U.S. patent application number 12/751821 was filed with the patent office on 2011-01-06 for systems and methods for electric vehicle power flow management.
This patent application is currently assigned to GridPoint, Inc.. Invention is credited to Zachary Axelrod, Seth W. Bridges, Joby Lafky, Seth B. Pollack.
Application Number | 20110004358 12/751821 |
Document ID | / |
Family ID | 42982790 |
Filed Date | 2011-01-06 |
United States Patent
Application |
20110004358 |
Kind Code |
A1 |
Pollack; Seth B. ; et
al. |
January 6, 2011 |
SYSTEMS AND METHODS FOR ELECTRIC VEHICLE POWER FLOW MANAGEMENT
Abstract
A system and methods that enables power flow management at the
local level. A power flow manager can coordinate the charging
activities of electrical devices, such as electric vehicles. Power
flow decisions may based on the site-level information. In
addition, power flow management strategies may be optimized. An
optimizer can choose a power flow management strategy and
electrical devices for implementing a strategy. In the event of a
system failure, power spikes may be avoided by using safe failure
modes to provide that the charging activities be coordinated in a
predictable and non-disruptive manner. The cost of providing power
may be reduced using generation stacks of power production. As
such, the total daily cost of providing energy generation may be
minimized.
Inventors: |
Pollack; Seth B.; (Seattle,
WA) ; Bridges; Seth W.; (Seattle, WA) ; Lafky;
Joby; (Seattle, WA) ; Axelrod; Zachary;
(Washington, DC) |
Correspondence
Address: |
GREENBERG TRAURIG, LLP (DC/ORL)
2101 L Street, N.W., Suite 1000
Washington
DC
20037
US
|
Assignee: |
GridPoint, Inc.
Arlington
VA
|
Family ID: |
42982790 |
Appl. No.: |
12/751821 |
Filed: |
March 31, 2010 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61165344 |
Mar 31, 2009 |
|
|
|
Current U.S.
Class: |
700/297 |
Current CPC
Class: |
H02J 7/00 20130101; Y02T
10/72 20130101; Y02T 90/12 20130101; B60L 53/305 20190201; B60L
53/64 20190201; Y02E 60/00 20130101; B60L 53/18 20190201; Y02T
90/168 20130101; B60L 53/65 20190201; Y02T 90/167 20130101; B60L
2240/70 20130101; H02J 2300/10 20200101; Y02T 90/169 20130101; B60L
55/00 20190201; Y04S 30/12 20130101; B60L 53/63 20190201; B60L
53/665 20190201; H02J 3/381 20130101; Y02T 90/16 20130101; B60L
53/68 20190201; Y04S 30/14 20130101; B60L 11/184 20130101; Y02T
10/70 20130101; Y02T 90/14 20130101; Y04S 10/126 20130101; Y02T
10/7072 20130101 |
Class at
Publication: |
700/297 |
International
Class: |
G06F 19/00 20060101
G06F019/00 |
Claims
1. A method for managing power flow at a local site, comprising the
steps: site-level charging of a plurality of electrical devices by
a power flow manager, wherein the power flow manager runs a smart
charging program, wherein the power flow manager coordinates
charging activities of the plurality of electrical devices, wherein
the plurality of electrical devices are located at the local site;
receiving site-level information, wherein the site-level
information is received by the power flow manager; making power
flow decisions based on the site-level information, wherein the
power flow decisions are made by the power flow manager; and,
managing power flow to the plurality of electrical devices by the
power flow manager, wherein the power flow manager responds to
requests.
2. The method of claim 1, wherein the power flow manager is a
central server.
3. The method of claim 1, wherein the power flow manager is located
at the local site.
4. The method of claim 1, wherein the power flow manager is located
remotely from the local site.
5. The method of claim 1, wherein the electrical devices are
electric vehicles.
6. The method of claim 1, wherein the site-level information is
selected from a group consisting of the following: electrical meter
data for the local site, electrical meter data for at least one
charge point; information from at least one of the plurality of
electrical devices; electric rate information for the local site;
electrical topology information; power limitation information; or
priority rules.
7. The method of claim 1, wherein the requests are selected from
the group consisting of the following: demand response event,
reserves call, renewable resource following, or system
regulation.
8. The method of claim 1, wherein the power flow manager
communicates with at least one of the plurality of electrical.
9. The method of claim 1, wherein the power flow manager
communicates with at least one charge point.
10. The method of claim 1, wherein the power flow decisions are
selected from the group consisting of the following: to provide
power, to draw power, to control power levels.
11. The method of claim 1, wherein the power flow decisions are
made based on constraints, priorities, optimizations, or
efficiencies.
12. The method of claim 1, wherein the power flow decisions are
implemented by an action selected from the group consisting of the
following: controlling relays to open close circuits; communicating
to charging points to control circuits or devices on the circuits;
communicating to at least one of the plurality of devices to
provide a command for power flow behavior.
13. A system for managing power flow at a local site, comprising: a
power flow manager, wherein the power flow manager coordinates
charging activities of a plurality of electrical devices, wherein
the plurality of electrical devices are located at the local site;
a plurality of charge points connected to the power flow manger,
wherein the plurality of charge points are operable to connect to
the plurality of electrical devices, wherein the plurality of
charge points are located at the local site; site-level
information, wherein the site-level information is received by the
power flow manager; and, power flow decisions based on the
site-level information, wherein the power flow decisions are made
by the power flow manager.
14. The system of claim 13, wherein the power flow manager is a
central server.
15. The system of claim 13, wherein the power flow manager is
located at the local site.
16. The system of claim 13, wherein the power flow manager is
located remotely from the local site.
17. The system of claim 13, wherein the electrical devices are
electric vehicles.
18. The system of claim 13, wherein the site-level information is
selected from a group consisting of the following: electrical meter
data for the local site, electrical meter data for at least one
charge point; information from at least one of the plurality of
electrical devices; electric rate information for the local site;
electrical topology information; power limitation information; or
priority rules.
19. The system of claim 13, wherein the power flow manager
communicates with at least one charge point.
20. The system of claim 13, wherein the power flow manager
communicates with at least one of the plurality of electrical.
21. The system of claim 20, wherein the power flow manager
communicates with at least one of the plurality of electrical via
at least one charge point.
22. The system of claim 20, wherein the power flow manager
communicates with at least one of the plurality of electrical via a
wireless connection.
23. A system for managing power flow for optimization of multiple
power flow management strategies, comprising: a power flow manager,
wherein the power flow manager coordinates charging activities of a
plurality of electrical devices; power flow services, wherein the
power flow services are controlled by the power flow manager; power
flow management strategies, wherein the power flow management
strategies are implemented by the power flow manager; and, a
meta-optimizer, wherein the meta-optimizer chooses at least one of
the power flow management strategies, wherein the meta-optimizer
chooses at least one of the electrical devices to utilize for
implementing the at least one of the power flow management
strategies.
24. The system of claim of 23, wherein the power flow services are
selected from a group consisting of the following: regulation,
spinning reserve, peak avoidance, or renewable generation
following.
25. The system of claim of 23, wherein the meta-optimizer choices
are based on maximizing value generated.
26. The system of claim of 23, wherein the meta-optimizer choices
are based on minimizing environmental impact.
27. The system of claim of 23, wherein the meta-optimizer choices
are based on a value function associated with the at least one of
the power flow management strategies.
28. The system of claim of 23, wherein the meta-optimizer choices
are based on a grid topological location.
29. The system of claim of 23, wherein the meta-optimizer choices
are based on multiple component requirements.
30. The system of claim of 23, wherein the meta-optimizer choices
are based on predictions.
31. The system of claim of 23, wherein the electrical devices are
electric vehicles.
32. A method for managing power flow by optimizing multiple power
flow management strategies, comprising: coordinating charging
activities of a plurality of electrical devices, wherein the charge
activities are coordinated by a power flow manager; controlling
power flow services, wherein the power flow services are controlled
by the power flow manager; choosing at least one of the power flow
management strategies, wherein the at least one of the power flow
management strategies is chosen by a meta-optimizer; choosing at
least one of the electrical devices to utilize for implementing the
at least one of the power flow management strategies, wherein the
at least one of the electrical devices is chosen by the
meta-optimizer; and, implementing power flow management strategies,
wherein the power flow management strategies are implemented by the
power flow manager.
33. The method of claim of 32, wherein the power flow services are
selected from a group consisting of the following: regulation,
spinning reserve, peak avoidance, or renewable generation
following.
34. The method of claim of 32, wherein the meta-optimizer choices
are based on factors selected from a group consisting of the
following: maximizing value generated; minimizing environmental
impact; a value function associated with the at least one of the
power flow management strategies; a grid topological location;
multiple component requirements; or predictions.
35. The method of claim of 32, wherein the meta-optimizer is the
power flow manager.
36. The method of claim of 32, wherein the power flow manager is a
site power flow manager that managing power flow at a local
site.
37. The method of claim of 32, wherein the electrical devices are
electric vehicles.
38. A system for managing power flow using safe failure modes,
comprising: a power flow manager, wherein the power flow manager
coordinates charging activities of a plurality of electrical
devices; a system failure event; and, a safe failure mode, wherein
the safe failure mode is implemented by the power flow manager,
wherein the safe failure mode provides that the charging activities
be coordinated in a predictable and non-disruptive manner.
39. The system of claim of 38, wherein the system failure event is
generated as a result of an introduction of a smart charging or
energy management system.
40. The system of claim of 38, wherein the system failure event
results in a spike in electricity demand.
