the environmental
impact and increasing the scalability of the multi-resource
offshore renewable energy installation 104. Floating installations
may also be capable of being raised and lowered as needed to
protect photovoltaic modules 124 and mounting systems 126, and keep
them operational, in the event of storms, rough seas, very large
waves, or other adverse environmental conditions.
[0120] Cooling of photovoltaic modules 124 can be achieved from
winds at the installation site or from the ocean water itself,
particularly where ocean thermal energy conversion components are
implemented that produce desalinized water from heating ocean
water. Floating or temporary structures also provide the benefit of
allowing photovoltaic modules 124 to be installed and used to
generate power in locations, particularly very deep ocean waters,
where seabed anchoring is not feasible.
[0121] The wind component 118 is comprised of a plurality of
large-scale, large capacity, commercial high-speed wind turbines
120. Each wind turbine 120 includes a rotor with blades turning
about either a horizontal or vertical axis, and has a controller
resident within a nacelle, coupled to operational and
power-generating circuit elements. The present invention
contemplates that the wind component 118 is comprised of an array
of wind turbines 120 each coupled to a respective renewable energy
resource control system 214.
[0122] One or more of the renewable resource control systems 214
are configured to control the wind turbines 120 by receiving input
data from and sending output signals to controllers coupled to
operational and power-generating output circuits inside each
nacelle. They are configured, in one aspect, to communicate at
least a real-time operational availability and power capacity 148
of each wind turbine 120, and in another aspect, to respond to
output signals generated by control system 214 to perform a host of
actions, such as for example turning an power output circuit 142 on
or off, adjusting rotor speed, or where applicable, rotating each
rotor to maximize operations under changing wind conditions, in
response to instruction from the power settlement module 218.
[0123] Wind turbines 120 commonly generate a power output in
alternating current form. The power output of each wind turbine 120
therefore needs to be rectified to direct current prior to
connection to the common direct current bus 158, and voltage source
converters 156 adjust the voltage level with either voltage step-up
or step-down transformers to ensure a compatible voltage level.
Power outputs of all of the wind turbines 120, and the voltage
output level of the system of voltage source converters 156, are
monitored by the transmission control system 230, in addition to
the power outputs of all other apparatuses that are being operated
to generate power, to make further adjustments if necessary as
discussed herein.
[0124] If it is the case that power is generated as direct current,
no inverter is needed for connection of the power output circuitry
to the common direct current bus 158 and the HVDC transmission
system 106. The transmission control system 230 must still however
account for variances in the voltage of each such power output, and
therefore would monitor the power output and voltage source
converters 156 as above, in conjunction with power output of other
apparatuses of other renewable energy resource components 116 and
in conjunction with each renewable energy resource control system
214, and make adjustments accordingly.
[0125] The present invention further contemplates that in this
manner, as with other renewable energy resource components 116,
both the power generation module 208, the renewable energy resource
control systems 214, transmission control system 230, and the
voltage source converters 156 allow for very flexible operation of
the wind turbines 120 to arrive at a proper power production
capacity that satisfies the power requirement 144 over the specific
period of time, as other systemic objectives such as transmission
system stability.
[0126] This flexible operational approach allows for many different
configurations of the wind component 118 within the scope of the
present invention. For example, wind turbine rotors may be axially
rotatable to maximize capacity where wind direction changes over
time. One or more rotors on a wind turbine tower may also be
movable so that it can either function as a wind turbine 120 or
wave turbine 130 or 134 as further discussed herein. Multiple
rotors on each tower may be used for to function as power
generating devices for both sources, so that one rotor is a wind
turbine 120, while the other is a wave turbine 130 or 134.
[0127] As with photovoltaic modules 124, wind turbines 120 may be
coupled so as to be either a fixed or permanent components of the
multi-resource offshore renewable energy installation 104, or
temporarily coupled thereto so as to be mobile and deployable to
different locations or as needed. Regardless, an array of wind
turbines 120 may also be mounted on a floating structure that
allows each wind turbine 120 to generate electricity in deep ocean
waters where seabed anchors or piles are not feasible, or on a
fixed structure with support that is permanently anchored to the
seabed. The fixed structure may be the tower supporting the wind
turbine 118 itself. Floating installations do not require permanent
anchoring mechanisms and can be positioned, for example, on
pontoon-based supports or on barges, reducing the environmental
impact and increasing the scalability of the multi-resource
offshore renewable energy installation 104.
[0128] The hydrokinetic component 128 may include multiple types of
apparatuses, each of which utilize some type of wave conversion to
harness energy from movement of water, whether based on surface
waves, sub-surface currents, or tides, to generate electrical power
output. These wave energy conversion devices are well-suited for
deep water applications as disclosed herein, as deep water waves
and currents generate greater energy and therefore are more useful
at generating power in high-capacity installations. The present
invention includes at least one of surface wave turbines 130,
oscillating water columns 132 and sub-surface or undersea wave
turbines 134 within the hydrokinetic component 128.
[0129] The surface and sub-surface wave turbines 130 and 134 are
contemplated to be large-scale, large capacity, commercial turbines
each having a rotor with blades turning about either a horizontal
or vertical axis to generate power. Each turbine has a controller
resident within a nacelle, coupled to operational and/or
power-generating output circuits. Oscillating water columns 132
generate power as waves enter and exit a partially submerged
collector, causing a water column inside the collector to rise and
fall and drive air inside the column into a turbine. The turbines
have controllers coupled to operational and/or power-generating
output circuits therein. The present invention contemplates that
the hydrokinetic component 128 is comprised of an array of each of
the surface wave turbines 130, oscillating water columns 132, and
sub-surface wave turbines 134.
