U.S. patent application number 17/316450 was filed with the patent office on 2021-08-26 for cloud computing smart solar configurator.
The applicant listed for this patent is Xendee Corporation. Invention is credited to Scott K. Mitchell, Adib Nasle, Michael Stadler.
Application Number | 20210264490 17/316450 |
Document ID | / |
Family ID | 1000005570264 |
Filed Date | 2021-08-26 |
United States Patent
Application |
20210264490 |
Kind Code |
A1 |
Nasle; Adib ; et
al. |
August 26, 2021 |
CLOUD COMPUTING SMART SOLAR CONFIGURATOR
Abstract
Systems, methods and non-transitory computer-readable storage
mediums are disclosed for cloud computing engineering, solar PV
(SPV) or solar PV with storage (SPV/S) system configuration,
pricing, quoting, advertising messaging, sales lead generation, and
content marketing.
Inventors: |
Nasle; Adib; (Poway, CA)
; Mitchell; Scott K.; (San Diego, CA) ; Stadler;
Michael; (Encinitas, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Xendee Corporation |
San Diego |
CA |
US |
|
|
Family ID: |
1000005570264 |
Appl. No.: |
17/316450 |
Filed: |
May 10, 2021 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
17099176 |
Nov 16, 2020 |
|
|
|
17316450 |
|
|
|
|
15896897 |
Feb 14, 2018 |
10839436 |
|
|
17099176 |
|
|
|
|
62459277 |
Feb 15, 2017 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 30/0611 20130101;
G06Q 30/0623 20130101; G06Q 50/06 20130101; G06Q 10/067 20130101;
G06Q 30/0641 20130101 |
International
Class: |
G06Q 30/06 20060101
G06Q030/06; G06Q 10/06 20060101 G06Q010/06; G06Q 50/06 20060101
G06Q050/06 |
Claims
1. A method comprising: generating, by a computing device, a base
case economic model for a virtual energy system, the base case
economic model based at least in part on a location of the virtual
energy system; generating, by the computing device, an objective
function model and one or more constraints for the virtual energy
system; calculating, by the computing device, a size of the virtual
energy system that achieves an objective function described by the
objective function model using the one or more constraints by
comparing an economic model of the virtual energy system with the
base case economic model; performing, by the computing device, a
simulation of the virtual energy system based on the calculated
size; generating, by the computing device, a virtual energy system
configuration based at least in part on results of the simulation;
and generating, by the computing device and based on the virtual
energy system, data for building a real-world version of the
virtual energy system.
2. The method of claim 1, wherein the virtual energy system is one
of a virtual solar photovoltaics (SPV) system, solar photovoltaics
with storage (SPV/S) system, or other distributed energy resources
system.
3. The method of claim 1, wherein the objective function model
comprises a data model, the one or more constraints technology
purchase or energy costs and loads.
4. The method of claim 3, wherein the data model includes
time-varying atmospheric data.
5. The method of claim 4, wherein the time-varying atmospheric data
includes future forecasted or annular solar irradiance, temperature
data and efficiency and power output ratings for solar panels.
6. The method of claim 1, wherein the base case economic model is
generated using energy purchased from an electrical utility to
supply a load at rates or tariffs charged by the electric utility
for the location of the virtual energy system.
7. The method of claim 1, wherein the objective function comprises
at least one energy cost minimization, carbon dioxide emission
minimization, resilience improvement, reliability improvement or
redundancy improvement.
8. The method of claim 1, wherein the objective function model
incorporates one or more technologies configured to operate within
one or more physical operating boundaries and one or more financial
constraints.
9. The method of claim 8, wherein the one or more physical
operating boundaries include a maximum rated electrical current
carrying capacity of power delivery equipment that make up an
electrical circuit of the virtual energy system.
10. The method of claim 8, wherein the one or more physical
operating boundaries are calculated by the simulation and include
at least one of power flow, transient stability, short circuit,
energy losses or loading of power delivery equipment that make up
an electrical circuit of the virtual energy system.
11. The method of claim 8, wherein the one or more physical
operating boundaries include an allowable voltage drop, short
circuit, harmonics, reliability, or transient stability at each
node in an electrical network of the virtual energy system in
two-dimensions or three-dimensions.