41. The system of claim of 38, wherein the system failure event
occurs as a result of a failure in communications between the
plurality of electrical devices and a master controller.
42. The system of claim of 38, wherein the system failure event
occurs as a result of a failure in a controller, wherein the
controller is incapable of communicating with the plurality of
electrical devices.
43. The system of claim of 38, wherein the system failure event
occurs as a result of a design defect shared by the plurality of
electrical devices causing the plurality of electrical devices to
simultaneously lose communications capabilities.
44. The system of claim of 38, wherein the safe failure mode
comprises maintaining a stable non-changing behavior for a defined
period of time around a failure event.
45. The system of claim of 38, wherein the safe failure mode
comprises executing a prearranged behavior in the event of a
failure condition.
46. The system of claim of 38, wherein the safe failure mode
comprises executing state transitions in prearranged behaviors at a
determined time offset by a random interval of time.
47. The system of claim of 38, wherein the safe failure mode
comprises using predictions about resource behaviors.
48. The system of claim of 38, wherein the electrical devices are
electric vehicles.
49. A method for managing power flow using safe failure modes,
comprising: coordinating charging activities of a plurality of
electrical devices, wherein the charge activities are coordinated
by a power flow manager; detecting a system failure event, wherein
the system failure event is detected by a power flow manager; and,
implementing a safe failure mode, wherein the safe failure mode is
implemented by the power flow manager, wherein the safe failure
mode provides that the charging activities be coordinated in a
predictable and non-disruptive manner.
50. The method of claim of 49, wherein the system failure event is
generated as a result of an introduction of a smart charging or
energy management system.
51. The method of claim of 49, wherein the system failure event
results in a spike in electricity demand.
52. The method of claim of 49, wherein the system failure event
occurs as a result of a failure in communications between the
plurality of electrical devices and a master controller.
53. The method of claim of 49, wherein the system failure event
occurs as a result of a failure in a controller, wherein the
controller is incapable of communicating with the plurality of
electrical devices.
54. The method of claim of 49, wherein the system failure event
occurs as a result of a design defect shared by the plurality of
electrical devices causing the plurality of electrical devices to
simultaneously lose communications capabilities.
55. The method of claim of 49, wherein the safe failure mode
comprises maintaining a stable non-changing behavior for a defined
period of time around a failure event.
56. The method of claim of 49, wherein the safe failure mode
comprises executing a prearranged behavior in the event of a
failure condition.
57. The method of claim of 49, wherein the safe failure mode
comprises executing state transitions in prearranged behaviors at a
determined time offset by a random interval of time.
58. The method of claim of 49, wherein the safe failure mode
comprises using predictions about resource behaviors.
59. The method of claim 49, wherein the electrical devices are
electric vehicles.
60. A system for managing power flow using generation stacks of
power production to reduce cost of providing power to electrical
devices, comprising: a power flow manager, wherein the power flow
manager coordinates charging activities of a plurality of
electrical devices; a power production stack, wherein the power
flow manager controls the power production stack, wherein the power
production stack orders available power; and, a dispatchable load,
wherein the dispatchable load is listed in the power production
stack, wherein the dispatchable load is removed based on a cost
reduction strategy.
61. The system of claim 60, wherein the available power is ordered
based on power prices ordered from cheapest to most expensive.
62. The system of claim 60, wherein the dispatchable load is the
most expensive load listed in the power production stack.
63. The system of claim 60, wherein the available power is provided
by a plurality of power producers.
64. The system of claim 60, wherein the cost reduction strategy is
to decrease a cost of providing power services to the plurality of
electrical devices.
65. The system of claim 60, wherein the cost reduction strategy is
to decrease a cost of providing power services to the plurality of
electrical devices, wherein the cost is a daily cost.
66. The system of claim 60, wherein the cost reduction strategy is
to minimize a cost based on the power production stack.
67. The system of claim 60, wherein the cost reduction strategy is
to dispatch the most expensive load.
68. The system of claim 60, wherein the cost reduction strategy is
based on a region.
69. The system of claim 60, wherein the cost reduction strategy
comprises forecasting the dispatchable load.
70. The system of claim 60, wherein the electrical devices are
electric vehicles.
71. A method for managing power flow using generation stacks of
power production to reduce cost of providing power to electrical
devices, comprising: coordinating charging activities of a
plurality of electrical devices, wherein the charge activities are
coordinated by a power flow manager; controlling a power production
stack, wherein the power flow manager controls the power production
stack, wherein the power production stack orders available power;
removing a dispatchable load, wherein the dispatchable load is
listed in the power production stack, wherein the dispatchable load
is removed based on a cost reduction strategy.
72. The system of claim 71, wherein the available power is ordered
based on power prices ordered from cheapest to most expensive.
73. The system of claim 71, wherein the dispatchable load is the
most expensive load listed in the power production stack.
74. The system of claim 71, wherein the available power is provided
by a plurality of power producers.
75. The system of claim 71, wherein the cost reduction strategy is
to decrease a cost of providing power services to the plurality of
electrical devices.
76. The system of claim 71, wherein the cost reduction strategy is
to decrease a cost of providing power services to the plurality of
electrical devices, wherein the cost is a daily cost.
77. The system of claim 71, wherein the cost reduction strategy is
to minimize a cost based on the power production stack.
78. The system of claim 71, wherein the cost reduction strategy is
to dispatch the most expensive load.
79. The system of claim 71, wherein the cost reduction strategy is
based on a region.
80. The system of claim 71, wherein the cost reduction strategy
comprises forecasting the dispatchable load.
81. The system of claim 71, wherein the electrical devices are
electric vehicles.
82. The method of claim 71, wherein the electrical devices are
electric vehicles.
Description
[0001] This non-provisional patent application claims priority to,
and incorporates herein by reference, U.S. Provisional Patent
Application No. 61/165,344 filed on Mar. 31, 2009. This application
also incorporates herein by reference the following: U.S. patent
application Ser. No. 12/252,657 filed Oct. 16, 2008; U.S. patent
application Ser. No. 12/252,209 filed Oct. 15, 2008; U.S. patent
application Ser. No. 12/252,803 filed Oct. 16, 2008; and U.S.
patent application Ser. No. 12/252,950 filed Oct. 16, 2008.
[0002] This application includes material which is subject to
copyright protection. The copyright owner has no objection to the
facsimile reproduction by anyone of the patent disclosure, as it
appears in the Patent and Trademark Office files or records, but
otherwise reserves all copyright rights whatsoever.
FIELD OF THE INVENTION
[0003] The present invention relates in general to the field of
electric vehicles, and in particular to novel systems and methods
for power flow management for electric vehicles.
BACKGROUND OF THE INVENTION
[0004] The electric power grid has become increasingly unreliable
and antiquated, as evidenced by frequent large-scale power outages.
Grid instability wastes energy, both directly and indirectly, e.g.
by encouraging power consumers to install inefficient forms of
backup generation. While clean forms of energy generation, such as
wind and solar, can help to address the above problems, they suffer
from intermittency. Hence, grid operators are reluctant to rely
heavily on these sources, making it difficult to move away from
carbon-intensive forms of electricity.
[0005] With respect to the electric power grid, electric power
delivered during periods of peak demand costs substantially more
than off-peak power. The electric power grid contains limited
inherent facility for storing electrical energy. Electricity 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). Distributed
electric resources, en masse can, in principle, provide a
significant resource for addressing the above problems. However,
current power services infrastructure lacks provisioning and
flexibility that are required for aggregating a large number of
small-scale resources, such as electric vehicle batteries, to meet
large-scale needs of power services.
[0006] Modern Electric vehicles could benefit in a variety of ways
from a centrally controlled smart charging program, wherein a
central server coordinates the charging activities of a number of
vehicles. Significant opportunities for improvement exist in
managing power flow at local level. More economical, reliable
electrical power needs to be provided at times of peak demand.
Power services, such as regulation and spinning reserves, can be
provided to electricity markets to provide a significant economic
opportunity. Technologies can be enabled to provide broader use of
intermittent power sources, such as wind and solar. What is needed
are power flow management systems and methods that manage power
flow at the site-level, that implement various power flow
strategies for the optimizing how to dispatch the resources under
management, that avoid power spikes, and that minimize the total
daily cost of providing energy generation.
SUMMARY OF THE INVENTION
[0007] In an embodiment, a method for managing power flow at a
local site includes site-level charging of electrical devices by a
power flow manager. The power flow manager runs a smart charging
program, and coordinates charging activities of the electrical
devices. The electrical devices may be located at the local site.
The method includes receiving site-level information, which is
received by the power flow manager. In addition, power flow
decisions are made, by the power flow manager, based on the
site-level information. Further, power flow to the electrical
devices is managed by the power flow manager, wherein the power
flow manager responds to requests.
[0008] In another embodiment, a method for managing power flow by
optimizing multiple power flow management strategies includes
coordinating charging activities of electrical devices. The charge
activities are coordinated by a power flow manager. Power flow
services are also controlled by the power flow manager. A power
flow management strategy is chosen by a meta-optimizer, which also
chooses the electrical devices to utilize for implementing the
power flow management strategy. The power flow management
strategies are implemented by the power flow manager.
[0009] In one embodiment, a method for managing power flow using
safe failure modes includes coordinating charging activities of
electrical devices by a power flow manager. The method includes
detecting a system failure event by a power flow manager, and
implementing a safe failure mode. The safe failure mode implemented
by the power flow manager provides that the charging activities be
coordinated in a predictable and non-disruptive manner.
[0010] In another embodiment, a method for managing power flow uses
generation stacks of power production to reduce cost of providing
power to electrical devices. This method also includes coordinating
charging activities of electrical devices by a power flow manager.