[0130] Each surface wave turbine 130, oscillating water column 132,
and sub-surface turbine 134 is coupled to one or more renewable
energy resource control systems 214 configured to control the
hydrokinetic component 128 and generate output signals to
controllers coupled to each surface wave turbine 130, oscillating
water column 132, and sub-surface turbine 134 to separably and
variably operable each apparatus. The controllers are configured,
in one aspect, to communicate at least a real-time operational
availability and power capacity 148 of each surface wave turbine
130, oscillating water column 132, and sub-surface turbine 134, and
in another aspect, to respond to output signals generated by the
renewable energy resource control system 214 to perform a host of
actions, such as for example turning power output circuits 142 on
or off, adjusting rotor speed, adjusting a water depth at which
ocean water is obtained in the case of the oscillation water
columns 130, or where applicable, rotating each rotor to maximize
operations under changing surface wave or ocean current conditions,
in response to instruction from the power settlement module 218.
Factors having substantial influence on operational availability
and power capacity 148 of each surface wave turbine 130,
oscillating water column 132, and sub-surface wave turbine 134, and
the ability to variably operate each, are meteorological conditions
such as surface wave and sub-surface ocean current strength, which
may be continuously measured at the offshore multi-resource
renewable energy installation 120.
[0131] The hydrokinetic components 128 are assumed to generate a
power output in alternating current form. Where this is the case,
the power output of each surface wave turbine 130, oscillating
water column 132, and sub-surface turbine 134 therefore needs to be
rectified to direct current prior to connection to the common
direct current bus 158, and voltage source converters 156 adjust
the voltage level with either voltage step-up or step-down
transformers to ensure a compatible voltage level. Power outputs of
all of the surface wave turbines 130, oscillating water columns
132, and sub-surface wave turbines 134, and the voltage output
level of the system of voltage source converters 156, are monitored
by the transmission control system 230, in addition to the power
outputs of all other apparatuses that are being operated to
generate power, to make further adjustments if necessary as
discussed herein.
[0132] If it is the case that power is generated as direct current,
no inverter is needed for connection of the power output circuitry
to the common direct current bus 158 and the HVDC transmission
system 106. The transmission control system 230 must still however
account for variances in the voltage of each such power output, and
therefore would monitor the power output and voltage source
converters 156 as above, in conjunction with power output of other
apparatuses of other renewable energy resource components 116 and
in conjunction with each renewable energy resource control system
214, to make adjustments accordingly.
[0133] The present invention further contemplates that in this
manner, both the power generation module 208, the renewable energy
resource control systems 214, transmission control system 230, and
the voltage source converters 156 allow for very flexible operation
of the surface wave turbines 130, oscillating water columns 132,
and sub-surface turbines 134 to arrive at the proper power
production capacity that satisfies the power requirement 144 over
the specific period of time, as well as transmission system
stability and other objectives.
[0134] This flexible operational approach allows for many different
configurations of the hydrokinetic components 128 within the scope
of the present invention. For example, surface or sub-surface wave
turbine rotors may be axially rotatable to maximize capacity where
wave or current direction changes over time. One or more rotors on
a turbine tower may also be movable so that it can either function
as a wind turbine 120 or wave turbine 130 or 134. Multiple rotors
on each tower may be used for to function as power generating
devices for both sources, so that one rotor is a wind turbine 120,
while the other is either a surface wave turbine 130 or a
sub-surface wave turbine 134.
[0135] The various apparatuses comprising the hydrokinetic
component 128 may also be coupled so as to be either a fixed or
permanent component of the multi-resource offshore renewable energy
installation 104, or temporarily coupled thereto so as to be mobile
and deployable to different locations or as needed. Regardless, any
of the surface wave turbines 130, oscillating water columns 132,
and sub-surface wave turbines 134 may also be mounted on a floating
structure that allows each apparatus to generate electricity in
deep ocean waters where seabed anchors or piles are not feasible,
or on a fixed structure with support that is permanently anchored
to the seabed. The fixed structure may also be a tower supporting a
surface turbine 130 or sub-surface wave turbine 134 itself.
Floating installations do not require permanent anchoring
mechanisms and can be positioned, for example, on pontoon-based
supports or barges, reducing the environmental impact and
increasing the scalability of the multi-resource offshore renewable
energy installation 104. Pontoons and barges floating on the ocean
surface may support any of the surface wave turbines 130,
oscillating water columns 132, or sub-surfaces wave turbines 134,
either separately or in combination.
[0136] A platform of multiple oscillating water columns 132,
whether floating or fixedly positioned, may also be capable of
being raised or lowered as necessary to protect the equipment to
keep them operational, such as in case of storms, rough seas, very
large waves, or other adverse environmental conditions. This helps
to ensure that waves are capable of entering and exiting the water
column 130 to ensure continued operation of this portion of the
hydrokinetic component 128, allow for easier maintenance, and to
ensure that damage does not occur.
[0137] The solar thermal component 136 utilizes thermal energy, or
heat, harnessed from solar energy. The solar thermal component 136
includes an array of high-temperature solar thermal collectors 138
that use lenses and mirrors to capture and intensify the sun's rays
to heat ocean water, which generates steam that drives a turbine
generator.
[0138] High-temperature solar thermal collectors 138 according to
this embodiment include intake systems through which ocean water is
collected and transported to be heated. These can be configured to
collect ocean water at variable water depths to maximize the
operational performance of each collector 138, since the
temperature of ocean water various according to depth, time of
year, current patterns, and other variables.