12. The method of claim 8, wherein the one or more financial
constraints include a maximum payback period or investment time
horizon.
13. The method of claim 1, wherein the data for building a
real-world version of the virtual energy system includes a bill of
materials (BOM).
14. The method of claim 1, further comprising: automatically
generating one-line or three-line electrical drawings based on the
virtual energy system design.
15. The method of claim 1, further comprising: automatically
generating a static snap-shot, quasi-static, time-series,
time-domain, or frequency domain power system simulation model of
the virtual energy system to obtain power system constraints for
the one or more physical operating boundaries.
16. The method of claim 1, wherein the objective function comprises
a combination of technologies to supply energy services required at
the location and to minimize costs or carbon dioxide emissions,
improve resilience, improve reliability or improve redundancy.
17. The method of claim 1, wherein the atmospheric data is
time-varying and includes solar irradiance, wind speed, and
temperature data at specified time-steps.
18. The method of claim 1, further comprising: automatically
generating a cost-optimal size for solar panels, storage technology
or other distributed energy technologies; and automatically
generating operation logic or dispatch for the storage technology
or other distributed energy technologies.
19. The method of claim 1, wherein the simulation is a power flow
simulation.
20. A system comprising: one or more processors; memory storing
instructions that when executed by the one or more processors,
cause the one or more processors to perform operations comprising.
generating a base case economic model for a virtual energy system,
the base case economic model based at least in part on a location
of the virtual energy system; generating an objective function
model and one or more constraints for the virtual energy system;
calculating a size of the virtual energy system that achieves an
objective function described by the objective function model using
the one or more constraints by comparing an economic model of the
virtual energy system with the base case economic model; performing
a simulation of the virtual energy system based on the calculated
size; generating a virtual energy system configuration based at
least in part on results of the simulation; and generating, based
on the virtual energy system, data for building a real-world
version of the virtual energy system.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. application Ser.
No. 17/099,176, filed Nov. 16, 2020, which is a continuation of
U.S. application Ser. No. 15/896,897, filed Feb. 14, 2018 and
issued as U.S. Pat. No. 10,839,436 on Nov. 17, 2020, which claims
priority to U.S. Application Ser. No. 62/459,277, filed on Feb. 15,
2017.
TECHNICAL FIELD
[0002] The subject matter of this application relates generally to
cloud computing applications.
BACKGROUND
[0003] Customer acquisition costs are extremely high for the solar
photovoltaics (PV) industry. That is, current methods and
technologies have failed to efficiently identify and target
customers, and new customer groups are not being sufficiently
enabled (e.g., community solar). Moreover, sales-people are not
effectively educating people about the opportunity or the
opportunity is not compelling enough, and this cumbersome and
confusing process is resulting in lost sales. For ubiquitous solar
to be achieved, new low cost methods of identifying, educating, and
selling to millions of customers will need to be developed for
residential, mid and large-scale solar installations, and customers
that range from individuals, to non-profits, to major
corporations.
[0004] For the solar PV industry, the cost of customer acquisition
continues to rise as the market moves beyond early adopters. The
cost and length of customer acquisition are increasing as fewer
early mover customers remain, and this challenge is limiting
growth. Existing technologies and methods to improve market
transparency and the consumer experience have been inadequate, and
aggressive marketing practices by the solar industry continue as
current methods are failing at both providing viable leads to
dealers and at empowering consumers with the tools they need to
make informed choices.
[0005] Existing solar PV marketing solutions and match-making
platforms rely on simple algorithms that can at best present very
generic system recommendations with wildly varying costs that only
serve to create more consumer confusion and skepticism. In fact,
current state-of-the-art platforms simply facilitate installer bids
for consumers to choose from. Such methods are not working.
[0006] Other popular solar PV system sizing solutions are geared
toward off-line studies for researchers and energy economics
experts, and offer no bill of materials (BOM) or detailed
engineering evaluation capabilities, and other applications while
providing greater accuracy in technical evaluation and costs, are
not coupled to local load or rate data to expedite user
evaluation.