In addition, the power flow manager controls a power production
stack, which orders available power. A dispatchable load is listed
in the power production stack. The dispatchable load is removed
based on a cost reduction strategy.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The foregoing and other objects, features, and advantages of
the invention will be apparent from the following more particular
description of embodiments as illustrated in the accompanying
drawings, in which reference characters refer to the same parts
throughout the various views. The drawings are not necessarily to
scale, emphasis instead being placed upon illustrating principles
of the invention.
[0012] FIG. 1 is a diagram of an example of a power aggregation
system.
[0013] FIGS. 2A-2B are diagrams of an example of connections
between an electric vehicle, the power grid, and the Internet.
[0014] FIG. 3 is a block diagram of an example of connections
between an electric resource and a flow control server of the power
aggregation system.
[0015] FIG. 4 is a diagram of an example of a layout of the power
aggregation system.
[0016] FIG. 5 is a diagram of an example of control areas in the
power aggregation system.
[0017] FIG. 6 is a diagram of multiple flow control centers in the
power aggregation system and a directory server for determining a
flow control center.
[0018] FIG. 7 is a block diagram of an example of flow control
server.
[0019] FIG. 8A is a block diagram of an example of remote
intelligent power flow module.
[0020] FIG. 8B is a block diagram of an example of transceiver and
charging component combination.
[0021] FIG. 8C is an illustration of an example of simple user
interface for facilitating user controlled charging.
[0022] FIG. 9 is a diagram of an example of resource communication
protocol.
[0023] FIG. 10 is a diagram of an example of a site power flow
manager.
[0024] FIG. 11 is a flow chart of an example of a site power flow
manager.
[0025] FIG. 12 is a flow chart of an example of optimization across
multiple power flow management strategies.
[0026] FIG. 13 is a flow chart of an example of avoiding power
spikes during energy management failures using safe failure
modes.
[0027] FIG. 14 is a flow chart of an example of
generation-stack-aware dispatch of resources.
DETAILED DESCRIPTION OF THE EMBODIMENTS
[0028] Reference will now be made in detail to the embodiments of
the present invention, examples of which are illustrated in the
accompanying drawings.
[0029] Overview
[0030] Described herein is a power aggregation system for
distributed electric resources, and associated methods. In one
implementation, a system communicates over the Internet and/or some
other public or private networks with numerous individual electric
resources connected to a power grid (hereinafter, "grid"). By
communicating, the system can dynamically aggregate these electric
resources to provide power services to grid operators (e.g.
utilities, Independent System Operators (ISO), etc).
[0031] "Power services" as used herein, refers to energy delivery
as well as other ancillary services including demand response,
regulation, spinning reserves, non-spinning reserves, energy
imbalance, reactive power, and similar products.
[0032] "Aggregation" as used herein refers to the ability to
control power flows into and out of a set of spatially distributed
electric resources with the purpose of providing a power service of
larger magnitude.
[0033] "Charge Control Management" as used herein refers to
enabling or performing the starting, stopping, or level-setting of
a flow of power between a power grid and an electric resource.
[0034] "Power grid operator" as used herein, refers to the entity
that is responsible for maintaining the operation and stability of
the power grid within or across an electric control area. The power
grid operator may constitute some combination of manual/human
action/intervention and automated processes controlling generation
signals in response to system sensors. A "control area operator" is
one example of a power grid operator.
[0035] "Control area" as used herein, refers to a contained portion
of the electrical grid with defined input and output ports. The net
flow of power into this area must equal (within some error
tolerance) the sum of the power consumption within the area and
power outflow from the area.
[0036] "Power grid" as used herein means a power distribution
system/network that connects producers of power with consumers of
power. The network may include generators, transformers,
interconnects, switching stations, and safety equipment as part of
either/both the transmission system (i.e., bulk power) or the
distribution system (i.e. retail power). The power aggregation
system is vertically scalable for use within a neighborhood, a
city, a sector, a control area, or (for example) one of the eight
large-scale Interconnects in the North American Electric
Reliability Council (NERC). Moreover, the system is horizontally
scalable for use in providing power services to multiple grid areas
simultaneously.
[0037] "Grid conditions" as used herein, refers to the need for
more or less power flowing in or out of a section of the electric
power grid, in response to one of a number of conditions, for
example supply changes, demand changes, contingencies and failures,
ramping events, etc. These grid conditions typically manifest
themselves as power quality events such as under- or over-voltage
events or under- or over-frequency events.
[0038] "Power quality events" as used herein typically refers to
manifestations of power grid instability including voltage
deviations and frequency deviations; additionally, power quality
events as used herein also includes other disturbances in the
quality of the power delivered by the power grid such as sub-cycle
voltage spikes and harmonics.
[0039] "Electric resource" as used herein typically refers to
electrical entities that can be commanded to do some or all of
these three things: take power (act as load), provide power (act as
power generation or source), and store energy. Examples may include
battery/charger/inverter systems for electric or hybrid-electric
vehicles, repositories of used-but-serviceable electric vehicle
batteries, fixed energy storage, fuel cell generators, emergency
generators, controllable loads, etc.
[0040] "Electric vehicle" is used broadly herein to refer to pure
electric and hybrid electric vehicles, such as plug-in hybrid
electric vehicles (PHEVs), especially vehicles that have
significant storage battery capacity and that connect to the power
grid for recharging the battery. More specifically, electric
vehicle means a vehicle that gets some or all of its energy for
motion and other purposes from the power grid. Moreover, an
electric vehicle has an energy storage system, which may consist of
batteries, capacitors, etc., or some combination thereof. An
electric vehicle may or may not have the capability to provide
power back to the electric grid.
[0041] Electric vehicle "energy storage systems" (batteries, super
capacitors, and/or other energy storage devices) are used herein as
a representative example of electric resources intermittently or
permanently connected to the grid that can have dynamic input and
output of power. Such batteries can function as a power source or a
power load. A collection of aggregated electric vehicle batteries
can become a statistically stable resource across numerous
batteries, despite recognizable tidal connection trends (e.g., an
increase in the total number of vehicles connected to the grid at
night; a downswing in the collective number of connected batteries
as the morning commute begins, etc.) Across vast numbers of
electric vehicle batteries, connection trends are predictable and
such batteries become a stable and reliable resource to call upon,
should the grid or a part of the grid (such as a person's home in a
blackout) experience a need for increased or decreased power. Data
collection and storage also enable the power aggregation system to
predict connection behavior on a per-user basis.
[0042] An Example of the Presently Disclosed System
[0043] FIG. 1 shows a power aggregation system 100. A flow control
center 102 is communicatively coupled with a network, such as a
public/private mix that includes the Internet 104, and includes one
or more servers 106 providing a centralized power aggregation
service. "Internet" 104 will be used herein as representative of
many different types of communicative networks and network mixtures
(e.g., one or more wide area networks--public or private--and/or
one or more local area networks). Via a network, such as the
Internet 104, the flow control center 102 maintains communication
108 with operators of power grid(s), and communication 110 with
remote resources, i.e., communication with peripheral electric
resources 112 ("end" or "terminal" nodes/devices of a power
network) that are connected to the power grid 114. In one
implementation, power line communicators (PLCs), such as those that
include or consist of Ethernet-over-power line bridges 120 are
implemented at connection locations so that the "last mile" (in
this case, last feet--e.g., in a residence 124) of Internet
communication with remote resources is implemented over the same
wire that connects each electric resource 112 to the power grid
114. Thus, each physical location of each electric resource 112 may
be associated with a corresponding Ethernet-over-power line bridge
120 (hereinafter, "bridge") at or near the same location as the
electric resource 112. Each bridge 120 is typically connected to an
Internet access point of a location owner, as will be described in
greater detail below. The communication medium from flow control
center 102 to the connection location, such as residence 124, can
take many forms, such as cable modem, DSL, satellite, fiber, WiMax,
etc. In a variation, electric resources 112 may connect with the
Internet by a different medium than the same power wire that
connects them to the power grid 114. For example, a given electric
resource 112 may have its own wireless capability to connect
directly with the Internet 104 or an Internet access point and
thereby with the flow control center 102.
[0044] Electric resources 112 of the power aggregation system 100
may include the batteries of electric vehicles connected to the
power grid 114 at residences 124, parking lots 126 etc.; batteries
in a repository 128, fuel cell generators, private dams,
conventional power plants, and other resources that produce
electricity and/or store electricity physically or
electrically.
[0045] In one implementation, each participating electric resource
112 or group of local resources has a corresponding remote
intelligent power flow (IPF) module 134 (hereinafter, "remote IPF
module" 134). The centralized flow control center 102 administers
the power aggregation system 100 by communicating with the remote
IPF modules 134 distributed peripherally among the electric
resources 112. The remote IPF modules 134 perform several different
functions, including, but not limited to, providing the flow
control center 102 with the statuses of remote resources;
controlling the amount, direction, and timing of power being
transferred into or out of a remote electric resource 112;
providing metering of power being transferred into or out of a
remote electric resource 112; providing safety measures during
power transfer and changes of conditions in the power grid 114;
logging activities; and providing self-contained control of power
transfer and safety measures when communication with the flow
control center 102 is interrupted. The remote IPF modules 134 will
be described in greater detail below.
[0046] In another implementation, instead of having an IPF module
134, each electric resource 112 may have a corresponding
transceiver (not shown) to communicate with a local charging
component (not shown). The transceiver and charging component, in
combination, may communicate with flow control center 102 to
perform some or all of the above mentioned functions of IPF module
134. A transceiver and charging component are shown in FIG. 2B and
are described in greater detail herein.