[0139] High-temperature solar thermal collectors 138 may be mounted
on tracking-type mounting systems to maximize operational
efficiency, so that the angle of tilt or inclination is moveable to
account for different positions of the sun at different times of
the day and year. Lenses and mirrors may also be mounted on movable
systems to increase the ability of each collector 138 to maximize
its operating efficiency. High-temperature solar thermal collectors
138 may be of any conventional design suitable for durable use in
deep-ocean, weather intensive environments. Typical conventional
designs include parabolic troughs, towers, parabolic dishes,
Fresnel reflectors, and other design capable of high-temperature
operation.
[0140] One or more renewable resource control systems 214 are
configured to control the high temperature solar thermal collectors
138, the system of mirrors and lenses, and the tracking mounting
systems on which both are mounted, and communicate with controllers
coupled to operational and power-generating output circuits. The
controllers are configured, in one aspect, to communicate at least
a real-time operational availability and power capacity 148 of each
apparatus and real-time sunlight availability conditions, and in
another aspect, to respond to output signals generated by the
control system 214 to perform a host of actions, such as for
example turning power output circuits 142 on or off in response to
instruction from the power settlement module 218, and rotating,
turning, or adjusting the angle of inclination of any of the
high-temperature solar thermal collectors 138, system or mirrors
and lenses, and tracking mounting systems.
[0141] The solar thermal energy components 134 contemplated herein
are assumed to generate a power output in alternating current form.
Where it is generated as alternating current, the power output of
each high-temperature solar thermal collector 138 therefore needs
to be rectified to direct current prior to connection to the common
direct current bus 158, and voltage source converters 156 adjust
the voltage level with either voltage step-up or step-down
transformers to ensure a compatible voltage level. Power output of
all of the high-temperature solar thermal collectors 138, are
monitored by the transmission control system 230, in addition to
the power outputs of all other apparatuses that are being operated
to generate power, to make further adjustments if necessary as
discussed herein.
[0142] If it is the case that power is generated as direct current,
no inverter is needed for connection of the power output circuitry
to the common direct current bus 158 and the HVDC transmission
system 106. The transmission control system 230 must still however
account for variances in the voltage of each such power output, and
therefore would monitor the power output and voltage source
converters 156 as above, in conjunction with power output of other
apparatuses of other renewable energy resource components 116 and
in conjunction with each renewable energy resource control system
214, to make adjustments accordingly.
[0143] As with other renewable energy resource components, both the
power generation module 208, the renewable energy resource control
systems 214, transmission control system 230, and the voltage
source converters 156 allow for very flexible operation of
high-temperature solar thermal collectors 138 to arrive at the
proper power production capacity that satisfies the power
requirement 144 over the specific period of time, as well as
transmission system stability and other objectives. This flexible
operational approach allows for many different configurations of
the high-temperature solar thermal collectors 138 within the scope
of the present invention. For example, different types of collector
designs may be used in combination, together with different types
and configurations of mirrors and lenses.
[0144] High-temperature solar thermal collectors 138 according to
one embodiment may also be coupled so as to be either a fixed or
permanent components of the multi-resource offshore renewable
energy installation 104, or temporarily coupled thereto so as to be
mobile and deployable to different locations or as needed.
Regardless, any of the high-temperature solar thermal collectors
138, lenses and mirrors, and mounting systems may also be mounted
on a floating structure that allows each apparatus to generate
electricity in deep ocean waters where seabed anchors or piles are
not feasible, or on a fixed structure with support that is
permanently anchored to the seabed, or both.
[0145] Floating installations do not require permanent anchoring
mechanisms and can be positioned, for example, on pontoon-based
supports or on barges, reducing the environmental impact and
increasing the scalability of the multi-resource offshore renewable
energy installation 104. Floating installations may also be capable
of being raised and lowered as needed to protect equipment,
components and mounting systems, and keep them operational, in the
event of storms, rough seas, very large waves, or other adverse
environmental conditions. Cooling capability can be generated from
the ocean water itself, particularly in floating structures and
particularly where ocean thermal energy conversion components are
implemented that produce desalinized water from heating ocean
water.
[0146] High-temperature solar thermal collectors 138 may be used to
generate power either during the day or at night, since heat can be
stored in large quantities to be supplied to the steam cycle of the
collectors at night. The present invention therefore contemplates,
that heat storage tanks may be also components on the
multi-resource offshore renewable energy installation 104.
[0147] The multi-resource offshore renewable energy installation
104 may also be configured to include an ocean thermal energy
conversion component 140 to generate a power output based on
differences between cooler deep water and warmer shallow or surface
water. This difference is used to generate steam which operates a
turbine to generate electricity. Different types of systems may be
incorporated, such as closed, open, or hybrid systems which take
advantage of the water temperature variations in different ways.
One such closed-loop system boils warm surface seawater directly in
a low-pressure container. The resulting expanded steam, which
becomes pure fresh water as a result of losing its salt, drives a
turbine attached to an electrical generator. It can then be
condensed into a liquid by exposure to cold temperatures from
waters found greater depths in a different chamber. This has the
potential to produce desalinized fresh water, suitable for drinking
water at the offshore installation site or transmission for onshore
use.