[0007] Some of the challenge is that solar PV model, size and
configuration outputs depend on user inputs, and such inputs may be
unknown to the user, particularly if that person is a ratepayer
seeking to install solar. Attempts to mitigate this challenge by
current solar PV evaluation services have had poor results. That
is, the consumer solar PV sales experience needs to deliver the
same transparency today's PC, laptop, and car buying experience
offers consumers, and avoid the opaqueness of the bid facilitating
purchasing process, such as Expedia.TM., where customers have no
idea what the person next to them has paid for the same airline
seat.
[0008] Today's solar PV system customer acquisition methods
continue to offer minimal pricing transparency. This places the
solar PV developer in control of the discussion (and often the
decision) for system configuration design and sizing. Indeed, the
distance separating the ratepayer from the electric power utility
(or technology vendor) facilitates a space for solar PV developers
to push certain packages out of economic self-interest without
disclosing all options to the ratepayer that may have improved
performance or economics.
[0009] Requiring solar PV shoppers to rely on the very same
salespeople they distrust for information on such large purchase
decisions is an untenable situation if the solar PV industry is to
grow past early adopters toward ubiquity.
[0010] Consumers are seeking solutions to simplify the solar-buying
experience, and to achieve confidence in the prices they are quoted
by installers. The need to eliminate the hassles of the
solar-buying experience in the same manner TrueCar.TM. and Kelly
Blue Book.TM. have for the car buying experience is one of the key
innovations needed to achieve ubiquitous solar PV energy.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] Features, aspects, and embodiments are described in
conjunction with the attached drawings.
[0012] FIG. 1 is an illustration of an example Smart Solar
Configurator logic flow in accordance with an embodiment.
[0013] FIG. 2 is an illustration of example business logic, data
models, and optimization and simulation analytics informing the
configurator user interface described in FIG. 1, in accordance with
an embodiment.
[0014] FIG. 3 is an illustration of a flowchart describing an
example method for advertising messaging that is based on value
added collaboration between a solar PV system dealer or installer
(advertiser) and a solar PV system planner (buyer) in order to
create a new lead generation advertising model and quoting by
advertiser on system(s) configured by buyer in accordance with an
embodiment.
[0015] FIG. 4 is an illustration of a flowchart describing an
example method for advertising messaging that is based on value
added collaboration between a vendor (advertiser) and a solar PV
planner (buyer) in order to create a new "advice" model advertising
and direct marketing of incentives in accordance with an
embodiment.
[0016] FIG. 5 is a block diagram of example computer architecture
for implementing the features and processes described in reference
to FIGS. 1-4, according to an embodiment.
[0017] For a more complete understanding of the principles
disclosed herein, and the advantages thereof, reference is now made
to the following descriptions taken in conjunction with the
accompanying drawings.
DESCRIPTION
[0018] Systems, methods and non-transitory computer-readable
storage mediums are disclosed for cloud computing engineering,
virtual solar PV (SPV) or solar PV with storage (SPV/S) system
configuration, pricing, quoting, advertising messaging, sales lead
generation, and content marketing.
[0019] According to one aspect, a method to automatically configure
virtual SPV or SPV/S systems for residential and commercial
applications comprises: a time-series (e.g., 1 year at 1 minute
resolution) power flow circuit model and simulator, snap-shot
(single time-step) power flow circuit model and simulator, economic
optimization solver, physically-based economic optimization model,
business logic, interactive 2-dimensional (2D) or three-dimensional
(3D) product configurator and visualization, logic rules and
workflows, techno-economic data models, SPV/S technology vendor
catalog database, market tariffs and incentives database, property
electrical energy consumption data, and location atmospheric
data.
[0020] In some implementations, a method comprises: displaying, by
a computing device, a user interface for the user configuration,
pricing and quoting of a virtual SPV or SPV/S system for a computer
analysis of a virtual SPV or SPV/S; receiving, by the user
interface element, user selection of Objective Function,
Constraints, Location, Technologies, Costs, and Loads.
[0021] According to one aspect, the Objective Function can be
energy cost minimization such that: A) energy balance is preserved
(e.g. energy supply=energy demand), B) technologies operate within
physical boundaries (e.g. power output <=max output), and C)
financial constraints are verified (e.g. savings obtained by use of
the new virtual SPV or SPV/S must generate savings that repay
investments within the user defined maximum payback period).