[0047] FIG. 2A shows another view of electrical and communicative
connections to an electric resource 112. In this example, an
electric vehicle 200 includes a battery bank 202 and a remote IPF
module 134. The electric vehicle 200 may connect to a conventional
wall receptacle (wall outlet) 204 of a residence 124, the wall
receptacle 204 representing the peripheral edge of the power grid
114 connected via a residential powerline 206.
[0048] In one implementation, the power cord 208 between the
electric vehicle 200 and the wall outlet 204 can be composed of
only conventional wire and insulation for conducting alternating
current (AC) power to and from the electric vehicle 200. In FIG.
2A, a location-specific connection locality module 210 performs the
function of network access point--in this case, the Internet access
point. A bridge 120 intervenes between the receptacle 204 and the
network access point so that the power cord 208 can also carry
network communications between the electric vehicle 200 and the
receptacle 204. With such a bridge 120 and connection locality
module 210 in place in a connection location, no other special
wiring or physical medium is needed to communicate with the remote
IPF module 134 of the electric vehicle 200 other than a
conventional power cord 208 for providing residential line current
at any conventional voltage. Upstream of the connection locality
module 210, power and communication with the electric vehicle 200
are resolved into the powerline 206 and an Internet cable 104.
[0049] Alternatively, the power cord 208 may include safety
features not found in conventional power and extension cords. For
example, an electrical plug 212 of the power cord 208 may include
electrical and/or mechanical safeguard components to prevent the
remote IPF module 134 from electrifying or exposing the male
conductors of the power cord 208 when the conductors are exposed to
a human user.
[0050] In some embodiments, a radio frequency (RF) bridge (not
shown) may assist the remote IPF module 134 in communicating with a
foreign system, such as a utility smart meter (not shown) and/or a
connection locality module 210. For example, the remote IPF module
134 may be equipped to communicate over power cord 208 or to engage
in some form of RF communication, such as Zigbee or Bluetooth.TM.,
and the foreign system may be able to engage in a different form of
RF communication. In such an implementation, the RF bridge may be
equipped to communicate with both the foreign system and remote IPF
module 134 and to translate communications from one to a form the
other may understand, and to relay those messages. In various
embodiments, the RF bridge may be integrated into the remote IPF
module 134 or foreign system, or may be external to both. The
communicative associations between the RF bridge and remote IPF
module 134 and between the RF bridge and foreign system may be via
wired or wireless communication.
[0051] FIG. 2B shows a further view of electrical and communicative
connections to an electric resource 112. In this example, the
electric vehicle 200 may include a transceiver 212 rather than a
remote IPF module 134. The transceiver 212 may be communicatively
coupled to a charging component 214 through a connection 216, and
the charging component itself may be coupled to a conventional wall
receptacle (wall outlet) 204 of a residence 124 and to electric
vehicle 200 through a power cord 208. The other components shown in
FIG. 2B may have the couplings and functions discussed with regard
to FIG. 2A.
[0052] In various embodiments, transceiver 212 and charging
component 214 may, in combination, perform the same functions as
the remote IPF module 134. Transceiver 212 may interface with
computer systems of electric vehicle 200 and communicate with
charging component 214, providing charging component 214 with
information about electric vehicle 200, such as its vehicle
identifier, a location identifier, and a state of charge. In
response, transceiver 212 may receive requests and commands which
transceiver 212 may relay to vehicle 200's computer systems.
[0053] Charging component 214, being coupled to both electric
vehicle 200 and wall outlet 204, may effectuate charge control of
the electric vehicle 200. If the electric vehicle 200 is not
capable of charge control management, charging component 214 may
directly manage the charging of electric vehicle 200 by stopping
and starting a flow of power between the electric vehicle 200 and a
power grid 114 in response to commands received from a flow control
server 106. If, on the other hand, the electric vehicle 200 is
capable of charge control management, charging component 214 may
effectuate charge control by sending commands to the electric
vehicle 200 through the transceiver 212.
[0054] In some embodiments, the transceiver 212 may be physically
coupled to the electric vehicle 200 through a data port, such as an
OBD-II connector. In other embodiments, other couplings may be
used. The connection 216 between transceiver 212 and charging
component 214 may be a wireless signal, such as a radio frequency
(RF), such as a Zigbee, or Bluetooth.TM. signal. And charging
component 214 may include a receiver socket to couple with power
cord 208 and a plug to couple with wall outlet 204. In one
embodiment, charging component 214 may be coupled to connection
locality module 210 in either a wired or wireless fashion. For
example, charging component 214 might have a data interface for
communicating wirelessly with both the transceiver 212 and locality
module 210. In such an embodiment, the bridge 120 may not be
required.
[0055] Further details about the transceiver 212 and charging
component 214 are illustrated by FIG. 8B and described in greater
detail herein.
[0056] FIG. 3 shows another implementation of the connection
locality module 210 of FIG. 2, in greater detail. In FIG. 3, an
electric resource 112 has an associated remote IPF module 134,
including a bridge 120. The power cord 208 connects the electric
resource 112 to the power grid 114 and also to the connection
locality module 210 in order to communicate with the flow control
server 106.
[0057] The connection locality module 210 includes another instance
of a bridge 120, connected to a network access point 302, which may
include such components as a router, switch, and/or modem, to
establish a hardwired or wireless connection with, in this case,
the Internet 104. In one implementation, the power cord 208 between
the two bridges 120 and 120' is replaced by a wireless Internet
link, such as a wireless transceiver in the remote IPF module 134
and a wireless router in the connection locality module 210.
[0058] In other embodiments, a transceiver 212 and charging
component 214 may be used instead of a remote IPF module 134. In
such an embodiment, the charging component 214 may include or be
coupled to a bridge 120, and the connection locality module 210 may
also include a bridge 120', as shown. In yet other embodiments, not
shown, charging component 214 and connection locality module 210
may communicate in a wired or wireless fashion, as mentioned
previously, without bridges 120 and 120'. The wired or wireless
communication may utilize any sort of connection technology known
in the art, such as Ethernet or RF communication, such as Zigbee,
or Bluetooth.
[0059] System Layouts
[0060] FIG. 4 shows a layout 400 of the power aggregation system
100. The flow control center 102 can be connected to many different
entities, e.g., via the Internet 104, for communicating and
receiving information. The layout 400 includes electric resources
112, such as plug-in electric vehicles 200, physically connected to
the grid within a single control area 402. The electric resources
112 become an energy resource for grid operators 404 to
utilize.
[0061] The layout 400 also includes end users 406 classified into
electric resource owners 408 and electrical connection location
owners 410, who may or may not be one and the same. In fact, the
stakeholders in a power aggregation system 100 include the system
operator at the flow control center 102, the grid operator 404, the
resource owner 408, and the owner of the location 410 at which the
electric resource 112 is connected to the power grid 114.
[0062] Electrical connection location owners 410 can include:
[0063] Rental car lots--rental car companies often have a large
portion of their fleet parked in the lot. They can purchase fleets
of electric vehicles 200 and, participating in a power aggregation
system 100, generate revenue from idle fleet vehicles.
[0064] Public parking lots--parking lot owners can participate in
the power aggregation system 100 to generate revenue from parked
electric vehicles 200. Vehicle owners can be offered free parking,
or additional incentives, in exchange for providing power
services.
[0065] Workplace parking--employers can participate in a power
aggregation system 100 to generate revenue from parked employee
electric vehicles 200. Employees can be offered incentives in
exchange for providing power services.
[0066] Residences--a home garage can merely be equipped with a
connection locality module 210 to enable the homeowner to
participate in the power aggregation system 100 and generate
revenue from a parked car. Also, the vehicle battery 202 and
associated power electronics within the vehicle can provide local
power backup power during times of peak load or power outages.
[0067] Residential neighborhoods--neighborhoods can participate in
a power aggregation system 100 and be equipped with power-delivery
devices (deployed, for example, by homeowner cooperative groups)
that generate revenue from parked electric vehicles 200.
[0068] The grid operations 116 of FIG. 4 collectively include
interactions with energy markets 412, the interactions of grid
operators 404, and the interactions of automated grid controllers
118 that perform automatic physical control of the power grid
114.
[0069] The flow control center 102 may also be coupled with
information sources 414 for input of weather reports, events, price
feeds, etc. Other data sources 414 include the system stakeholders,
public databases, and historical system data, which may be used to
optimize system performance and to satisfy constraints on the power
aggregation system 100.
[0070] Thus, a power aggregation system 100 may consist of
components that:
[0071] communicate with the electric resources 112 to gather data
and actuate charging/discharging of the electric resources 112;
[0072] gather real-time energy prices;
[0073] gather real-time resource statistics;
[0074] predict behavior of electric resources 112 (connectedness,
location, state (such as battery State-Of-Charge) at a given time
of interest, such as a time of connect/disconnect);
[0075] predict behavior of the power grid 114/load;
[0076] encrypt communications for privacy and data security;
[0077] actuate charging of electric vehicles 200 to optimize some
figure(s) of merit;
[0078] offer guidelines or guarantees about load availability for
various points in the future, etc.
[0079] These components can be running on a single computing
resource (computer, etc.), or on a distributed set of resources
(either physically co-located or not).
[0080] Power aggregation systems 100 in such a layout 400 can
provide many benefits: for example, lower-cost ancillary services
(i.e., power services), fine-grained (both temporal and spatial)
control over resource scheduling, guaranteed reliability and
service levels, increased service levels via intelligent resource
scheduling, and/or firming of intermittent generation sources such
as wind and solar power generation.