[0148] In addition to provide an additional source of power for the
power requirement 144, this renewable resource 114 can be used to
self-power the offshore multi-resource renewable energy
installation 120, together with any feedback loop incorporated in
any of one of the power output circuits 142 to make use of excess
capacity generated. This component is well-suited for such uses,
because the temperature variances between water at different depths
may be not enough for large-capacity power production. However, it
is likely that at deep ocean installations, water depths will be
great enough to generate some notable difference in temperatures,
thereby providing at least one source of power for the
multi-resource offshore renewable energy installation 104 itself.
Use of a renewable energy resource component 116 to self-power the
multi-resource offshore renewable energy resource installation 120
reduces the environmental impact of the installation by reducing
the need for connecting to a non-renewable source of power.
[0149] As with other renewable resource components 116, the ocean
thermal energy component 140 may communicate with one or more
renewable resource control systems 214 and the transmission control
system 230 to generate power to satisfy the power requirement 144.
These control systems are configured to control the ocean thermal
energy component 140 and communicate with controllers coupled to
operational and power-generating output circuits inside each
apparatus to separably and variably operate each one. The
controllers are therefore configured, in one aspect, to communicate
at least a real-time operational availability and power capacity
148 of an ocean thermal energy component 140, and in another
aspect, to respond to output signals generated by the renewable
energy resource control system 214 to perform actions such as
turning power output circuits 142 on or off, and adjusting a water
depth at which ocean water is obtained in response to instruction
from the power settlement module 218. Meteorological conditions
such as changes in sea water temperature at different depths have
substantial influence on the operational availability of each ocean
thermal energy component 140 and the ability to variably operate
each, and therefore these are continuously measured at the offshore
multi-resource renewable energy installation 120.
[0150] The ocean thermal energy components 140 contemplated herein
are also assumed to generate a power output in alternating current
form, and therefore the power outputs needs to be rectified to
direct current prior to connection to the common direct current bus
158, and voltage source converters 156 adjust the voltage level
with either voltage step-up or step-down transformers to ensure a
compatible voltage level. Power outputs of all of the ocean thermal
energy components 140 are monitored by the transmission control
system 230, in addition to the power outputs of all other
apparatuses that are being operated to generate power, to make
further adjustments if necessary as discussed herein.
[0151] As with other components 116, where it is the case that
power is generated as direct current, no inverter is needed for
connection of the power output circuitry to the common direct
current bus 158 and the HVDC transmission system 106. The
transmission control system 230 must still however account for
variances in the voltage of each such power output, and therefore
would monitor the power output and voltage source converters 156 as
above, in conjunction with power output of other apparatuses of
other renewable energy resource components 116 and in conjunction
with each renewable energy resource control system 214, to make
adjustments accordingly.
[0152] Ocean thermal energy components 140 may be either fixed or
permanent components of the multi-resource offshore renewable
energy installation 104, or temporarily coupled thereto so as to be
mobile and deployable to different locations or as needed.
Regardless, they may also be part of a floating installation of
renewable resource components 116, or a fixed installation with
support that is permanently anchored to the seabed. Floating
installations do not require permanent anchoring mechanisms and can
be positioned, for example, on pontoon-based supports or on barges,
reducing the environmental impact and increasing the scalability of
the multi-resource offshore renewable energy installation 104.
Floating installations may also be capable of being raised and
lowered as needed to protect ocean thermal energy converters 140,
and keep them operational, in the event of storms, rough seas, very
large waves, or other adverse environmental conditions.
[0153] As referenced herein, the various embodiments of the present
invention can be configured in many different ways. In one
embodiment, the present invention is contemplated to be available
as a "packaged" configuration of multiple processes, hardware, and
apparatuses that together act as a self-contained system. Such a
self-contained system can be deployable and scalable for temporary
uses, such as to provide power grid infrastructure such as in a
field military base or large-scale disaster response
situations.
[0154] Distributed computing infrastructure 150 provides a
computing and network operational architecture for the renewable
resource energy management system 100, multi-resource offshore
renewable energy installation 104, and electricity grid
infrastructure 300 of the present invention. The distributed
computing infrastructure 150 utilizes the combined computing power
of multiple interconnected computing networks 152 to manage data
flow, perform data processing functions, and facilitate
communications in the present invention. It also provides the power
distribution module 200, the power generation module 208, the power
settlement module 218, and power transmission module 226 with
flexibility to perform the critical power grid infrastructure
functions with which they are assigned. The distributed computing
infrastructure 150 is therefore a high-level computing architecture
designed to spread computational power around multiple computing
environments in a distributed fashion and which aggregates the many
interconnected computing networks 152 to perform the multiple
processes needed to host and perform the present invention.
[0155] The various modules and control systems of the present
invention may therefore be thought of as utilizing one or more
available computing resources as needed from across the distributed
computing infrastructure 150, regardless of where particular
elements of each are stored. Alternatively, system elements such as
control systems may be thought of as being "embedded" at various
points within the distributed computing infrastructure 150, such as
for example renewable energy resource control systems 214 may be
embedded within one or more controllers capable of operating each
renewable energy resource component 116. Regardless, it is to be
understood that many different configurations are possible and
contemplated within the distributed computing infrastructure
150.
[0156] In one embodiment, the distributed computing infrastructure
150 employs cloud computing principles and technology to provide a
distributed platform and resources for hosting multiple modules and
data access, processing, modeling, and storage, as well as
communication between infrastructure systems and components, so
that no one portion of the overall renewable energy resource
management system 100, multi-resource offshore renewable energy
installation 104, or electricity grid infrastructure 300 is
required to host, process, or store information. The distributed
computing infrastructure 150 may also be thought as a grid
computing architecture in which middleware provides the link
between the various modules and control systems of the present
invention to facilitate distributed data processing. Regardless,
the present invention employs the cloud-based or grid-based
distributed computing infrastructure 150 and interconnected
computing networks 152 in multiple ways to meet the operational
functions and objectives disclosed herein. Additionally, it is to
be understood that communications with the distributed computing
infrastructure 150 may be through both wired and wireless
means.