[0022] According to another aspect, the Objective Function can be
Carbon Dioxide emission minimization such that: A) energy balance
is preserved (e.g. energy supply=energy demand), B) technologies
operate within physical boundaries (e.g. power output <=max
output), and C) financial constraints are verified (e.g. savings
obtained by use of the new virtual SPV or SPV/S must generate
Carbon Dioxide emission savings that repay investments within the
user defined maximum payback period).
[0023] According to one aspect, the Constraints can be financial
boundaries such as the user's desired maximum payback period or
investment time horizon.
[0024] According to another aspect, the Constraints can be physical
boundaries such as the maximum rated electrical current (ampere)
carrying capacity of cables, wires, transformers and other power
delivery equipment that make up the electrical circuit the virtual
SPV or SPV/S system will interconnect or integrate with.
[0025] According to another aspect, the Constraints can be
operating boundaries calculated by power flow simulation such as
energy losses and loading, or "hosting capacity" of existing
cables, wires, transformers and other power delivery equipment that
make up the electrical circuit the PVS/S system will interconnect
or integrate with.
[0026] According to another aspect, the Constraints can be
operating boundaries such as the allowable voltage drop at each
node in the electrical network the virtual SPV or SPV/S system in
two-dimensions or three-dimensions.
[0027] In some implementation, a method comprises: displaying, by a
computing device, a user interface for electronic creation,
configuration, simulation, optimization, management, pricing,
quoting and displaying of a virtual SPV or SPV/S system via
business logic, logic rules and workflows that help enhance
application engagement, automate the selection and configuration
process and minimize errors and illogical choices.
[0028] According to one aspect, the rules and workflows can be:
rules-based logic, constraint-based logic, or scenario-based
logic.
[0029] According to another aspect, a detailed bill of materials
(BOM), which can include array, lines, disconnects, solar inverter,
and racking styles is automatically generated for the configured
PVS system.
[0030] According to another aspect, draft one-line or three-line
electrical drawings are automatically generated based on the
configured virtual SPV or SPV/S system and installation
choices.
[0031] According to another aspect, a quasi-static time-series
power flow simulation model of the configured SPV/S system is
automatically generated.
[0032] According to another aspect, a static "snap-shot" power flow
simulation model of the configured PVS/S system is automatically
generated.
[0033] According to another aspect, a static "snap-shot" power flow
simulation of the configured PVS/S system is performed to obtain
power flow Constraints for physical and operational boundaries.
[0034] According to another aspect, time-varying or quasi-static
time-series power flow simulation of the configured virtual SPV or
SPV/S system is performed to obtain power flow Constraints for
physical and operational boundaries for one year at various time
step resolutions (e.g. every 15 minutes for 1 year or every 1 hour
for 1 year). For example, for an annual simulation at 1-hour
resolution, 8,760 time-steps are simulated and analyzed. The
time-varying atmospheric data model, which includes annual solar
irradiance and temperature data at certain time-steps (e.g. every
hour of every day for a year), along with the solar PV technology
performance, efficiency and power output ratings (Solar PV Panel DC
Output Rating in Kilowatts (kW), Solar PV system inverter rating in
Kilo-Volt-Amps (KVA), Solar PV Technology Power to Efficiency
Curve, Solar PV Technology Temperature to and Power Curve provide
the power flow simulation model for determining, via time-series
power flow analysis, the electrical power output for the size of
Solar PV technology being configured by the user.
[0035] According to another aspect, the optimization technique can
be based on simulation model and method with: pre-defined set of
rules with only one possible output per input. The objective is to
find the optimal combination of technology to supply of all energy
services required at the property under consideration, while
optimizing the energy flows to minimize costs and/or CO2 emissions.
The time-varying atmospheric data model, which includes annual
solar irradiance and temperature data at certain time-steps (e.g.
every hour of every day for a year), along with the solar PV
technology performance, efficiency and power output ratings (Solar
PV Panel DC Output Rating in Kilowatts (kW), Solar PV system
inverter rating in Kilo volt amps (KVA), Solar PV Technology Power
to Efficiency Curve, and Solar PV Technology Temperature to Power
Curve) provide the simulation model required for determining the
electrical power output for the size of solar PV technology being
configured by the user at their property location. That is, solar
panel temperature affects the power output potential of the solar
PV system. Cold temperatures generate the most power output, while
warmer temperatures produce less power output from solar PV
technology. Moreover, the lower the power output from the solar PV
panel, generally the less efficient it will operate.
