system, method, computer program product, and configured system, method, and computer program produc

专利摘要:
Various embodiments are provided to facilitate the operation and control of a fleet of local energy assets and to optimize energy dispatch across the fleet, thereby facilitating the use of local energy assets rather than the consumption of energy supplied by the grid. An exemplary system may comprise a central platform and a plurality of local gate devices configured to perform local asset control. An exemplary method may include receiving a service availability call, performing fleet level optimization, generating a local level set of schedules, and causing, as a function of local level schedules, real-time local asset control. other embodiments provide for determining a location of each power consumer connected to the power grid, in which power consumption from the grid is reduced, determining a reduction amount of power consumption from the grid, and transmitting a signal to each corresponding port device. located at the specified location, the signal comprising indicative data for instructions for carrying out the on-site energy dispatch.
公开号:BR112019010630A2
申请号:R112019010630
申请日:2017-11-15
公开日:2019-10-01
发明作者:Noone Corey；Audrey Lee Ja-Chin；Knox Kate
申请人:Advanced Microgrid Solutions Inc；
IPC主号:

专利说明:

SYSTEM, METHOD, PRODUCT OF COMPUTER PROGRAM AND CONFIGURED SYSTEM, METHOD AND PRODUCT OF COMPUTER PROGRAM TO PERFORM TECHNOLOGY FROTACAMPLE LEVEL MANAGEMENT [0001] The embodiments of the present invention generally refer to the facilitation of the operation and control of a fleet of vehicles. local energy assets (for example, located at the customer) which may include energy storage systems, renewable fuels or diesel generators, gas turbines in particular for methods, devices and computer program products to optimize energy dispatch in the entire fleet to provide an energy provider (for example, a utility, a system operator or a retail energy provider) with firm capacity, for example, for the purpose of resource matching, other services or market products in nodes and to reduce electrical costs for end customers with these localized controllable assets on site.
STATE OF THE ART [0002] Conventional systems require operators and utilities of electricity transmission and distribution systems to build infrastructure to support peak demand, the costs of which are passed on to the customer, for example, through tariffs including response programs to demand, market-based prices and other time-based prices. While incentives can be offered to reduce demand during peak hours, customers are generally not in a position to do so through measures
Petition 870190069613, of 7/22/2019, p. 5/91
2/74 conventional load reduction and load shifting and, as such, tried to employ, for example, the use of local energy storage systems (eg batteries) or other energy assets. However, the customer bears the cost of having the local energy storage system installed, maintained and operated and, in addition, takes the risk that the cost savings do not justify the expenses. In addition, utilities generally have no control over the deployment and operation of energy storage systems deployed at the site and cannot rely on these resources, like other traditional generators, such as firm capacity products, for purposes of resource matching.
[0003] In this regard, areas were identified to improve known and existing systems. Through the applied effort, ingenuity and innovation, solutions to improve such systems have been realized and are described in connection with embodiments of the present invention.
BRIEF SUMMARY [0004] A computer program method, apparatus and product are therefore provided in accordance with an exemplary embodiment of the present invention for operating a local energy asset such as an on-site energy storage system to co-optimize the dispatch of energy or asset, thereby providing an energy provider (for example, a user, a system operator or a retail energy provider) with firm electrical capacity in specific locations and providing fare cost benefits to an end customer (for example, reducing your monthly energy bill). That
Petition 870190069613, of 7/22/2019, p. 6/91
3/74 system is suitable for various applications, including backup / emergency power, grid support behind the meter, peak cut to reduce demand costs and electrical cost of the day and as a basis for a micro-network.
[0005] In some embodiments, a system may be provided, the system comprising a platform apparatus and a local port apparatus, comprising at least one processor and at least one memory including the computer program code, at least one memory and the computer program code configured to, with the processor, make the device calculate the local load curves indicating the expected local load of a customer in each of several periods of a day as a function of one or more historical data meter and collection, taking into account other existing local generation resources, and market or climatic data, for each of one or more customers with local energy assets within a given portfolio aggregation, perform portfolio level optimization as a function of local load curves and tariff library, portfolio level optimization configured to segment local load curves according to tariff periods and other restrictions at the local level, and for each segment, calculate and issue a maximum energy consumption limit, generate a set of schedules at the local level, depending on the optimization at the portfolio level and a or more local restrictions, the set of timelines at the local level configured to be provided to a door appliance to facilitate the use of controllable resources on site instead of the electricity consumption supplied by the network, and the door appliance comprising at least one processor and at least one
Petition 870190069613, of 7/22/2019, p. 7/91
4/74 memory including computer program code, with at least one memory and computer program code configured to, with the processor, make the device receive the schedule locally from the platform device and store this schedule locally at a local level, at a starting time of a given segment, provide instructions to facilitate the control of local assets in real time or close to real time.
[0006] In some embodiments, local energy assets comprise energy storage resources and restrictions at the local level comprise instructions on charging and discharging the battery. In some embodiments, the computer program code configured to facilitate control of the local asset, which further comprises the computer program code configured to, with the processor, make the device during a segment in which the tariff or rate of the customer is less than a pre-defined limit and restrictions at the local level allow charging, make the local charge satisfied via consumption of electricity supplied by the network and allowing the battery to be charged as long as the expected charge on site do not meet the programmed maximum limit. In some embodiments, the computer program code configured to facilitate control of the local asset, also comprises that the computer program code is configured to, with the processor, make the device during a segment in which the tariff or rate customer is less than a pre-defined limit and the restrictions at the local level do not allow charging, it makes the predicted local charge to be satisfied through the electrical consumption provided by the network and that does not allow the charge of the
Petition 870190069613, of 7/22/2019, p. 8/91
5/74 battery. In some embodiments, the computer program code configured to facilitate the control of the local asset, also comprises that the computer program code configured, with the processor, makes the device during a tariff or customer fee segment is greater than a predefined limit and the local level restrictions do not allow charging, causes the predicted local charge to be satisfied through the electrical consumption provided by the grid up to a programmed maximum limit and causing any remaining portion of the predicted local charge to be satisfied by generating electricity from the local energy asset and preventing the battery from charging.