[0081] The power aggregation system 100 enables a grid operator 404
to control the aggregated electric resources 112 connected to the
power grid 114. An electric resource 112 can act as a power source,
load, or storage, and the resource 112 may exhibit combinations of
these properties. Control of a set of electric resources 112 is the
ability to actuate power consumption, generation, or energy storage
from an aggregate of these electric resources 112.
[0082] FIG. 5 shows the role of multiple control areas 402 in the
power aggregation system 100. Each electric resource 112 can be
connected to the power aggregation system 100 within a specific
electrical control area. A single instance of the flow control
center 102 can administer electric resources 112 from multiple
distinct control areas 501 (e.g., control areas 502, 504, and 506).
In one implementation, this functionality is achieved by logically
partitioning resources within the power aggregation system 100. For
example, when the control areas 402 include an arbitrary number of
control areas, control area "A" 502, control area "B" 504, . . . ,
control area "n" 506, then grid operations 116 can include
corresponding control area operators 508, 510, . . . , and 512.
Further division into a control hierarchy that includes control
division groupings above and below the illustrated control areas
402 allows the power aggregation system 100 to scale to power grids
114 of different magnitudes and/or to varying numbers of electric
resources 112 connected with a power grid 114.
[0083] FIG. 6 shows a layout 600 of a power aggregation system 100
that uses multiple centralized flow control centers 102 and 102'
and a directory server 602 for determining a flow control center.
Each flow control center 102 and 102' has its own respective end
users 406 and 406'. Control areas 402 to be administered by each
specific instance of a flow control center 102 can be assigned
dynamically. For example, a first flow control center 102 may
administer control area A 502 and control area B 504, while a
second flow control center 102' administers control area n 506.
Likewise, corresponding control area operators (508, 510, and 512)
are served by the same flow control center 102 that serves their
respective different control areas.
[0084] In various embodiments, an electric resource may determine
which flow control center 102/102' administers its control area
502/504/506 by communicating with a directory server 602. The
address of the directory server 602 may be known to electric
resource 112 or its associated IPF module 134 or charging component
214. Upon plugging in, the electric resource 112 may communicate
with the directory server 602, providing the directory server 112
with a resource identifier and/or a location identifier. Based on
this information, the directory server 602 may respond, identifying
which flow control center 102/102' to use.
[0085] In another embodiment, directory server 602 may be
integrated with a flow control server 106 of a flow control center
102/102'. In such an embodiment, the electric resource 112 may
contact the server 106. In response, the server 106 may either
interact with the electric resource 112 itself or forward the
connection to another flow control center 102/102' responsible for
the location identifier provided by the electric resource 112.
[0086] In some embodiments, whether integrated with a flow control
server 106 or not, directory server 602 may include a publicly
accessible database for mapping locations to flow control centers
102/102'.
[0087] Flow Control Server
[0088] FIG. 7 shows a server 106 of the flow control center 102.
The illustrated implementation in FIG. 7 is only one example
configuration, for descriptive purposes. Many other arrangements of
the illustrated components or even different components
constituting a server 106 of the flow control center 102 are
possible within the scope of the subject matter. Such a server 106
and flow control center 102 can be executed in hardware, software,
or combinations of hardware, software, firmware, etc.
[0089] The flow control server 106 includes a connection manager
702 to communicate with electric resources 112, a prediction engine
704 that may include a learning engine 706 and a statistics engine
708, a constraint optimizer 710, and a grid interaction manager 712
to receive grid control signals 714. Grid control signals 714 are
sometimes referred to as generation control signals, such as
automated generation control (AGC) signals. The flow control server
106 may further include a database/information warehouse 716, a web
server 718 to present a user interface to electric resource owners
408, grid operators 404, and electrical connection location owners
410; a contract manager 720 to negotiate contract terms with energy
markets 412, and an information acquisition engine 414 to track
weather, relevant news events, etc., and download information from
public and private databases 722 for predicting behavior of large
groups of the electric resources 112, monitoring energy prices,
negotiating contracts, etc.
[0090] Remote IPF Module
[0091] FIG. 8A shows the remote IPF module 134 of FIGS. 1 and 2 in
greater detail. The illustrated remote IPF module 134 is only one
example configuration, for descriptive purposes. Many other
arrangements of the illustrated components or even different
components constituting a remote IPF module 134 are possible within
the scope of the subject matter. Such a remote IPF module 134 has
some hardware components and some components that can be executed
in hardware, software, or combinations of hardware, software,
firmware, etc. In other embodiments, executable instructions
configured to perform some or all of the operations of remote IPF
module 134 may be added to hardware of an electric resource 112
such as an electric vehicle that, when combined with the executable
instructions, provides equivalent functionality to remote IPF
module 134. References to remote IPF module 134 as used herein
include such executable instructions.
[0092] The illustrated example of a remote IPF module 134 is
represented by an implementation suited for an electric vehicle
200. Thus, some vehicle systems 800 are included as part of the
remote IPF module 134 for the sake of description. However, in
other implementations, the remote IPF module 134 may exclude some
or all of the vehicles systems 800 from being counted as components
of the remote IPF module 134.
[0093] The depicted vehicle systems 800 include a vehicle computer
and data interface 802, an energy storage system, such as a battery
bank 202, and an inverter/charger 804. Besides vehicle systems 800,
the remote IPF module 134 also includes a communicative power flow
controller 806. The communicative power flow controller 806 in turn
includes some components that interface with AC power from the grid
114, such as a powerline communicator, for example an
Ethernet-over-powerline bridge 120, and a current or
current/voltage (power) sensor 808, such as a current sensing
transformer.
[0094] The communicative power flow controller 806 also includes
Ethernet and information processing components, such as a processor
810 or microcontroller and an associated Ethernet media access
control (MAC) address 812; volatile random access memory 814,
nonvolatile memory 816 or data storage, an interface such as an
RS-232 interface 818 or a CANbus interface 820; an Ethernet
physical layer interface 822, which enables wiring and signaling
according to Ethernet standards for the physical layer through
means of network access at the MAC/Data Link Layer and a common
addressing format. The Ethernet physical layer interface 822
provides electrical, mechanical, and procedural interface to the
transmission medium--i.e., in one implementation, using the
Ethernet-over-powerline bridge 120. In a variation, wireless or
other communication channels with the Internet 104 are used in
place of the Ethernet-over-powerline bridge 120.
[0095] The communicative power flow controller 806 also includes a
bidirectional power flow meter 824 that tracks power transfer to
and from each electric resource 112, in this case the battery bank
202 of an electric vehicle 200.
[0096] The communicative power flow controller 806 operates either
within, or connected to an electric vehicle 200 or other electric
resource 112 to enable the aggregation of electric resources 112
introduced above (e.g., via a wired or wireless communication
interface). These above-listed components may vary among different
implementations of the communicative power flow controller 806, but
implementations typically include: [0097] an intra-vehicle
communications mechanism that enables communication with other
vehicle components; [0098] a mechanism to communicate with the flow
control center 102; [0099] a processing element; [0100] a data
storage element; [0101] a power meter; and [0102] optionally, a
user interface.
[0103] Implementations of the communicative power flow controller
806 can enable functionality including: [0104] executing
pre-programmed or learned behaviors when the electric resource 112
is offline (not connected to Internet 104, or service is
unavailable); [0105] storing locally-cached behavior profiles for
"roaming" connectivity (what to do when charging on a foreign
system, i.e., when charging in the same utility territory on a
foreign meter or in a separate utility territory, or in
disconnected operation, i.e., when there is no network
connectivity); [0106] allowing the user to override current system
behavior; and [0107] metering power-flow information and caching
meter data during offline operation for later transaction.
[0108] Thus, the communicative power flow controller 806 includes a
central processor 810, interfaces 818 and 820 for communication
within the electric vehicle 200, a powerline communicator, such as
an Ethernet-over-powerline bridge 120 for communication external to
the electric vehicle 200, and a power flow meter 824 for measuring
energy flow to and from the electric vehicle 200 via a connected AC
powerline 208.
[0109] Power Flow Meter
[0110] Power is the rate of energy consumption per interval of
time. Power indicates the quantity of energy transferred during a
certain period of time, thus the units of power are quantities of
energy per unit of time. The power flow meter 824 measures power
for a given electric resource 112 across a bidirectional
flow--e.g., power from grid 114 to electric vehicle 200 or from
electric vehicle 200 to the grid 114. In one implementation, the
remote IPF module 134 can locally cache readings from the power
flow meter 824 to ensure accurate transactions with the central
flow control server 106, even if the connection to the server is
down temporarily, or if the server itself is unavailable.
[0111] Transceiver and Charging Component
[0112] FIG. 8B shows the transceiver 212 and charging component 214
of FIG. 2B in greater detail. The illustrated transceiver 212 and
charging component 214 is only one example configuration, for
descriptive purposes. Many other arrangements of the illustrated
components or even different components constituting the
transceiver 212 and charging component 214 are possible within the
scope of the subject matter. Such a transceiver 212 and charging
component 214 have some hardware components and some components
that can be executed in hardware, software, or combinations of
hardware, software, firmware, etc.
[0113] The illustrated example of the transceiver 212 and charging
component 214 is represented by an implementation suited for an
electric vehicle 200. Thus, some vehicle systems 800 are
illustrated to provide context to the transceiver 212 and charging
component 214 components.