[0157] Microgrid control systems 110, for example, each perform the
critical task of determining real-time power needs of customers 112
coupled to each microgrid 108 without needing a physical location
near a microgrid 108 or its customers 112. Microgrid control
systems 200 may be resident anywhere within the cloud or grid-based
distributed computing infrastructure 150 and utilize interconnected
computing networks 152 and controllers to collect input data
regarding the microgrid 108 and the power customers 112 coupled
thereto, mathematically model power needs relative to physical
characteristics of the microgrid system they are responsible for
controlling, and generate output data used in one aspect to arrive
at the power demand 146 for the microgrid 108, and in another
aspect, to manage delivery of the necessary power requirement 144
to each microgrid 108 as discussed herein.
[0158] Furthermore, the distributed computing infrastructure 150
may be a privately-hosted, shared computing environment in which
secure data communications, processing, and storage necessary to
accomplish the present invention are possible. Effectively a
private, secure cloud, the distributed computing infrastructure 150
according to this aspect of the present invention has substantial
application in supporting enhancements in power grid infrastructure
security given the increasing need to protect power grid
infrastructure from security threats as noted in detail herein.
[0159] Microgrid 108 decoupling has specific application in grid
infrastructure security, together with the distributed,
decentralized nature of the computing environment. The distributed
computing infrastructure 150 allows communication and connectivity
of modules and control systems, and data functions and services
managed and controlled by them, to be re-routed and re-deployed
where necessary, permitting power to continue to be delivered
uninterrupted in the event of a major security threat or attack
intended to disrupt flow of power to key public infrastructure.
Extra layers further solidify the security aspects of the present
invention, as the privately-hosted, shared distributed computing
infrastructure 150 allows easier integration of specific
information security measures designed to limit the possibility
that systems can be penetrated and increasing the difficulty in
locating and disrupting distributed services.
[0160] The distributed computing infrastructure 150 is capable of
facilitating access and communication with one or more external
computing networks 154 to carry out one or more tasks in practicing
the present invention. Data from these types of external networks
154 provide information needed by one or more modules and control
systems of the present invention. An example an external computing
network 154 is an energy commodity trading platform 160 or other
public or private exchange involving commodities and capable of
providing pricing of commodities. Another example is a weather
satellite system 162 capable of providing meteorological data. Yet
another example is a database 164, public or private, that tracks
regulatory requirements for purchasing renewable energy resources
as well as public or private databases for tracking contractual
requirements for the same.
[0161] In the present invention, there are several reasons for
monitoring, modeling, and forecasting data relative to
meteorological conditions and energy commodity prices. Within both
the renewable resource energy management system 100 and the
electricity grid infrastructure 300 embodiments of the present
invention, it is imperative to assess energy commodity prices to
arrive at an optimized purchase price for each renewable energy
resource 114 to be purchased. This is influenced by many factors,
such as purchasing conditions related to contractual and regulatory
requirements obligating the purchase of particular renewable energy
resources 114 at particular times and in particular quantities,
such as for example commodity price signals, or other conditions
such as tariffs. Meteorological conditions may also be a factor in
energy commodity prices over the specific period of time, and
therefore meteorological condition models for each renewable energy
resource 114 may be components in mathematical models of energy
commodity prices over the period of time to be assessed.
[0162] Similarly, within both the renewable energy management
system 100 and the multi-resource offshore renewable energy
installation 104 embodiments of the present invention, it is
imperative to assess both meteorological conditions and energy
commodity prices to arrive at both an optimized sale price for each
renewable energy resource 114 to be purchased and an efficient
operational availability and power capacity 148 for each renewable
resource component 116. For example, an operator of a
multi-resource offshore renewable energy resource installation 120
may model meteorological conditions at the installation site and
energy commodity prices to forecast an operational availability and
power capacity 18 of each renewable energy resource component 116
at the installation.
[0163] Monitoring and modeling meteorological conditions is a
function performed by one or more of the power generation module
208, the power distribution module 200, and the power settlement
module 218 in the renewable energy resource management system 100,
by one or more renewable resource control systems 214 in the
multi-resource offshore renewable energy installation 104, and by
one or more of various modules and control systems in the
distributed management system 302 in the electricity grid
infrastructure 300 according to different embodiments of the
present invention. This function is used to forecast of
meteorological conditions over the specific period of time so that
the power requirement 144 can be satisfied, so that the operational
power capacity 148 of each renewable resource component 116 at a
multi-resource offshore renewable energy installation 104 is
maximized to ensure efficiency and cost-effectiveness, and to
balance power production with power consumption.
[0164] Many different measurements of meteorological conditions are
contemplated with the scope of the present invention, and therefore
it is possible that many external networks 154 are to be used to
access such data. Among the different meteorological conditions to
be measured include wind speed and direction influenced by weather
patterns indicating storms, sunlight conditions including time of
sunrise and sunset, cloud patterns, surface and sub-surface ocean
wave, current and tidal conditions and patterns, ocean temperature
at various depths, humidity, barometric pressure, precipitation,
and many other variables, each of which alone or in combination
affect the performance, availability, and capacity of the renewable
energy resource components 116 available at the multi-resource
offshore renewable energy installation 104.