[0007] In some embodiments, the computer program code configured to facilitate the control of local assets, further comprises, that the computer program code configured, with the processor, makes the device prevent net export to the network caused by the generation of electricity from the energy asset, if such a local restriction exists on utility, interconnection or other regulations and requirements.
[0008] In some embodiments, the energy storage resources comprise battery systems. In some embodiments, the computer program code configured to facilitate the control of the local asset, also includes that the computer program code configured, with the processor, makes the device prevent net export to the network caused by the user of the local energy assets, if such local restriction exists on utility, interconnection or other regulations and requirements. In some embodiments, local energy assets are made up of
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6 / Ί ^ one or more of the renewable or non-renewable fuel generators or turbines.
[0009] In some embodiments, a method may be provided, the method comprising calculating local load curves indicating the customer's predicted local load in each of a plurality of day periods as a function of one or more historical data of the meter and collection, taking into account other existing local generation resources and market or climatic data, for each one or more customers with local energy assets within a given portfolio aggregation, performing optimization at the portfolio level depending on of the local load curves and a tariff library, the optimization at the portfolio level configured to segment the local load curves according to tariff periods and other restrictions at the local level, and for each segment, calculate and produce a maximum consumption limit of energy, generating a set of schedules at the local level, as a function of the optimization at the portfolio level and one or more In local restrictions, the local level schedule set to be provided for a door appliance to facilitate the use of controllable local assets instead of electricity consumption supplied to the grid, and to transmit the schedule at the local level to a door appliance , and causing local assets to be controlled in real time or near real time in a specific segment start time.
[0010] In some embodiments, local energy assets include energy storage resources and restrictions at the local level include instructions on charging and discharging the battery. In some embodiments, control of local assets
Petition 870190069613, of 7/22/2019, p. 10/91
7/74 also includes during a segment in which the tariff or customer fee is below a pre-defined limit and restrictions at the local level allow charging, making the predicted local charge to be satisfied through the consumption of electricity provided through the network and allowing the battery to charge as long as the predicted local charge does not meet the programmed maximum limit. In some embodiments, the control of the local asset also comprises during a segment in which the tariff or customer rate is below a pre-defined limit and the restrictions at the local level do not allow loading, making the expected local load to be satisfied through the consumption of electrical energy provided by the network and that does not allow the battery to charge. In some embodiments, the control of local assets also comprises during a segment in which the tariff or customer rate is greater than a pre-defined limit and the restrictions at the local level do not allow loading, making the expected local load to be satisfied through the consumption of electricity supplied from the grid up to a programmed maximum limit and making sure that any remaining portion of the predicted local charge is satisfied via electricity generation from the local energy asset and preventing battery charging. In some embodiments, the control of local assets also includes the impediment of net export to the grid caused by the generation of electricity from the energy asset, in case the local restriction exists from utility, interconnection, or other regulations and requirements.
[0011] In some achievements, the resources in storage power comprise systems of battery. In some achievements, the method can also understand The
Petition 870190069613, of 7/22/2019, p. 11/91
8/74 prevention of net export to the network caused by the user of local energy assets, if such local restriction exists of utility, interconnection, or other regulations and requirements. In some embodiments, local energy assets are made up of one or more of the renewable or non-renewable fuel generators or turbines.
[0012] In some embodiments, a computer program product may be provided comprising at least one non-transitory computer-readable storage medium containing instructions for computer executable program code, instructions for computer executable program code comprising instructions for program code to calculate local load curves indicating a customer's predicted local load in each of a plurality of one-day periods depending on one or more of the meter and billing historical data, considering other local generation resources and market or weather data, for each of the one or more customers with local energy assets within a given portfolio aggregation, performing portfolio level optimization as a function of local load curves and a tariff library, optimization at the portfolio level configured to segment the load curves lo lime according to tariff periods and other restrictions at the local level; for each segment, calculate and issue a maximum limit of energy consumption, generating a set of schedules at the local level, as a function of the optimization at the portfolio level and one or more local restrictions, the set of local level schedules configured to be provided for a door appliance to facilitate the use of controllable local assets instead of consumption
Petition 870190069613, of 7/22/2019, p. 12/91
9/74 of electricity supplied to the network, transmitting the schedule at a local level to a door device, and causing, at the start time of a given segment, the control of local assets in real time or close to real time.
[0013] In some embodiments, local energy assets comprise energy storage resources and restrictions at the local level comprise instructions on charging and discharging the battery. In some embodiments, the computer program code configured to facilitate the control of local assets, further comprises program code instructions for, during a segment in which the customer rate or rate is below a predefined limit and restrictions on local level allow charging, make sure that the predicted local charge is satisfied through the consumption of electricity provided by the network and allowing the battery to be charged as long as the predicted local charge does not meet the programmed maximum limit. In some embodiments, the computer program code configured to facilitate the control of local assets, also includes program code instructions for, during a segment in which the customer rate or rate is below a predefined limit and local restrictions do not. they allow charging, make the expected local charge be satisfied through the consumption of electrical energy provided by the network and do not allow the battery to charge. In some embodiments, the computer program code configured to facilitate the control of local assets also includes program code instructions for, during a tariff or customer fee segment, it is greater than a predefined limit and level restrictions do not allow loading, make the expected local load
Petition 870190069613, of 7/22/2019, p. 13/91
10/74 is satisfied through the consumption of electricity supplied to the grid up to a programmed maximum limit and to ensure that any remaining portion of the expected local charge is satisfied via electricity generation from the local energy asset and prevent battery charging. In some embodiments, the computer program code configured to facilitate the control of local assets also includes program code instructions to prevent net export to the network caused by the generation of electricity from the energy asset, if such a local restriction exists in utility , interconnection or other regulations and requirements. In some embodiments, the energy storage features comprise battery systems.