[0036] This data model, along with the Objective Function,
Constraints data model, and Costs and Loads data model inform the
optimization engine which then calculates the most cost-optimal
size for the solar PV technology. This method provides rapid sizing
optimization, but is limited in scope to solar PV technology and is
unable to calculate storage system size and dispatch
accurately.
[0037] According to another aspect, the optimization technique can
be based on a physically-based economic optimization model and
Mixed Integer Linear Program (MILP) method. The objective is to
find the optimal combination of technology and operation schedule
(dispatch) to supply of all energy services required at the
property under consideration, while optimizing the energy flows to
minimize costs and/or CO2 emissions. The time-varying atmospheric
data model, which includes annual solar irradiance and temperature
data at certain time-steps (e.g. every hour of every day for a
year), along with the solar PV technology performance, efficiency
and power output ratings (Solar PV Panel DC Output Rating in
Kilowatts (kW), Solar PV system inverter rating in Kilo-Volt-Amps
(KVA), Solar PV Technology Power to Efficiency Curve, Solar PV
Technology Temperature to and Power Curve) inform the power flow
simulation model that is used to perform quasi-static time-series
power flow analysis and calculate the electrical power output for
the size of Solar PV technology being configured by the user. This
data model, along with the Objective Function, Constraints data
model, and Costs and Loads data model inform the MILP optimization
engine which then calculates the most cost-optimal size for the
solar PV with Storage technology selected.
[0038] Storage technologies can include lithium ion batteries, ice
storage systems, flow batteries and other energy storage systems.
If the user has selected SPV or SPV/S technology to configure, then
the optimization engine calculates the most cost-optimal size for
both solar PV and Storage, and also computes the operation logic
(dispatch) for the storage technology. That is, the optimal size of
solar PV and the optimal size of storage are calculated, along with
the annual charging and discharging schedule for the storage
system. The schedule to charge and discharge stored energy is
referred to as the dispatch curve which is in Per Unit format, with
1.0 indicating 100% discharging state and -1.0 indicating 100%
discharging state. This method provides high accuracy and requires
additional computation time by the server due to the complexity of
the problem space.
[0039] According to another aspect, a method for advertising
messaging and lead generation can comprise of: a cloud computing
Smart Solar Configurator that provides a user who is a buyer and a
user who is an advertiser access to quoting and sales
communications. The user who is a buyer can invite advertisers to
offer quotes on her configured virtue SPV or SPV/S system. The
buyer can also share configuration data, BOM, Costs, and Loads data
with the advertisers and use analysis and simulation features to
validate the benefits and value of any additions or modifications
the advertisers recommend.
[0040] According to another aspect, a method for advertising and
content marketing messaging and lead generation can comprise of: a
cloud computing Smart Solar Configurator application that provides
a user who is a buyer and a user who is a manufacturer access to
sales and advertising communication. The user who is a manufacturer
can offer targeted incentives to the buyer during the virtual SPV
or SPV/S configuration process to influence purchase decisions. The
buyer can also share configuration, BOM, Costs and Load data with
the manufacturer to get advice on options and technologies. The
manufacturer can communicate product differentiation and
demonstrate benefits collaboratively with the buyer.
[0041] In some implementations, a method comprises: providing, by a
server computer, an interactive Smart Solar Configurator, pricing
and quoting environment for selecting, analyzing and simulating a
virtual SPV or SPV/S system; providing, by the server computer, a
collaborative interface in the interactive configurator environment
for allowing users to share a configuration, the collaborative
interface configured to allow the users access, using client
devices in communication with the server device, a copy of a shared
configuration maintained by the server device, and to edit the
shared configuration; and providing, by the server computer, user
interface elements that are selectable by the users on their
respective client devices to perform an analysis or simulation of
the shared configuration and share the results of the analysis or
simulation in the collaborative interface.