[0165] Similarly, monitoring and modeling renewable energy resource
commodity pricing is also a function performed by one or more of
the power generation module 208, the power distribution module 200,
and the power settlement module 218 in the renewable energy
resource management system 100, by one or more renewable resource
control systems 214 in the multi-resource offshore renewable energy
installation 104, and by one or more of various modules and control
systems in the distributed management system 302 of the electricity
grid infrastructure 300 according to different embodiments of the
present invention. This function is used to forecast both a
commodity purchase price, in the case of the intelligent power
distribution network 102, and a commodity selling price, in the
case of the multi-resource offshore renewable energy installation
104, over the specific period of time, for each renewable energy
resource 114 available to satisfy the power requirement 144.
[0166] Commodity pricing is a component of satisfying the power
requirement 144 because energy prices fluctuate widely over time
and for each type of renewable energy resource 114, whether it be
solar, wind, hydrokinetic, solar thermal, ocean thermal, or any
other energy resource. Incorporating a commodity pricing component
allows an efficient operational power capacity 148 of each
renewable energy resource component 116 to be achieved, and informs
a cost-effective, efficient exchange of resources by allowing both
the buyer of power and the seller of power arrive at a price point
for each resource. Therefore, monitoring and modeling renewable
energy commodity prices helps the power requirement 144 to be
satisfied, and helps to predict the operational power capacity 148
of each renewable resource component 116 to maximize efficiency and
cost-effectiveness. It is contemplated that least some of the
renewable energy resources 114 from which power is to be generated
are traded within one or more energy commodities exchanges. It is
therefore further contemplated that a forecast of commodity prices
must take into account at least those that are traded on
exchanges.
[0167] Types of external computing networks 154 that may be
accessed to monitor and forecast meteorological conditions include,
but are not limited to, proprietary weather assessment networks,
sites capable of accessing data from weather satellites,
governmental weather system portals, other particular
weather-related websites, and any other networks capable of
aggregating useful data relative to assessing and predicting
meteorological conditions. Types of external computing networks 154
that may be accessed to monitor and forecast energy commodity
prices include, but are not limited, proprietary commodities
exchange trading platforms, particular commodities pricing
information sites, and any other networks capable aggregating
useful commodity price information that can be used to assess and
predict energy commodity prices.
[0168] The distributed computing infrastructure 150 may also host
one or more artificial neural networks tasked with heuristically
modeling data within the present invention to perform a variety of
functions, such as predicting commodity pricing and meteorological
conditions, assessing power usage patterns and power 146 customers,
and assessing power capacity 148 of the renewable energy resource
components 116. These artificial neural networks introduce data
modeling tools to the framework of the various embodiments of the
present invention to heuristically model the complex relationships
between inputs and outputs of data and to identify and take
advantage of data patterns. Artificial neural networks may take on
many forms within the distributed computing infrastructure 150,
such as for example multiple remote computing environments or
program calls that are accessed when needed by the modules and
control systems within the present invention.
[0169] Artificial neural networks therefore may perform a critical
role in increasing and improving the efficiency of the present
invention by, for example, heuristically assessing weather
conditions at the deep-ocean location of the multi-resource
offshore renewable energy installation 104 site to learn how to
predict when weather conditions are most and least favorable for
operation of a particular renewable resource component 116, and by
heuristically assessing future trends in energy commodity prices to
learn how to predict when pricing of commodities is most and least
favorable for operation of the particular renewable resource
component 116 and predict a range of prices at which commodities
are to be both bought and sold, and combining the two concepts to
further increase efficient performance within the present
invention.
[0170] Heuristic modeling in artificial neural networks can be
performed alone or as part of the many variables and
characteristics that comprise modeling and forecasting for energy
commodity prices and meteorological conditions. It may also help to
identify instances where one or more of the modules and control
systems operative within the present invention should buy, sell, or
trade, financial instruments in conjunction with commodity prices
of renewable energy resources 114. Artificial neural networks may
therefore be a useful tool, incorporated with other mathematical
modeling within the present invention, to predict energy commodity
pricing trends and when hedging may be advantageous.
[0171] In one example of the use of an artificial neural network,
where a microgrid control system 110 responsible for assessing
power usage patterns to determine a power demand 146 of power
customers 112 coupled to a microgrid 108, the microgrid control
system 110 may initiate a program call to introduce a separate
predicted assessment of power usage as part of a closed-loop system
of analyzing output signals of the microgrid control system 110.
Such a program call initiates a heuristic assessment of data
aggregation reflecting different usage components, usage type, any
fluctuation tolerance over the specific period of time at issue
which may influence load variances, and other possible variables
affecting power demand 146 as noted herein. This effectively
introduces a data modeling tool to act as a comparative check of
the assessed power demand 146, to ensure accurate data collection
and sampling. Artificial neural networks may therefore have
significant application acting as data modeling checks to ensure,
for example, that error rates are properly managed.
[0172] Energy installations located offshore face the significant
problem of transferring power to the onshore power consumer in an
efficient manner. For deep-sea installations, this may be done
using an undersea direct current transmission link, since
long-distance alternating current transmission systems suffer
losses that are unacceptably high. However, modern electricity grid
infrastructure requires substantially all power in alternating
current form for downstream delivery to consumers thereof. Power
consumers that do require direct current power rely on substations
to ensure they are getting the correct form of electricity.
Additionally, many wind, hydrokinetic, and solar thermal
manufacturers configure their apparatuses to generate power in
alternating current form to easily meet the needs of the
electricity grid consumers. Providers therefore have the problem of
components generating a mix of AC and DC power, which must be
transferred as DC, and then delivered as AC and then rectified
later if necessary.