[0014] In some embodiments, the computer program code configured to facilitate the control of local assets also includes program code instructions for preventing net export to the network caused by the user of local energy assets, if such a local restriction utility, interconnection or other regulations and requirements exist. In some embodiments, local energy assets comprise one or more of renewable or non-renewable fuel generators or turbines.
[0015] In some embodiments, a system can be provided, the system configured to perform fleet level management to reduce the energy consumption provided by the network with a firm capacity reduction, the system comprising a platform device and a plurality of door appliances, the plurality of door appliances comprising at least one first door appliance located in a first location, the first location being in the
Petition 870190069613, of 7/22/2019, p. 14/91
11/74 location of a power consumer connected to the network and the second door appliance located at a second location, the second location being at a different location from the energy consumer connected to the network or at a different energy consumer connected to the network, each of the plurality of door devices configured to control a local energy asset, comprising at least one energy device asset, to control the use of local energy instead of the energy consumption supplied by the network, the platform appliance comprising at least at least one processor and at least one memory including computer program code, at least one memory and computer program code configured to, with the processor, make the device receive or access input data, determine, as a function of the input data, a location for each energy consumer connected to the network to reduce the energy consumption supplied by the network; determine a quantity of a reduction in energy consumption provided by the network and still allocate a total reduction through the systems of each energy consumer connected to the network; transmit a signal to each corresponding port device located at the given location, the signal comprising indicative data of instructions for carrying out energy dispatch at the location.
[0016] In some embodiments, the instructions are configured to replace a schedule at a local level previously provided and increase the use of the local asset. In some embodiments, at least one memory and the computer program code are additionally configured to, with the processor, cause the device to receive a utility request, the utility request comprising at least
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12/74 a geographic area or a set of substations and a period of time in which to reduce the consumption of energy supplied by the network and to perform optimization at the fleet level to determine which one or more of the plurality of door devices instruct to execute the dispatch of energy on site and at what times, thereby reducing the consumption of energy supplied in consideration of net export restrictions where applicable, and providing one or more schedules at the local level for each of a plurality of affected door appliances for facilitate the control of the use of local energy assets and the consumption of electricity supplied by the network. In some embodiments, fleet-level optimization comprises maximizing a sum of total invoice savings across all utility bills and revenue minus amortized development cost. In some embodiments, the optimization at the fleet level is a function of the amount of bill savings for each of the energy consumers connected to the grid. In some embodiments, fleet level optimization is a function of utility revenue, utility revenue being a function of an amount of energy dispatched on site. In some embodiments, optimization at the fleet level is a function of a development cost, the development cost being a function of one or more cost of the local energy storage system, installation cost, maintenance cost and operational cost.
[0017] In some embodiments, the method can be provided to perform fleet-level management to reduce the energy consumption provided by the network with a firm capacity reduction, the method comprising receiving or accessing
Petition 870190069613, of 7/22/2019, p. 16/91
13/74 input data from a plurality of door devices, the plurality of door devices comprising at least one first door device located in a first location, the first location being in the location of a power consumer connected to the network electrical and the second door appliance located at a second location, the second location being at a different location than the power consumer connected to the electrical network or at a different energy consumer connected to the electrical network, each of the plurality of door appliances configured to control a local energy asset comprising at least one energy device asset to control the use of local energy instead of the consumption of energy supplied by the network, determine, as a function of the input data, a location for each energy consumer connected to the grid to reduce the energy consumption provided by the network, determine a reduction amount of the energy consumption provided through the network and still allocate a total reduction through the systems of each energy consumer connected to the network, transmit a signal to each corresponding port device located in the determined location, the signal comprising indicative data of instructions for carrying out the energy dispatch in the location .
[0018] In some embodiments, the instructions are configured to replace a local level schedule previously provided and increase the use of the local asset. In some embodiments, the method also comprises receiving a utility request, the utility request comprising at least one geographic area or a set of substations and the time period to reduce the energy consumption supplied by the network and perform the optimization at the level of
Petition 870190069613, of 7/22/2019, p. 17/91
14/74 fleet to determine which one or more of the plurality of door devices instruct to execute energy dispatch on site and at what times, thereby reducing the consumption of energy supplied by the network in consideration of net export restrictions, where applicable , and provide one or more schedules at the local level for each of a plurality of affected door devices to facilitate control of the use of local energy assets and consumption of electricity supplied by the network.
[0019] In some embodiments, optimization at the fleet level comprises maximizing a sum of total invoice savings across all utility bills and revenue minus amortized development cost. In some embodiments, the optimization at the fleet level is a function of the amount of bill savings for each of the energy consumers connected to the grid. In some embodiments, fleet level optimization is a function of utility revenue, utility revenue being a function of an amount of energy dispatched on site. In some embodiments, fleet level optimization is a function of a development cost, the development cost being a function of one or more of the cost of the local energy storage system, installation cost, maintenance cost and operational cost .
[0020] In some embodiments, a computer program product may be provided to perform fleet-level management to reduce the power consumption supplied by the network with a firm capacity reduction, the computer program product comprising at least one storage medium
Petition 870190069613, of 7/22/2019, p. 18/91
15/74 per readable non-transitory computer having program code instructions stored, computer executable program code instructions comprising program code instructions for receiving or accessing input data from a plurality of door devices, plurality of door appliances comprising at least one first door appliance located in a first location, the first location being in the location of a power consumer connected to the network and the second door appliance located in a second location, the second location being in a different location of the grid-connected power consumer or a different grid-connected power consumer, each of the plurality of gate devices configured to control a local power asset comprising at least one power device asset to control usage of local energy instead of the energy consumption supplied by the grid, determine, as a function of the input data, a location for each of the energy consumers connected to the power grid to reduce the energy consumption supplied by the network, determine an amount of a reduction in the energy consumption provided by the network, and still allocate a total reduction through of the systems of each energy consumer connected to the network, transmit a signal to each corresponding port device located at the given location, the signal comprising data indicative of instructions for carrying out energy dispatch at the location.