Example Server Architecture
[0042] FIG. 5 is a block diagram of example computer architecture
for implementing the features and processes described in reference
to FIGS. 1-4, according to an embodiment. Other architectures are
possible, including architectures with more or fewer components. In
some implementations, architecture 500 includes one or more
processor(s) 502 (e.g., dual-core Intel.RTM. Xeon.RTM. Processors),
one or more network interface(s) 506, one or more storage device(s)
504 (e.g., hard disk, optical disk, flash memory) and one or more
computer-readable medium(s) 508 (e.g., hard disk, optical disk,
flash memory, etc.). These components can exchange communications
and data over one or more communication channel(s) 510 (e.g.,
buses), which can utilize various hardware and software for
facilitating the transfer of data and control signals between
components.
[0043] The term "computer-readable medium" refers to any medium
that participates in providing instructions to processor(s) 502 for
execution, including without limitation, non-volatile media (e.g.,
optical or magnetic disks), volatile media (e.g., memory) and
transmission media. Transmission media includes, without
limitation, coaxial cables, copper wire and fiber optics.
[0044] Computer-readable medium(s) 508 can further include
operating system instructions 512 (e.g., Mac OS.RTM. server,
Windows.RTM. NT server), network communication module instructions
514 and smart solar configurator instructions 516 for implementing
the features and process described in reference to FIGS. 1-4.
[0045] Operating system 512 can be multi-user, multiprocessing,
multitasking, multithreading, real time, etc. Operating system 512
performs basic tasks, including but not limited to: recognizing
input from and providing output to devices 502, 504, 506 and 508;
keeping track and managing files and directories on
computer-readable medium(s) 508 (e.g., memory or a storage device);
controlling peripheral devices; and managing traffic on the one or
more communication channel(s) 510. Network communications module
514 includes various components for establishing and maintaining
network connections (e.g., software for implementing communication
protocols, such as TCP/IP, HTTP, etc.).
[0046] Architecture 500 can be included in any computer device,
including one or more server computers in a local or distributed
network each having one or more processing cores. Architecture 500
can be implemented in a parallel processing or peer-to-peer
infrastructure or on a single device with one or more processors.
Software can include multiple software components or can be a
single body of code.
[0047] Particular implementations disclosed herein provide one or
more of the following advantages. A cloud computing Smart Solar
Configurator provides a key innovation toward addressing customer
acquisition costs for the solar industry by integrating
capabilities never before combined, and delivering them via an
engaging on-line experience that informs and creates consumer
excitement without complexity. The Smart Solar Configurator
leverages multiple existing data sources, coupled with SPV and
SPV/S economic optimization and sizing analytics (typically
inaccessible by non-power system engineering experts) to deliver a
first-of-a-kind "Smart Solar Configurator" that enables the general
public and solar shoppers from all backgrounds with the tools they
need to automatically determine the most optimal SPV or SPV/S
system size for their home or business, along with an interactive
configurator that gives them the freedom to explore, and choose
options and accessories that are compatible with the make, model
and size of system they wish to purchase.
[0048] Just as consumers can easily research, explore, and
configure options including accessories for cars, PCs, and laptops
by make and model, with a cloud computing Smart Solar Configurator
shoppers will, for the first time ever, have a similar product
decision tool, powered by advanced simulation and DER sizing and
optimization technologies, coupled with the information and pricing
transparency they have become conditioned to and expect from
durable consumer goods purchasing experiences.
[0049] Solar customers will be empowered with accurate upfront
system cost estimates for an optimally sized PV system that will
include a range of typical installation fees for the model and
options selected, and see how different options and features impact
their configured system pricing and return on investment time-line
in real-time as they explore and configure systems--all before
deciding to be contacted by an installer.
[0050] Solar installers and project developers operate in a highly
competitive market in which access to customers and informed solar
system pricing are essential to installer profitability. A cloud
computing Smart Solar Configurator will benefit installers and
dealers by attracting informed, in-market consumers in a
cost-effective and accountable manner that helps them sell more
solar systems profitably. Moreover, a cloud computing Smart Solar
Configurator can increase the trust between installers and solar
buyers, which will help dealers increase volume and reduce customer
acquisition costs.