[0114] The depicted vehicle systems 800 include a vehicle computer
and data interface 802, an energy storage system, such as a battery
bank 202, and an inverter/charger 804. In some embodiments, vehicle
systems 800 may include a data port, such as an OBD-II port, that
is capable of physically coupling with the transceiver 212. The
transceiver 212 may then communicate with the vehicle computer and
data interface 802 through the data port, receiving information
from electric resource 112 comprised by vehicle systems 800 and, in
some embodiments, providing commands to the vehicle computer and
data interface 802. In one implementation, the vehicle computer and
data interface 802 may be capable of charge control management. In
such an embodiment, the vehicle computer and data interface 802 may
perform some or all of the charging component 214 operations
discussed below. In other embodiments, executable instructions
configured to perform some or all of the operations of the vehicle
computer and data interface 802 may be added to hardware of an
electric resource 112 such as an electric vehicle that, when
combined with the executable instructions, provides equivalent
functionality to the vehicle computer and data interface 802.
References to the vehicle computer and data interface 802 as used
herein include such executable instructions.
[0115] In various embodiments, the transceiver 212 may have a
physical form that is capable of coupling to a data port of vehicle
systems 800. Such a transceiver 212 may also include a plurality of
interfaces, such as an RS-232 interface 818 and/or a CANBus
interface 820. In various embodiments, the RS-232 interface 818 or
CANBus interface 820 may enable the transceiver 212 to communicate
with the vehicle computer and data interface 802 through the data
port. Also, the transceiver may be or comprise an additional
interface (not shown) capable of engaging in wireless communication
with a data interface 820 of the charging component 214. The
wireless communication may be of any form known in the art, such as
radio frequency (RF) communication (e.g., Zigbee, and/or
Bluetooth.TM. communication). In other embodiments, the transceiver
may comprise a separate conductor or may be configured to utilize a
powerline 208 to communicate with charging component 214. In yet
other embodiments, not shown, transceiver 212 may simply be a radio
frequency identification (RFID) tag capable of storing minimal
information about the electric resource 112, such as a resource
identifier, and of being read by a corresponding RFID reader of
charging component 214. In such other embodiments, the RFID tag
might not couple with a data port or communicate with the vehicle
computer and data interface 802.
[0116] As shown, the charging component 214 may be an intelligent
plug device that is physically connected to a charging medium, such
as a powerline 208 (the charging medium coupling the charging
component 214 to the electric resource 112) and an outlet of a
power grid (such as the wall outlet 204 shown in FIG. 2B). In other
embodiments charging component 214 may be a charging station or
some other external control. In some embodiments, the charging
component 214 may be portable.
[0117] In various embodiments, the charging component 214 may
include components that interface with AC power from the grid 114,
such as a powerline communicator, for example an
Ethernet-over-powerline bridge 120, and a current or
current/voltage (power) sensor 808, such as a current sensing
transformer.
[0118] In other embodiments, the charging component 214 may include
a further Ethernet plug or wireless interface in place of bridge
120. In such an embodiment, data-over-powerline communication is
not necessary, eliminating the need for a bridge 120. The Ethernet
plug or wireless interface may communicate with a local access
point, and through that access point to flow control server
106.
[0119] The charging component 214 may also include Ethernet and
information processing components, such as a processor 810 or
microcontroller and an associated Ethernet media access control
(MAC) address 812; volatile random access memory 814, nonvolatile
memory 816 or data storage, a data interface 826 for communicating
with the transceiver 212, and an Ethernet physical layer interface
822, which enables wiring and signaling according to Ethernet
standards for the physical layer through means of network access at
the MAC/Data Link Layer and a common addressing format. The
Ethernet physical layer interface 822 provides electrical,
mechanical, and procedural interface to the transmission
medium--i.e., in one implementation, using the
Ethernet-over-powerline bridge 120. In a variation, wireless or
other communication channels with the Internet 104 are used in
place of the Ethernet-over-powerline bridge 120.
[0120] The charging component 214 may also include a bidirectional
power flow meter 824 that tracks power transfer to and from each
electric resource 112, in this case the battery bank 202 of an
electric vehicle 200.
[0121] Further, in some embodiments, the charging component 214 may
comprise an RFID reader to read the electric resource information
from transceiver 212 when transceiver 212 is an RFID tag.
[0122] Also, in various embodiments, the charging component 214 may
include a credit card reader to enable a user to identify the
electric resource 112 by providing credit card information. In such
an embodiment, a transceiver 212 may not be necessary.
[0123] Additionally, in one embodiment, the charging component 214
may include a user interface, such as one of the user interfaces
described in greater detail below.
[0124] Implementations of the charging component 214 can enable
functionality including: [0125] executing pre-programmed or learned
behaviors when the electric resource 112 is offline (not connected
to Internet 104, or service is unavailable); [0126] storing
locally-cached behavior profiles for "roaming" connectivity (what
to do when charging on a foreign system or in disconnected
operation, i.e., when there is no network connectivity); [0127]
allowing the user to override current system behavior; and [0128]
metering power-flow information and caching meter data during
offline operation for later transaction.
[0129] User Interfaces (UI)
[0130] Charging Station UI. An electrical charging station, whether
free or for pay, can be installed with a user interface that
presents useful information to the user. Specifically, by
collecting information about the grid 114, the electric resource
state, and the preferences of the user, the station can present
information such as the current electricity price, the estimated
recharge cost, the estimated time until recharge, the estimated
payment for uploading power to the grid 114 (either total or per
hour), etc. The information acquisition engine 414 communicates
with the electric resource 112 and with public and/or private data
networks 722 to acquire the data used in calculating this
information.
[0131] The types of information gathered from the electric resource
112 could include an electric resource identifier (resource ID) and
state information like the state of charge of the electric resource
112. The resource ID could be used to obtain knowledge of the
electric resource type and capabilities, preferences, etc. through
lookup with the flow control server 106.
[0132] In various embodiments, the charging station system
including the UI might also gather grid-based information, such as
current and future energy costs at the charging station.
[0133] User Charge Control UI Mechanisms. In various embodiments,
by default, electric resources 112 may receive charge control
management via power aggregation system 100. In some embodiments,
an override control may be provided to override charge control
management and charge as soon as possible. The override control may
be provided, in various embodiments, as a user interface mechanism
of the remote IPF module 134, the charging component 214, of the
electric resource (for example, if electric resource is a vehicle
200, the user interface control may be integrated with dash
controls of the vehicle 200) or even via a web page offered by flow
control server 106. The control could be presented, for example, as
a button, a touch screen option, a web page, or some other UI
mechanism. In one embodiment, the UI may be the UI illustrated by
FIG. 8C and discussed in greater detail below. In some embodiments,
the override would be a one-time override, only applying to a
single plug-in session. Upon disconnecting and reconnecting, the
user may again need to interact with the UI mechanism to override
the charge control management.
[0134] In some embodiments, the user may pay more to charge with
the override on than under charge control management, thus
providing an incentive for the user to accept charge control
management. Such a cost differential may be displayed or rendered
to the user in conjunction with or on the UI mechanism. This
differential could take into account time-varying pricing, such as
Time of Use (TOU), Critical Peak Pricing (CPP), and Real-Time
Pricing (RTP) schemes, as discussed above, as well as any other
incentives, discounts, or payments that might be forgone by not
accepting charge control management.
[0135] UI Mechanism for Management Preferences. In various
embodiments, a user interface mechanism of the remote IPF module
134, the charging component 214, of the electric resource (for
example, if electric resource is a vehicle 200, the user interface
control may be integrated with dash controls of the vehicle 200) or
even via a web page offered by flow control server 106 may enable a
user to enter and/or edit management preferences to affect charge
control management of the user's electric resource 112. In some
embodiments, the UI mechanism may allow the user to enter/edit
general preferences, such as whether charge control management is
enabled, whether vehicle-to-grid power flow is enabled or whether
the electric resource 112 should only be charged with clean/green
power. Also, in various embodiments, the UI mechanism may enable a
user to prioritize relative desires for minimizing costs,
maximizing payments (i.e., fewer charge periods for higher
amounts), achieving a full state-of-charge for the electric
resource 112, charging as rapidly as possible, and/or charging in
as environmentally-friendly a way as possible. Additionally, the UI
mechanism may enable a user to provide a default schedule for when
the electric resource will be used (for example, if resource 112 is
a vehicle 200, the schedule would be for when the vehicle 200
should be ready to drive). Further, the UI mechanism may enable the
user to add or select special rules, such as a rule not to charge
if a price threshold is exceeded or a rule to only use charge
control management if it will earn the user at least a specified
threshold of output. Charge control management may then be
effectuated based on any part or all of these user entered
preferences.
[0136] Simple User Interface. FIG. 8C illustrates a simple user
interface (UI) which enables a user to control charging based on
selecting among a limited number of high level preferences. For
example, UI 2300 includes the categories "green", "fast", and
"cheap" (with what is considered "green", "fast", and "cheap"
varying from embodiment to embodiment). The categories shown in UI
2300 are selected only for the sake of illustration and may instead
includes these and/or any other categories applicable to electric
resource 112 charging known in the art. As shown, the UI 2300 may
be very basic, using well known form controls such as radio
buttons. In other embodiments, other graphic controls known in the
art may be used. The general categories may be mapped to specific
charging behaviors, such as those discussed above, by a flow
control server 106.
[0137] Electric Resource Communication Protocol
[0138] FIG. 9 illustrates a resource communication protocol. As
shown, a remote IPF module 134 or charging component 214 may be in
communication with a flow control server 106 over the Internet 104
or another networking fabric or combination of networking fabrics.
In various embodiments, a protocol specifying an order of messages
and/or a format for messages may be used to govern the
communications between the remote IPF module 134 or charging
component 214 and flow control server 106.