[0021] In some embodiments, the instructions are configured to replace a previously provided local level schedule and increase the use of the local asset. In some embodiments, executable program code instructions
Petition 870190069613, of 7/22/2019, p. 19/91
16/74 per computer additionally comprise program code instructions for receiving a utility request, the utility request comprising at least one geographic area or a set of substations and the time period within which to reduce the energy consumption supplied by the network, and perform fleet level optimization to determine which one or more of the plurality of door devices instruct to execute energy dispatch on site and at what times, thus reducing the energy consumption supplied by the network in consideration of net export restrictions , where applicable, and provide one or more schedules at the local level for each of a plurality of affected door appliances to facilitate control of the use of local energy assets and consumption of electricity supplied to the grid.
[0022] In some embodiments, optimization at the fleet level comprises maximizing the sum of total invoice savings across all accounts and utility revenue less amortized development cost. In some embodiments, the optimization at the fleet level is a function of the amount of bill savings for each of the energy consumers connected to the grid. In some embodiments, fleet level optimization is a function of utility revenue, utility revenue being a function of an amount of energy dispatched on site. In some embodiments, optimization at the fleet level is a function of a development cost, the development cost being a function of one or more costs of the local energy storage system, installation cost, maintenance cost and operational cost.
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17/74
BRIEF DESCRIPTION OF THE DRAWINGS [0023] Having thus described the embodiments of the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and in which:
[0024] Figure 1 is a block diagram of a system that can be configured specifically in accordance with an example embodiment of the present invention;
[0025] Figure 2 is a block diagram showing an exemplary embodiment of the operating platform that can be specifically configured in accordance with an example embodiment of the present invention;
[0026] Figure 3 is a block diagram showing an exemplary local level diagram that can be specifically configured according to an example embodiment of the present invention;
[0027] Figure 4 is a block diagram of an apparatus that can be specifically configured in accordance with an example embodiment of the present invention;
[0028] Figure 5 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention;
[0029] Figure 6 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention;
[0030] Figure 7 illustrates an exemplary schedule at the local level that can be generated according to an example embodiment of the present invention;
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18/74 [0031] Figure 8 illustrates an exemplary segmented local level load curve that can be used according to an example embodiment of the present invention;
[0032] Figure 9 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention;
[0033] Figure 10 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention;
[0034] Figure 11 is a data flow diagram showing an exemplary data flow according to an embodiment of the present invention and [0035] Figure 12 is a block diagram of a system that can be specifically configured according to an example embodiment of the present invention.
DETAILED DESCRIPTION [0036] Some example embodiments will now be more fully described below with reference to the accompanying drawings, in which some, but not all, embodiments are shown. In fact, example embodiments can take many different forms and should not be construed as limited to the embodiments presented here; instead, these embodiments are provided so that such disclosure meets applicable legal requirements. Similar reference numbers refer to similar elements throughout the text. The terms data, content, information and similar terms can be used interchangeably, according to some example embodiments,
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19/74 to refer to data capable of being transmitted, received, operated and / or stored. In addition, the term exemplary, as used here, is not provided to convey any qualitative assessment, but only to convey an illustration of an example. Therefore, the use of any of these terms should not
be taken to limit the spirit and O scope of achievements of the present invention.[0037] 0 term assets power or active controllable, such as used here, you can refer The one or more systems
energy storage (ie, lithium-ion battery systems) or any other energy sources such as diesel generators, gas turbines, etc. The term firm capacity can refer to the amount of energy available for production or transmission that can be guaranteed to be available at any given time. The term power provider, as used herein, can refer to a user, a system operator, a retail power provider or the like.
Global View [0038] Embodiments of the present invention generally related to a system to co-optimize battery dispatch through a fleet of energy storage units behind the meter (1) to provide a power provider with firm capacity in nodules of specific markets and (2) minimizing electrical costs to the end customer (for example, reducing their monthly energy bill). The system can be configured to provide operations behind the meter at a hosting location (that is, on site or at the client), communicate with the power provider and use controllable assets such as,
Petition 870190069613, of 7/22/2019, p. 23/91
20/74 eg energy storage systems provided by third parties (eg controller / inverter / site batteries). The system can be configured to provide pre-sales analytical services and / or operational service, each using the same software infrastructure, described below, as well as individually configured models that perform co-optimization calculations for the entire fleet.
[0039] The platform can be configured to coordinate the dispatch of aggregate local capacity to a power distribution and supply system, as well as providing operations behind the meter at one or more customer locations, for example, using controllable assets as a hardware of energy storage system provided by third parties in the customer's home facilities. The operational platform can be configured to implement reduced demand collection and more general tariff optimization for the customer's housing facilities, as well as the dispatch of aggregate local capacity for the energy supply and distribution system.
[0040] The operational platform can be configured for communication with the energy provider to receive event signals and send telemetry data, communication with distributed controllable assets (for example, energy storage systems), optimization of energy dispatch in response to event signals received from the energy provider, and optimization of energy dispatch to reduce energy costs for the customer, one aspect is Demand Load Reduction (DCR).
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21/74
System Architecture [0041] Figure 1, shown below, is a high level diagram showing the hardware infrastructure and data flow between the electrical utility 100, several third party repositories 200, and the AMS system, which comprises a platform operations 300 as well as 400A-400N port devices and a 500A-500N energy storage system which, as shown in Figure 2, comprises a local controller, an inverter, a DC combiner panel and batteries in each location.