[0051] Solar equipment manufacturers benefit from a cloud computing
Smart Solar Configurator by offering targeted incentives to
consumers, allowing manufacturers to focus their customer
acquisition efforts through a direct marketing channel. The ability
to deliver focused incentives enables manufacturers to reach
consumers that might otherwise purchase a solar system from a
competing manufacturer.
[0052] A cloud computing Smart Solar Configurator addresses
concerns for electrical utility distribution system planners with
determining the impact of residential and non-residential PV on the
macro-grid. This can include feeder hosting capacity to more
detailed deep circuit power flow studies. A cloud computing Smart
Solar Configurator delivers to utilities an open-source data
package that includes all the information necessary for system
planners to update their circuit models and achieve a more
efficient interconnection and permitting process.
[0053] The features described herein may be implemented in digital
electronic circuitry or in computer hardware, firmware, software,
or in combinations of them. The features may be implemented in a
computer program product tangibly embodied in an information
carrier, e.g., in a machine-readable storage device, for execution
by a programmable processor; and method steps may be performed by a
programmable processor executing a program of instructions to
perform functions of the described implementations by operating on
input data and generating output.
[0054] The described features may be implemented advantageously in
one or more computer programs that are executable on a programmable
system including at least one programmable processor coupled to
receive data and instructions from, and to transmit data and
instructions to, a data storage system, at least one input device,
and at least one output device. A computer program is a set of
instructions that may be used, directly or indirectly, in a
computer to perform a certain activity or bring about a certain
result. A computer program may be written in any form of
programming language (e.g., Objective-C, Java), including compiled
or interpreted languages, and it may be deployed in any form,
including as a stand-alone program or as a module, component,
subroutine, or other unit suitable for use in a computing
environment.
[0055] Suitable processors for the execution of a program of
instructions include, by way of example, both general and special
purpose microprocessors, and the sole processor or one of multiple
processors or cores, of any kind of computer. Generally, a
processor will receive instructions and data from a read-only
memory or a random-access memory or both. The essential elements of
a computer are a processor for executing instructions and one or
more memories for storing instructions and data. Generally, a
computer may communicate with mass storage devices for storing data
files. These mass storage devices may include magnetic disks, such
as internal hard disks and removable disks; magneto-optical disks;
and optical disks. Storage devices suitable for tangibly embodying
computer program instructions and data include all forms of
non-volatile memory, including by way of example, semiconductor
memory devices, such as EPROM, EEPROM, and flash memory devices;
magnetic disks such as internal hard disks and removable disks;
magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor
and the memory may be supplemented by, or incorporated in, ASICs
(application-specific integrated circuits). To provide for
interaction with a user the features may be implemented on a
computer having a display device such as a CRT (cathode ray tube),
LED (light emitting diode) or LCD (liquid crystal display) display
or monitor for displaying information to the author, a keyboard and
a pointing device, such as a mouse or a trackball by which the
author may provide input to the computer.
[0056] One or more features or steps of the disclosed embodiments
may be implemented using an Application Programming Interface
(API). An API may define on or more parameters that are passed
between a calling application and other software code (e.g., an
operating system, library routine, function) that provides a
service, that provides data, or that performs an operation or a
computation. The API may be implemented as one or more calls in
program code that send or receive one or more parameters through a
parameter list or other structure based on a call convention
defined in an API specification document. A parameter may be a
constant, a key, a data structure, an object, an object class, a
variable, a data type, a pointer, an array, a list, or another
call. API calls and parameters may be implemented in any
programming language. The programming language may define the
vocabulary and calling convention that a programmer will employ to
access functions supporting the API. In some implementations, an
API call may report to an application the capabilities of a device
running the application, such as input capability, output
capability, processing capability, power capability, communications
capability, etc.
[0057] A number of implementations have been described.
Nevertheless, it will be understood that various modifications may
be made. Elements of one or more implementations may be combined,
deleted, modified, or supplemented to form further implementations.
In yet another example, the logic flows depicted in the figures do
not require the particular order shown, or sequential order, to
achieve desirable results. In addition, other steps may be
provided, or steps may be eliminated, from the described flows, and
other components may be added to, or removed from, the described
systems. Accordingly, other implementations are within the scope of
the following claims.
* * * * *