[0139] In some embodiments, the protocol may include two channels,
one for messages initiated by the remote IPF module 134 or charging
component 214 and for replies to those messages from the flow
control server 106, and another channel for messages initiated by
the flow control server 106 and for replies to those messages from
the remote IPF module 134 or charging component 214. The channels
may be asynchronous with respect to each other (that is, initiation
of messages on one channel may be entirely independent of
initiation of messages on the other channel). However, each channel
may itself be synchronous (that is, once a message is sent on a
channel, another message may not be sent until a reply to the first
message is received).
[0140] As shown, the remote IPF module 134 or charging component
214 may initiate communication 902 with the flow control server
106. In some embodiments, communication 902 may be initiated when,
for example, an electric resource 112 first plugs in/connects to
the power grid 114. In other embodiments, communication 902 may be
initiated at another time or times. The initial message 902
governed by the protocol may require, for example, one or more of
an electric resource identifier, such as a MAC address, a protocol
version used, and/or a resource identifier type.
[0141] Upon receipt of the initial message by the flow control
server 106, a connection may be established between the remote IPF
module 134 or charging component 214 and flow control server 106.
Upon establishing a connection, the remote IPF module 134 or
charging component 214 may register with flow control server 106
through a subsequent communication 903. Communication 903 may
include a location identifier scheme, a latitude, a longitude, a
max power value that the remote IPF module 134 or charging
component 214 can draw, a max power value that the remote IPF
module 134 or charging component 214 can provide, a current power
value, and/or a current state of charge.
[0142] After the initial message 902, the protocol may require or
allow messages 904 from the flow control server 106 to the remote
IPF module 134 or charging component 214 or messages 906 from
remote IPF module 134 or charging component 214 to the flow control
server 106. The messages 904 may include, for example, one or more
of commands, messages, and/or updates. Such messages 904 may be
provided at any time after the initial message 902. In one
embodiment, messages 904 may include a command setting, a power
level and/or a ping to determine whether the remote IPF module 134
or charging component 214 is still connected.
[0143] The messages 906 may include, for example, status updates to
the information provided in the registration message 903. Such
messages 906 may be provided at any time after the initial message
902. In one embodiment, the messages 906 may be provided on a
pre-determined time interval basis. In various embodiments,
messages 906 may even be sent when the remote IPF module 134 or
charging component 214 is connected, but not registered. Such
messages 906 may include data that is stored by flow control server
106 for later processing. Also, in some embodiments, messages 904
may be provided in response to a message 902 or 906.
[0144] Site Power Flow Manager
[0145] Modern electric vehicles benefit in a variety of ways from a
centrally controlled smart charging program where a central server
coordinates the charging activities of a number of vehicles. While
many such smart charging programs may be operated by electric
utilities to control electric vehicles over a wide area, many of
the benefits of a smart charging program can be realized at a local
level by the operator of a facility operating in isolation from the
any other entity. In a place where multiple plug-in vehicles may
park and connect to the grid, it is valuable to have site-level
charging management.
[0146] As shown in FIG. 10, the charging process of electric
vehicles 1000 is managed by a site power flow manager 1010 at the
site-level 1020. Site-level charging management is an important
feature at charging locations where multiple plug-in electric
vehicles 1000 may park and connect to the grid 1030. Such
locations/sites 1020 may include public or private parking lots, or
the base of operations for a fleet.
[0147] There are a number of benefits for managing the power flow
at the site-level. Having control over the flow of power is useful
when, for example, the grid connection 1030 at the site 1020 is not
capable of supporting every electric vehicle 1000, and/or other
devices on site, that is simultaneously drawing power. In some
instances, the wiring to specific charge points 1040 at the site,
or to banks of charge points at the site 1020, may not be capable
of supporting every vehicle 1000 drawing power at the same time.
Many sites are subject to demand charges based on peak power draw
during a time period (e.g. month), so avoiding power spikes can
also save money. Furthermore, power usage can be tuned to the
specific electric rate structure of the site.
[0148] A site power flow manager 1010 could address these issues,
inter alia. Providing a power flow management system at the
site-level allows important information to be taken as input,
including but not limited to: electrical meter data for the site
1020 as a whole, and/or electrical meter data for specific charge
points 1040 or banks of charge points. In addition, the system can
consider information from devices, such as plug-in vehicles 1000,
at the site that are connected to the electric grid 1030. Such
information might be transmitted in a variety of ways, including by
a power-line carrier or a wireless means. This information may
include a unique identifier, resource type, current state of
charge, and max power in/out levels. Further, the system can
receive information about the electric rate structure of the site,
and information about the electrical topology and power limitations
of various circuits within the site. A connection to a power flow
manager 1010 operates at a higher level of the grid topology, i.e.
at the substation level or the control area level, so that the site
power flow manager 1010 can receive information and also respond to
requests, such as a demand response event, a reserves call,
renewable resource following, or system regulation. In one
embodiment, the site power flow manager 1010 and the higher level
site controller can have priority rules, e.g. not overloading local
circuits takes priority over remote requests.
[0149] A site power flow manager 1010 can analyze the current, and
the predicted future, state of the world. In doing so, the site
power flow manager 1010 can make various determinations, including
whether or not to allow certain devices/vehicles 1000 to draw
power. In addition, site power flow manager 1010 can request that
the devices/vehicles 1000 provide power, and further control the
power levels of the devices/vehicles 1000. These decisions could be
made within constraints, such as not overloading a circuit or going
over a certain total power draw. Such constraints may be performed,
as in one embodiment, with prioritization, such as optimizing to
get power to certain devices versus others. For example, the site
power flow manager 1010 may charge vehicles 1000 that are at the
lowest state of charge, that have been plugged in the longest, or
that have priority for recharge. In an embodiment, the site power
flow manager 1010 may allow for optimizing with regard to the
overall site electric cost minimization or total cost minimization,
or to recharge in the greenest, most efficient meaner.
[0150] Decisions made by the site power flow manager 1010 can be
carried out in several ways, including controlling relays to open
or close certain circuits. In addition, the site power flow manager
1010 can communicate with smart charging points 1040 or smart banks
of charging points 1040 to control certain circuits or devices 1000
on those circuits. The site power flow manager 1010 may also
communicate with the devices 1000 to give them a request or command
for their power flow behavior, such as telling a vehicle 1000 to
charge at half power or to recharge in an efficient manner. Such
communications may traverse via a smart charging point 1040 or bank
thereof. The site power flow manager 1010 may be located at the
site 1020 being managed, but can also located remote to the site
1020.
[0151] FIG. 11 illustrates the site-level charging of electrical
devices by a power flow manager 1110. The power flow manager
receives site-level information 1120, and makes power flow
decisions based on the site-level information 1130. In addition,
power flow to the electrical devices is managed by the power flow
manager 1140, such that the power flow manager responds to requests
including demand response event, reserves call, renewable resource
following, or system regulation.
[0152] Meta-Optimization Across Multiple Power Flow Management
Strategies
[0153] Managing one or an aggregation of power resources (such as
load, generation, storage, plug-in vehicles), power flow manager
can use the combined capabilities of the assets under its control
to implement a variety of beneficial services. These services may
include regulation, spinning reserve, and/or peak avoidance.
Regulation involves increasing or decreasing the load present on
the grid in real time in order to maintain balance between power
production and power consumption in the entire grid. Spinning
reserve provides the ability to quickly make up a large amount of
missing power after the failure of a generation or transmission
asset within the grid. Peak avoidance results in reducing peak
power consumption for the day, which is typically the most
expensive power for the utility to provide.
[0154] There are many other similar services, such as to provide
capacity or to provide renewable generation following. As the power
flow manager may use any number of different strategies to decide
how to dispatch the resources under management, it will be
understood by those skilled in the art that other strategies, and
combinations thereof, may be implemented in various embodiments. In
one embodiment, the power flow manager may be a site power flow
manager 1010, as shown in FIG. 10.
[0155] Such services provide a substantial cost savings to an
electric utility. In many circumstances, it is also possible for a
utility or other operator to sell these services through an energy
market. While each of these services have very distinct
characteristics from the perspective of the electric utility, the
services are each implemented in fundamentally the same way on the
power resource endpoint. That is, by selectively flowing power in
to or out of the power resource in response to commands from the
central power flow manager.
[0156] Because the same pool of resources can be used to implement
each of the possible services, a conflict arises. As an example, If
an entire population of electric vehicles is committed entirely to
regulation services, that population not be able to fully
participate in a peak avoidance program. Because the relative costs
and benefits of the various services change over time, it is
undesirable to simply pick the most valuable service and commit all
the assets to it all of the time.
[0157] Given a set of such strategies, a meta-optimizer decides
which strategy to use at appropriate times. The meta-optimizer may
be located within the power flow manager. The meta-optimizer
determines which resources are to be used in implementing a
strategy. The determination may be based on a variety of factors,
such as maximizing value generated and/or minimizing environmental
impact. In an embodiment, the meta-optimizer chooses the strategy
that is likely to generate the most value for a given time period,
e.g. the next hour. The implementation may have a value function
associated with each strategy, and then take the maximum value
across all strategies.
[0158] The decision may vary by grid topological location. For
example, if a given feeder is overloaded, the best decision for
resources on that feeder may be to reduce the load, even if
elsewhere on the grid a different strategy or action may be
best.
[0159] The decision may also take into account multiple component
requirements. For example, in managing plug-in vehicle recharging,
it may be desirable to get vehicles recharged in a timely fashion,
while also maximizing value created through other services
provided.