[0042] Operating platform 300 can be configured to communicate with each of a plurality of 400A-400N port devices, each located at a host client site in conjunction with a 500A500N energy storage system, the power provider 100, third-party resources that can provide useful / necessary data (ie, third-party repositories 200) and various types of users. Operational platform 300 can be configured to use, for example, historical meter and billing data, a library of tariffs and market / weather data to perform forecasting and optimization at the site and portfolio level and generate schedules at the local level that are provided to the door devices in place. Telemetry data can be received from local port devices, aggregated and transmitted to the utility. Figure 2 shows the platform device in more detail.
[0043] The door device is located at the customer's location. The door device can be configured to receive schedule data at the local level from the operating platform 300 and implement a power dispatch plan according to
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22/74 schedule data instructing local controller 500A to implement power dispatch in real time or near real time.
[0044] The 500A controllable asset system, which can be incorporated as an energy storage system, can comprise, for example, a local controller, an inverter, a DC combination panel and a battery. The local controller can be configured to receive, in real time or near real time, instructions regarding the dispatch of the battery and instruct the inverter to reduce or increase the battery charge or discharge accordingly. In other embodiments, the controllable assets can be diesel generators or the like, the controllable asset system 500A can comprise, for example, the diesel generator instead of the battery.
[0045] Figure 2 is a block diagram showing an exemplary embodiment of the operating platform that can be specifically configured in accordance with an example embodiment of the present invention. The platform device can comprise and / or be configured to leverage or otherwise leverage one or more of the following components to perform optimization and other analysis in an operational and pre-sales context: a tariff library and billing mechanism 212, a mechanism for collecting historical customer data and repository 216; load forecasting mechanism 218; collection of electricity market price data and repository 222; dispatch forecasting mechanism 220; customer model (representation of customer data on the operating platform, for example, service account number, meter number, substation, etc.) 226; (7) contract library (for example,
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23/74 host client contract rules, utilities contract rules) 228; and (8) 224 co-optimization model.
[0046] The 224 portfolio co-optimization model can be configured to optimize (1) utility, system operator or market-based dispatch and (2) savings on customer invoices, for example, to maximize or increase revenue. This co-optimization model can be modified to operate in each of a plurality of operating modes in different contexts: (1) portfolio optimization in an operational context that can be configured to generate optimized dispatch instructions for multiple battery units, based on a scenario analysis of a near period (for example, the next hour), considering whether or not a power system likely requires energy dispatch in a steady load drop response. (2) portfolio optimization in a deterministic context of pre-sales analysis that can be configured to analyze a set of several local customers and their respective load profiles and local restrictions to determine whether the project economy will allow any controllable asset, such as , for example, a battery system, to be located in a specific location of the customer and, also, the ideal size of the battery system for each location, or (3) to execute in operations or in pre-sales with a portfolio of one single location, to provide pre-sales analysis of an individual customer load profile or in operations, generate schedule only for that individual location. In some embodiments, this model can be configured to perform co-optimization through a plurality of locations, much like the portfolio optimization section described below. In some embodiments, this model can be
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24/74 executed on a periodic basis (for example, daily, hourly or similar), and can send DCR schedules to the controllable asset systems each time it executes and it can also receive external signals for the dispatch of the entire fleet of firm capacity and allocate that dispatch signal optimally across a fleet of controllable asset systems, in light of other DCR activities at those locations and available fall load at each location if the export of electricity to the grid is not allowed, in order to meet the request for aggregate dispatch, considering restrictions at the local level.
[0047] The operating platform 300 can be based on the cloud (for example, hosted on a virtual cloud-based server).
Operating platform 300 can facilitate communications, as shown in the diagram below. To communicate with the distributed fleet, the operational platform 300 can use REST API methods or distributed queuing system (for example, publish / subscribe method) that the door devices can invoke at regular intervals (for example, 1 minute), protected for the security of the transport layer of mutual authentication mode (for example, TLS).
Infrastructure at the local level [0048] Figure 3 is a block diagram showing an exemplary local level diagram that can be specifically configured according to an example embodiment of the present invention. For example, where the customer has local generation, the system supplies meters at the local level (S), at the level of renewable energy generation (G) and at the battery inverter (B), so that S = L - G - B (that is, the local load (S) is equal to
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25/74 total site load (L) minus the renewable energy generated (G) minus the battery power (B), where load (L) is a calculated value. The system can control battery usage so that battery power is never exported. This is done by ensuring that B <L (that is, the energy provided by the battery is always less than the load at the total location). Note that energy from local generation can be exported and, as such, when S is negative and L is zero, B is zero.
Apparatus [0049] Regardless of the type of device incorporating any of the 400A-400Nv port devices or platform device 300, any of the 400A400N port devices or platform device 300 can include or be associated with an apparatus 400 as shown in FIGURE 4. In this regard, the apparatus may include or be in communication with a processor 402, a memory device 404, a communication interface 406 and a user interface 408. As such, in some embodiments, although devices or elements are shown as being in communication with each other, hereinafter referred to devices or elements should be considered as capable of being incorporated in the same device or element and, therefore, devices or elements shown in communication should be understood alternatively as parts of the same device or element.
[0050] In some embodiments, processor 402 (and / or coprocessors or any other processing circuit assisting or otherwise associated with the processor) may be in communication with the 404 memory device via a
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2.6 / Ί4.
bus to pass information between device components. The memory device may include, for example, one or more volatile and / or non-volatile memories. In other words, for example, the memory device can be an electronic storage device (for example, a computer-readable storage medium) comprising ports configured to store data (for example, bits) that can be retrieved by a machine ( for example, a computing device such as the processor). The memory device can be configured to store information, data, content, applications, instructions or the like to allow the apparatus 400 to perform various functions in accordance with an example embodiment of the present invention. For example, the memory device can be configured to buffer input data for processing by the processor. Additionally or alternatively, the memory device can be configured to store instructions for execution by the processor.