[0173] FIG. 5 is a system diagram of components of a power
transmission system in accordance with the various embodiments of
the present invention, indicating power outputs of the renewable
energy resource components 116 connected to an HVDC transmission
system 106, which includes a sub-sea high-voltage direct current
link that transfers power generated by the multi-resource offshore
renewable energy installation 104 to the intelligent power
distribution network 102. Power output circuits 142 feed into a
system of one or more voltage source converters 156 that ensure
that each renewable energy resource component 116, and each
apparatus therein, produces a power output in the proper current at
a common or constant voltage level for connection to a common
direct current bus 158 connected to the HVDC transmission system
106. All renewable energy resource components 116 and apparatuses
of the multi-resource offshore renewable energy installation 104
are directly connected to the system of voltage source converters
156 and the common direct current bus 158 in the HVDC transmission
system 206, either in series or in parallel depending on the power
output of each, so that a direct current power output is fed into
the voltage source converters 156 and the common direct current bus
158 of the HVDC transmission system 106. Where a power output
circuit 142 generates AC-based power, it first passes through a
rectifier circuit prior to entering a voltage source converter 156
to ensure all electricity entering the common bus 158 is direct
current.
[0174] The HVDC transmission system 106 also allows each renewable
energy resource component 116 to be independently and variably
operated because the system of voltage source converters 156,
together with any rectifiers needed to convert AC to DC, conduct
the necessary power output transformation to ensure consistent and
common voltage and current. The HVDC transmission system 106
therefore supports full operational variability of the renewable
energy resource components 116 at the multi-resource offshore
renewable energy installation 104 to adjust power capacity 148 as
needed to satisfy the power requirement 144 relative to all other
considerations discussed herein, since designers need not be
primarily concerned with the effects of adjusting power capacity
148 on voltage levels.
[0175] This design allows for scalability of the multi-resource
offshore renewable energy installation 104 to accommodate hundreds
and thousands of apparatuses within each component 116. Traditional
and existing installations are usually single-resource and are
connected to electricity grids either in close proximity thereto
and/or under the assumption that because of the small percentage of
its relative share of the overall power supply, its size and
influence require less stringent attention to connection
requirements. However, as electricity grids require more and more
power from renewable resources, and multi-resource installations
become economically feasible both onshore and at deep sea locations
far away from land, the design importance of power electronics
considerations increases dramatically.
[0176] The voltage source converters 156 allow system designers to
reduce the complexity of output circuits 142 of each apparatus of
each renewable energy resource component 116, since extra
converters in power output circuits 142 are not necessary. This
allows for much easier independent and variable operation of
apparatuses and devices that produce power from renewable energy
resources.
[0177] HVDC transmission provides direct current electricity to one
or more onshore receiving locations 236 prior to delivery to the
intelligent power distribution network 102. The present invention
contemplates that electricity can be inverted to AC for those
portions of the intelligent power distribution network 102 needing
AC, diverted to selected DC-only or DC-specific microgrids 108 or
to other DC-only buyers, or transmitted further onward in DC form
to other receiving locations of other downstream intelligent power
distribution networks 102 for later decision whether to invert to
AC or divert for DC-only needs. The framework of the intelligent
power distribution network 102, together with the plurality of
microgrids 108, supports both AC and DC-based electricity grids and
allows power to delivered and consumed in either AC or DC, as
needed and instructed by each microgrid 108. DC-only microgrids 108
can therefore receive power directly from the offshore provider
without needing to employ a system of rectifiers and inverters.
[0178] Because some components can be configured to generate power
in DC, a voltage source converter 156 may not be needed with every
power output circuit 142 except to regulate any output prior to
linking with the common direct current bus 158. Since power output
levels may be monitored in conjunction with the transmission
control system 230, a bypass circuit may be included to circumvent
the VSC system 232 where voltage levels and direct current output
are already compatible with requirements of the common direct
current bus 158.
[0179] The HVDC transmission system 106, in addition to monitoring
the voltage source converters 156 and power output circuits 142 of
each apparatus to ensure compatible current and voltage levels, may
also monitor, together with the transmission control system 220,
the power output of each apparatus within each component 116 to
determine, as an additional system check, whether an over or
under-production of power is being generated for the specific
period of time. This adds an additional layer of analysis to ensure
a power balance matching power production to power consumption is
being achieved, and so that a minimal battery storage requirement
at both the multi-resource offshore renewable energy installation
104 and the one or more receiving locations 236 of the intelligent
power distribution network 102 is maintained. Where an
under-production is detected, the transmission control system 230
is capable of working with specific modules, controllers and with
other control systems 212 to increase power production somewhere
among the renewable resource components 116. Similarly in the case
of a power over-production, power production can be decreased in
the same manner.
[0180] The present invention also contemplates that one or more
feedback loops may be utilized to either transfer power to a
temporary battery for storage of the excess power, or to the
multi-resource offshore renewable energy installation 104 itself to
self-power the installation and its renewable energy resource
components 116. In this regard, the HVDC transmission system 106
may act as a source of power for the multi-resource offshore
renewable energy installation 104, either directly or from the
temporary battery, so that no or very limited additional sources of
power are needed to power the installation itself.