[0160] In one embodiment, the decision may be based on predictions
about the future. For example, it may be worth a certain amount at
hour N to take some action, such as charging plug-in vehicles to
provide down regulation. However, if that means the resources might
be unavailable at hour N+1, when the resource may be worth more
than at hour N, then the meta-optimizer might delay the action so
that the resource is available to provide more value.
[0161] FIG. 12 shows an embodiment of a method for managing power
flow by optimizing multiple power flow management strategies
including coordinating charging activities 1210 and controlling
power flow service 1220. A meta-optimizer can choose a power flow
management strategy and an electrical device 1230 such that the
power flow manager may implement the power flow management
strategies 1240.
[0162] Avoiding Power Spikes During Energy Management Failures
[0163] Historically, utilities had to depend on the independent and
random nature of electrical loads on the grid. While an individual
electrical load is unpredictable and can be switched on or off at
any time, each load is only a small part of total power
consumption. The large number of individual loads on the electrical
system provides a form of smoothing. Electrical consumption
increases and decreases over time, but the overall change
fluctuates along a somewhat predictable curve and power companies
are able to adjust power production to match consumption.
[0164] In distributed energy management systems where
communications are not 100% reliable, it is important that no loss
of communications between the elements of the system or unexpected
system controller failure cause unexpected system behavior. One
particular behavior to be avoided is an unexpected, coordinated
action across distributed resources that results from a failure
mode. For example, when a controller suffers a failure, it could be
detrimental to the electrical grid if all distributed resources
started drawing power from the grid simultaneously.
[0165] The introduction of a smart charging or energy management
system causes otherwise isolated loads to potentially operate in
concert. This creates the possibility of adverse coordinated action
in the event of system failure. In particular, if each electrical
load is designed to revert to a maximum energy consumption level in
the case of communications loss, then a failure of the management
system may result in an instantaneous and coordinated spike in
electricity demand. When the population of controlled devices is
sufficiently large, the spike in demand can exceed the utility's
capacity for rapid adjustment and result in a blackout.
[0166] An example of a failure mode includes failed communications
between individual resources and the master controller or
controllers. Communications can also fail between a controller and
some or all of the resources. In addition, a controller or a set of
controllers can fail in a non-network related way that renders such
controllers incapable of communicating with the resources. A
failure mode may also be a design defect shared by a large
population of resources causing the population to simultaneously
lose communications capabilities when an unexpected event
occurred.
[0167] In the case of any failure mode, the system behavior should
be predictable and non-disruptive. To prevent disruptive impacts on
the grid as a whole, endpoints normally controlled by a central
energy management server may employ a variety of safe failure
modes. A system for maintaining predictable behavior may include a
distributed resource with various capabilities, including the
ability to receive/enact a sequence of commands to be executed at
one or various points in time.
[0168] An example of a safe failure mode includes maintaining
stable (non-changing) behavior for a defined period of time around
a failure event. For example, after communications is lost, an
isolated EVSE can continue charging at the rate last specified by
the charge management controller. After some period of time, the
EVSE may slowly transition to a different autonomous strategy.
[0169] Another safe failure mode includes executing a pre-arranged
behavior in the event of a failure condition. As an example, if a
group of EVSE's was connected to a electrical circuit that was only
capable of providing 70% of the combined maximum power draw of the
group, each EVSE could be pre-programmed to operate at 70% of
capacity in the event of communications failure.
[0170] Yet another safe failure mode includes executing state
transitions in pre-arranged behaviors at the determined time offset
by a random interval of time. As an example, EVSE's that are off
when communications fail could wait a random amount of time between
0 and 30 minutes before powering on. This random startup causes the
increase in power consumption to be spread over time, allowing the
utility the opportunity to respond.
[0171] A safe failure mode may also include using predictions about
resource behaviors, such as the comings and goings from the system,
to further enhance the estimate of the state of the world. As an
example, if an EVSE is normally commanded to consume power along a
curve (to harmonize with grid conditions), the EVSE could be
programmed to follow type-based typical curve in the absence of
communications. Since the central smart charging system would know
the curve the detached EVSE was following, its behavior could still
be input in to the charge management algorithms.
[0172] FIG. 13 illustrates an embodiment for managing power flow
using safe failure modes including coordinating charging activities
of electrical devices 1310 and detecting a system failure event
1320. The power flow manager implements a safe failure mode 1330
that provides predictable and non-disruptive system behavior.
[0173] Generation-Stack-Aware Dispatch of Resources
[0174] One potential goal of a distributed energy management system
is to dispatch resources to minimize cost. A basic cost reduction
strategy is to reduce electricity consumption when electricity
prices are high. This basic strategy reduces the cost of
electricity consumed by the endpoints under active management.
[0175] A more advanced strategy could manipulate the electricity
consumed by controlled endpoints in a way that impacts the market
price of power. Such a system can reduce the cost of providing
power to all devices within a utility's service area, not just
those under active management.
[0176] In many regions, power production is managed by separate
entities from the utilities responsible for distribution. Utilities
purchase electricity from Power producers, and re-sell it to their
customers.
[0177] Often, the transactions between power producers and
distribution utilities take place in formalized market. Such a
market typically operates as a single price auction. In such a
market, each power producer states the price at which they are
willing to provide power, and power production is allocated to the
cheapest producers first, moving up the stack to more expensive
produces until sufficient power has been obtained. The last
(highest) price selected set the price that all power producers are
paid.
[0178] Each type of generation asset in an energy generation
system, such as the electrical grid, has a marginal cost.
Generation assets are dispatched in the order of increasing
marginal cost. The most expensive generator dispatched at any time
sets the cost basis for energy generation.
[0179] Different types of power plants have sharply different
marginal costs of operation. For example, Hydroelectric is often
much cheaper than gas turbines. As a result, there may be a sharp
increase in the cost of electricity as available hydro is
exhausted, and the gas turbines begin coming online.
[0180] At times, a distributed energy manager can remove enough
load from the system to eliminate the need for higher cost
generation, thereby decreasing the total cost to provide
service.
[0181] The distributed energy manager can minimize the total daily
cost to provide energy generation by forecasting total system and
dispatchable load. The distributed energy manager schedules
dispatchable load to draw power from the grid at times that will
minimize cost based on the available generation stack. Altering the
total price of power paid has a larger financial impact than the
amount paid specifically for automotive power. Also, moving the
market may be easier at one time of day than another. As a result,
dispatchable load will not always be scheduled to the lowest-cost
time of day, but rather when it will have the most beneficial
overall effect to the utility.
[0182] Further, the generation stack can change from region to
region, and load profiles and consumption can change daily.
Therefore, the present method will produce different dispatch
patterns in different regions.
[0183] FIG. 14 shows an embodiment of managing power flow using
generation stacks of power production to reduce cost of providing
power to electrical devices. Charge activities are coordinated by a
power flow manager 1410. A power production stack is controlled the
power flow manager 1420 such that the power production stack orders
available power. Based on a cost reduction strategy, a dispatchable
load is removed 1430. The dispatchable load is listed in the power
production stack.
[0184] Business Model of Selling Aggregated Power Resource
Management Services to Power Generators or Others
[0185] Power resource management services include aggregating the
following: plug-in vehicles, thermostats, residential or
commercial/industrial load, or fixed energy storage. Such services
provide regulation, reserves, load shifting, renewable resource
following, or peak avoidance. A power flow manager is able to
provide a variety of services that can improve the stability of the
electric grid. For example, electricity consumption of distributed
resources can be increased and decreased as necessary to absorb the
differences between electricity production and consumption on the
grid.
[0186] Customers for aggregated power resource management services
include electric utilities, ISOs, and TSOs. Such entities are
primarily responsible for the stability of the grid. But aggregated
power resource management services may be sold to various types of
power generators.
[0187] Some classes of electricity generation suffer from a high
degree of intermittency, meaning that their power production is
irregular. By bundling this irregular power production with the
smoothing/stabilizing abilities of aggregated power resource
management assets, it is possible to produce a higher grade of
wholesale power, which may be more easily sold in energy
markets.
[0188] In one example, a wind farm is the buyer of aggregated power
resource management services. Wind farms are susceptible to
fluctuations in the supply and demand of energy. For example,
prices for energy may drop drastically when the amount of wind is
great, or unexpectedly high. In addition, wind farms may be
temporarily disconnected from a grid when there is not enough
transmission or other capacity to absorb the power.
[0189] Economical issues resulting from such instability in the
supply or demand of energy can be effectively addressed by
providing owners of intermittent renewable generation with
aggregated power resource management services. Power generators may
increase their net load from the aggregated power resources when
there is a large and/or unexpectedly high amount of wind, and
decrease net load with there is a small and/or unexpectedly low
amount of wind.
[0190] In an embodiment, power generators can use aggregated power
resource management to smooth sudden ramping events in power
output, or to firm the power output to a desired level. The sum of
power generation plus net load from the aggregated power resources
can be made constant, or less susceptible to changes in the supply
or demand of energy.
[0191] As a result, power generators such as power plants may
retain the value of the energy they create. Such an integration
allow the operator of the generation asset to take direct action to
address the intermittency issues associated with their type of
generation. In some markets, this may be far more desirable than
waiting for other parties to provide such services through the
marketplace.
CONCLUSION
[0192] Although systems and methods have been described in language
specific to structural features and/or methodological acts, it is
to be understood that the subject matter defined in the appended
claims is not necessarily limited to the specific features or acts
described. Rather, the specific features and acts are disclosed as
examples of implementations of the claimed methods, devices,
systems, etc. It will be understood by those skilled in the art
that various changes in form and details may be made therein
without departing from the spirit and scope of the invention.
* * * * *