[0051] As noted above, apparatus 400 may be made by any of the 400A-400Nv port devices or platform device 300 configured to employ an example embodiment of the present invention. However, in some embodiments, the device may be incorporated as a chip or chip set. In other words, the apparatus may comprise one or more physical packages (for example, chips) including materials, components and / or cables in a structural assembly (for example, a base plate). The structural assembly can provide physical strength, conservation of size and / or limitation of electrical interaction for component circuits included in it. The device can therefore, in some cases, be
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27/74 configured to implement an embodiment of the present invention on a single chip or as a single system on a chip. As such, in some cases, a chip or chip set may be a means of performing one or more operations to provide the functionality described here.
[0052] Processor 402 can be realized in several different ways. For example, the processor can be incorporated as one or more of several hardware processing means such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing element with or without an accompanying DSP or various other processing circuits, including integrated circuits such as, for example, an ASIC (application specific integrated circuit), an FPGA (field programmable door command), a micro controller (MCU), a hardware accelerator, a special purpose computer chip or the like. As such, in some embodiments, the processor may include one or more processing cores configured to function independently. A multi-core processor can enable multi-processing within a single physical package. Additionally or alternatively, the processor may include one or more processors configured together across the bus to allow independent instruction execution, instruction segmentation and / or multithreading.
[0053] In an example embodiment, processor 402 may be configured to execute instructions stored on memory device 404 or otherwise accessible to the processor. Alternatively or additionally, the processor can be configured to perform functionality
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28/74 coded. As such, whether configured by hardware or software methods, or by a combination thereof, the processor may represent an entity (for example, physically incorporated into circuits) capable of performing operations in accordance with an embodiment of the present invention while configured accordingly. . Thus, for example, when the processor is incorporated as an ASIC, FPGA or similar, the processor may be hardware specifically configured to conduct the operations described here. Alternatively, as another example, when the processor is realized as an executor of software instructions, the instructions can specifically configure the processor to execute the algorithms and / or operations described here when the instructions are executed. However, in some cases, the processor may be a processor of a specific device configured to employ an embodiment of the present invention by further configuring the processor by instructions to perform the algorithms and / or operations described herein. The processor may include, among other things, a clock, an arithmetic logic unit (ALU) and logic gates configured to support the operation of the processor. In one embodiment, the processor may also include a user interface circuit configured to control at least some functions of one or more elements of user interface 408.
[0054] However, the communication interface 406 can be any means, such as a device or circuit embedded in hardware or a combination of hardware and software that is configured to receive and / or transmit data between any of the 600 user devices, 400A port devices
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400N, platform device 300, third party repositories 200 or utility 100. In this regard, communication interface 406 may include, for example, an antenna (or multiple antennas) and supporting hardware and / or software to enable wireless communication . Additionally or alternatively, the communication interface may include the circuit to interact with the antennas to cause the transmission of signals through the antennas or to handle the reception of signals received through the antennas. For example, the communication interface can be configured to communicate wirelessly, such as via wi-fi, bluetooth or other wireless communication techniques. In some cases, the communication interface may alternatively or also support wired communication. As such, for example, the communication interface may include a communication modem and / or other hardware / software to support communication via cable, digital subscriber line (DSL), universal serial bus (USB) or other mechanisms. For example, the communication interface can be configured to communicate via wired communication with other components of the computing device.
[0055] User interface 408 may be in communication with processor 402, such as the user interface circuit, to receive an indication of a user input and / or to provide an audible, visual, mechanical or other output for a user. As such, the user interface may include, for example, a keyboard, a mouse, a joystick, a monitor, a touchscreen, a microphone, a speaker and / or other input / output mechanisms. In some embodiments, a display may refer to the display on a screen, on a wall,
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30/74 in glasses (eg close-up view), in the air, etc. The user interface can also be in communication with the memory 404 and / or the communication interface 406, such as via a bus.
Pre-sales analysis of locations [0056] The system can be configured to apply a portfolio optimization model to determine battery configuration in a plurality of locations based on electrical usage profiles at the location, under the terms of the contract and in applicable tariffs for each location under consideration. That is, a given location will have a specific profile for electrical use (from which a load curve can be predicted), a specific contract under which the customer is involved with one or more energy providers and specific tariff rates or other structures costs provided by energy providers. The system can be configured to determine the battery configuration (for example, size and / or type) and available cost and revenue savings. This process can also be used to inform proposals for public service contracts.
[0057] In a pre-sales context, the portfolio optimization model can be configured to be executed with a portfolio from a single location, to determine the ideal size of the system for a given location, considering the profile of electrical use in local level contract terms and tariffs applicable to that location.
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General operation [0058] The operational platform provides, for example, monthly a load curve at the local level and generates a schedule identifying a load plan at the local level, the load plan at the local level indicating energy dispatch instructions that optimize the use of the battery to maximize the capacity or delivery of another product to the energy provider and to minimize the customer's energy costs based on the customer's relevant tariffs (for example, time demand charges and energy charges). Each schedule optimized at the local level can be generated according to the expected load curve, with the specific contract of the utility provider and the applicable tariff data for the location. A local level schedule is provided to a gate device and the gate device provides real-time or near real-time instructions to the third-party local controller, which controls the inverter and DC combiner panel.
Restrictions at the local level [0059] In each context in which the system is being used (for example, analysis or pre-sales operations), the system can be configured to operate optimally for each location according to various local restrictions, as a no-charge period (ie battery charging is prohibited during a certain window) and a no-export rule (ie battery power cannot be exported).