[0181] Excess power production may also be routed to one or more
energy storage facilities that provide backup or alternate sources
of power for electricity grids. Such grid-scale batteries may serve
one or more broader electricity grids or one or more microgrids
108, and may utilize power over-production from renewable energy
resources as an additional layer of power supply in the event of
sudden and/or localized variances to the amount of power needed,
such as in emergency situations. Where excess power is transferred
to grid-scale energy storage facilities, it may be routed thereto
from either the multi-resource offshore renewable energy
installation 104 upon output signals from the transmission control
system 230 or from the intelligent power distribution network 102
at the receiving location 236 or some other component thereof.
[0182] Power transmission in the present invention can also be
configured so that power is delivered from the multi-resource
offshore renewable energy installation 104 to the intelligent power
distribution network 102 using wireless systems and methods. One
example of wireless energy transfer is through electromagnetic
radiation, such as with lasers. Power can be transmitted by
converting electricity into laser beams that can be transmitted
using a laser emitter to an antenna at one or more receiving
locations 236 of the intelligent power distribution network 102.
The antenna receives the laser beam and converts the light to
direct current-based power to be delivered and routed to microgrids
108 as discussed herein.
[0183] The laser beam emitter may be located in a fixed
configuration at the multi-resource offshore renewable energy
installation 104, or in a temporary configuration that may be
deployable as needed. Regardless, it is contemplated that despite
possible deep-ocean locations that may result in long distances
between the multi-resource offshore renewable energy installation
104 and receiving locations 236, the distance will not result in a
substantial loss of power, and laser beam emitters are to be
configured to emit laser beams that will not result in a large loss
over the distance transmitted.
[0184] Where a laser beam-based wireless energy transmission is
utilized, the transmission system 106 must account for any power
loss that will be encountered with converting power produced at the
multi-resource offshore renewable energy installation 104 into a
laser beam. Accordingly, power outputs of the renewable energy
resource components 116, and the power output circuits 142, may
have to be adjusted, either through variable operation of the
renewable energy resource components 116 or through the voltage
source converters 156.
[0185] The type of power transmission can be managed so that the
present invention is capable of either by undersea HVDC
transmission link, by wireless energy transmission methods as
discussed herein, or both. In one embodiment, the transmission
control system 230 performs the function of selecting the
appropriate transmission method, based on input data from the
intelligent power distribution network 102, by the power
distribution module 200, power generation module 208, power
settlement module 218, or power transmission module 226 of the
renewable resource energy management system 100, by the distributed
management system 302, or by any another source of such input data.
One or more of these or other modules may also be configured to
manage the task of determining which method of transmission is to
be used.
[0186] Use of wireless energy transmission may be utilized where a
security or maintenance issue arises with the HVDC transmission
system 106. In such situations, wireless energy transmission
ensures uninterrupted flow of power from the multi-resource
offshore renewable energy installation 104 to the intelligent power
distribution network 102 and to the electricity grid infrastructure
300.
[0187] FIG. 6 and FIG. 7 are overview perspective and top plan
views of the present invention, showing a multi-resource offshore
renewable energy installation 104 connected to an intelligent power
distribution network 102 via a transmission system 106. FIG. 6 and
FIG. 7 show different embodiments of the multi-resource offshore
renewable energy installation 104. FIG. 6 shows an embodiment in
which multiple floating apparatuses, such as platforms or barges,
can produce power from multiple renewable energy components 116 to
an intelligent power distribution network 102. FIG. 7 shows another
embodiment in which a mobile, semi-submersible production platform
provides support for a number of such multiple floating
apparatuses. The multi-resource offshore renewable energy
installations 104 in FIG. 6 may therefore be coupled in any number
to a mobile semi-submersible production platform as shown in FIG.
7. Regardless, it is to be understood that numerous configurations
of the present invention are contemplated and possible to achieve
the various objectives discussed herein.
[0188] The present invention contemplates many other embodiments
that are within the scope of this disclosure. For example, in one
such embodiment, systems and methods of determining, on one side,
an optimal power demand and on the other side, an optimal supply
within an electricity grid infrastructure. This includes a method
of determining an optimal delivery of power to be generated
entirely from renewable resources for an electricity grid
infrastructure. Another method according to this embodiment
involves determining an optimal generation of power to be delivered
to an electricity grid infrastructure. Yet further methods involve
settling a transfer of power that is entirely generated from
renewable resources and satisfies a power requirement of an
electricity grid infrastructure, and transmitting an optimal
delivery of power to customers of an electricity grid
infrastructure.
[0189] In another such embodiment, the present invention discloses
a system and method of balancing power production with power
consumption in an electricity grid infrastructure. This embodiment
includes a method of adapting renewable resource energy production
to energy consumption, a method of minimizing storage of
electricity for delivery to an electricity grid infrastructure, and
a balanced renewable resource-based energy management system
comprising a source of power generated entirely from renewable
energy resources and a consumer of power having a predictable power
demand over any given period of time, wherein the power transmitted
satisfies the entire power requirement only from renewable energy
resources and at an operational level that maximizes the efficiency
of each renewable energy resource.
[0190] In yet another embodiment, the present invention discloses a
system and method of enhancing grid infrastructure security. This
embodiment includes methods of improving electricity grid security
and securely delivering power to an electricity grid
infrastructure. The embodiment may also include a security system
for ensuring delivery of power to an electricity grid
infrastructure.
[0191] It is to be understood that still other embodiments will be
utilized and structural and functional changes will be made without
departing from the scope of the present invention. The foregoing
descriptions of embodiments of the present invention have been
presented for the purposes of illustration and description. It is
not intended to be exhaustive or to limit the invention to the
precise forms disclosed. Accordingly, many modifications and
variations are possible in light of the above teachings. It is
therefore intended that the scope of the invention be limited not
by this detailed description.
* * * * *