[0060] When a customer has no local generation, the system can be configured to reduce battery usage measured, for example, by a meter on the inverter, as the local meter is
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32/74 approaches 0 kW. As such, battery power is never exported. When the customer has local generation, the system supplies meters at the local level, at the level of renewable energy generation and in the inverter (B), such that S = L - G - B (that is, the local load (S) is equal at the total site load (L) minus the renewable energy generated (G) minus the battery power (B), where load (L) is a calculated value. The system can control the battery usage so that the battery power never be exported if this is a constraint. This is done by guaranteeing B <L (ie the energy supplied by the battery is always less than the total site load). Note that the energy from the local generation can be exported and, as , when S is negative and L is zero, B is 0. Figure 3 shows this embodiment.
Multi-site Portfolio Operation Model [0061] The system can be configured in such a way that each cloud-based platform and the local port device are configured to receive signals from the power provider requesting energy dispatch. When dispatched by the energy provider through the cloud-based platform, the platform can determine, through optimization, how to dispatch controllable assets within the portfolio of available locations or customer contracts (which may comprise a plurality of locations). The system can determine a better fit by determining a load quantity and a site selection to instruct a discrete dispatch event, so that one or more local port devices will be instructed to override the schedule at the local level and increase usage of the battery, further reducing electricity consumption
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33/74 supplied by the network and reducing the total distribution load of the power provider. In addition, these dispatch signals for each local energy storage unit will take into account local tariff considerations and restrictions, so that the energy storage control will update the planned charging limits and parameters in light of the energy capacity battery expected after the dispatch event. When power is dispatched by the power provider through the door device, the logic in the device ensures that the dispatch instructions are compatible with (and secondary to) the platform-based dispatch instructions.
[0062] The system can be configured to perform portfolio optimization, which comprises identifying the best locations to obtain the highest possible performance score for each dispatch signal of utility with the battery and charging resources that the system has available in its portfolio.
[0063] It should be noted that the optimization model is generic in nature and may be able to handle multi-site portfolio optimization, while accommodating any combination of market assets and products (eg wholesale markets), as well as programs utilities. Thus, the approach is capable of providing stacked services for the distribution and transmission networks, resulting in multiple and simultaneous revenue streams. By co-optimizing a portfolio of flexible loads, storage and distributed generation assets to provide these network services, the AMS approach provides an economically sustainable business model that will facilitate the integration of renewable generation and storage assets,
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34/74 resulting in greenhouse gas emissions improved by energy quality and resilience.
Processes [0064] In an example embodiment of the present invention, a computer program system, apparatus or product can be provided to implement or execute a method, process or algorithm to generate and subsequently provide a schedule at the local level for a monitoring device. door to facilitate control of the use of local energy assets and consumption of electricity provided by the network.
[0065] In exemplary embodiments, the system, comprising the operating platform and the door device, can be configured to use, for example, historical meter and billing data, a tariff library and market / weather data to run at level and, in some embodiments, optimization at the portfolio level and subsequently generate schedules at the local level. Local level schedules can then be provided to door devices to drive battery usage at a local level versus power consumption from the grid. The door device can be configured to receive the schedule at the local level from the operating platform and implement a load reduction plan according to the schedule data by instructing the local controller to implement battery dispatch in real time or almost In real time. Figure 5 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention.
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35/74 [0066] As shown in block 505 of Figure 5, an apparatus, such as apparatus 20 incorporated by operating platform 300 and / or apparatus 400, can be configured to determine or otherwise calculate a local load curve. The apparatus incorporated by the operating platform 300 and / or apparatus 400 may therefore include means, such as processor 402, communication interface 406 or the like, to calculate a local load curve, for example, for each or more customers with energy assets within a given portfolio aggregation (for example, market node or other aggregation). The local load curve can be indicative of an expected local load of, for example, a host customer, in each of a plurality of periods of one day. In some embodiments, the local load curve can be determined as a function of and / or taking into account other existing local generation resources (for example, generators of solar energy, wind, fuel cells, combustion). The determination or calculation of the local load curve can be done based on one or more historical data of the meter, historical data of collection and / or market / climatic data. In some embodiments, a predefined confidence interval can dictate the DCR limits. Additionally or alternatively, calculations related to the probability of the event may result in the recalculation of the ideal DCR limits.
[0067] As shown in block 510 of Figure 5, a device, such as the device 20 incorporated by the operating platform 300 and / or device 400, can be configured to carry out portfolio level optimization. The device incorporated by the operating platform 300 and / or device 400 can therefore
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36/74 therefore, include means, such as processor 402, communication interface 406 or the like, to perform portfolio level optimization. The performance of the optimization at the portfolio level can be done according to the local load curve and data of the time of use type (for example, a tariff library). In some embodiments, portfolio level optimization can be done as a function of local load curves and a tariff library, portfolio level optimization is configured to segment local load curves according to tariff periods and others local level restrictions on battery charging and discharging, and for each segment, calculate and produce a maximum limit on energy consumption. In particular, the optimization process at the portfolio level may include the segmentation of the local load curve according to the tariff periods and, for each segment, the calculation and generation of the maximum limit of energy consumption. For example, Figure 8 shows a graph that illustrates the segmentation of the local load curve and the limits of the associated DCR voltages.
[0068] As shown in block 515 of Figure 5, an apparatus, such as apparatus 20 incorporated by operational platform 300 and / or apparatus 400, can be configured to generate a set of schedules at the local level. The apparatus incorporated by the operational platform 300 and / or apparatus 400 may, therefore, include means, such as processor 402, communication interface 406 or similar, to provide a set of schedules at the local level for a door apparatus to facilitate the control of the use of the local energy asset and the consumption of electricity.
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37/74 [0069] Once generated, the schedule at the local level can be configured to be delivered to a door device. Figure 7 illustrates an exemplary local-level schedule that can be generated according to an example embodiment of the present invention.
[0070] As shown in block 520 of Figure 5, an apparatus, such as apparatus 20 incorporated by operational platform 300 and / or apparatus 400, can be configured to provide the schedule at the local level. The apparatus incorporated by the operational platform 300 and / or apparatus 400 may, therefore, include means, such as processor 402, communication interface 406, or the like, to provide the schedule at the local level to a door apparatus to facilitate the control of the use of local energy assets and consumption of energy supplied by the network.
[0071] In an example of an embodiment of the present invention, a computer program system, apparatus or product can be provided to implement or execute a method, process or algorithm to facilitate control of the use of local assets and consumption of energy provided by network.
[0072] In an exemplary embodiment, the system, comprising the operational platform and the door device, can be configured to use schedule data at the local level and implement a load cut plan according to schedule data at the level instructing the local controller to implement battery dispatch in real time or near real time. Figure 6 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention.
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38/74 [0073] As shown in block 605 of Figure 6, an apparatus, such as an apparatus 20 incorporated by the input apparatus 400A- 400N 300 and / or apparatus 400, can be configured to probe the operating platform for receiving or otherwise access the schedule at the local level. The apparatus incorporated by the port apparatus 400A-400N 300 and / or apparatus 400 may therefore include means, such as processor 402, communication interface 406 or the like, for searching, receiving or accessing the schedule at the local level.
[0074] As shown in block 610 of FIGURE 6, an apparatus, such as an apparatus 20 incorporated by the input apparatus 400A-400N 300 and / or apparatus 400, can be configured to provide instructions that facilitate in real time or near real time almost real control of local energy assets. The apparatus incorporated by the port apparatus 400A-400N 300 and / or apparatus 400 may therefore include means, such as processor 402, communication interface 406 or the like, to provide instructions that facilitate in real time or near real time control of local energy assets. Exemplary instructions are provided below, which show various values for each of a plurality of categories. For example, the door device can record in the battery logs for the next event, a function and / or condition or command mode, Maximum Target Power, Minimum Target Power, Target Charge State, Maximum Charge Power and Maximum Power Discharge.
[0075] {min_site_power_w: 0.0, dispatch level: 0.0, schedu1e_detai1s_i d: 511, max__charge_power__w: 250000.0,
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39/74 max__si te_power__w: 4130 0 0.0, soe_target_wh: 1650000.0, event start time: 2016-03-07108: 00: 00 + 00: 00, max discharge power w: 250000.0, fk_schedule_id: 9} [0076] The model is configured to consider any combination of arbitrary costs and maximize revenue through them. For example, during a segment in which the tariff or customer rate reflects the lowest costs is below a pre-defined or similar threshold (for example, in an off-peak period) and restrictions at the local level allow for charging, as shown in block 615 of Figure 6, an apparatus, such as an apparatus 20 incorporated by the input apparatus 400A-400 N 300 and / or apparatus 400, can be configured to cause the expected load to be satisfied by consuming the energy supplied over the network and allow charging of the local energy storage system (for example, a battery) insofar as the expected local charge does not meet or exceed the limit. The apparatus incorporated by the port apparatus 400A-400N 300 and / or apparatus 400 may, therefore, include means, such as processor 402, communication interface 406 or the like, to ensure that the expected local load is satisfied through consumption of the energy supplied by the network and allow the battery to charge as long as the expected local charge does not reach the limit.
[0077] During a segment, a customer's electricity consumption is below a pre-defined limit and restrictions at the local level do not allow charging, as shown in block 620 of Figure 6, an appliance, such as an appliance 20 incorporated by the 400A- 400N 300 door appliance and / or appliance
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400, can be configured to ensure that the expected local load is satisfied by consuming the energy supplied by the network and to prevent loading of the local energy storage system. The apparatus incorporated by the port apparatus 400A-400N 300 and / or apparatus 400 may therefore include means, such as processor 402, communication interface 406 or the like, to ensure that the expected local load is satisfied through consumption of energy supplied by the network and prevent loading of the local energy storage system.
[0078] During a segment, a customer's electrical consumption is greater than a pre-defined limit and restrictions at the local level do not allow charging, as shown in block 625 of Figure 6, an appliance, such as an appliance 20 incorporated by the input device 400A-400N 300 and / or device 400, it can be configured to cause the predicted local load to be satisfied through consumption of electricity supplied from the grid up to an associated DCR limit and to make any remaining portion of the expected local charge is satisfied via local energy assets and prevent battery charging. The apparatus incorporated by the port apparatus 400A-400N 300 and / or apparatus 400 may therefore include means, such as processor 402, communication interface 406 or the like, to ensure that the expected local load is satisfied through consumption power supplied by the grid up to an associated DCR limit and ensure that any remaining portion of the expected local charge is satisfied through local energy assets and prevent battery charging.
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41/74 [0079] During a segment in which a rate is within a predefined range (for example, above a first limit and, for example, below a second limit, ie, intermediate peak) and restrictions at a local level they allow charging (for example, the no-load rule is not in effect), as shown in block 630 of FIGURE 6, an apparatus, such as an apparatus 20 incorporated by the input apparatus 400 A- 400 N 300 and / or device 400, can be configured to ensure that the predicted local load is satisfied through the consumption of electrical energy supplied by the network up to the associated DCR limit and allow the charging of the local energy storage system as the predicted local load does not reach the limit. The apparatus incorporated by the port apparatus 400A-400N 300 and / or apparatus 400 may therefore include means, such as processor 402, communication interface 406 or the like, to ensure that the expected local load is satisfied through consumption of electricity supplied by the grid up to the associated DCR limit and allow the charging of the local energy storage system to the point where the predicted local load does not reach the limit.
[0080] During a segment in which a rate is within a pre-defined range (for example, above a first limit and, for example, below a second limit, ie, intermediate peak) and level restrictions do not allow charging (for example, no-load rule is in effect), as shown in block 635 of Figure 6, an apparatus, such as an apparatus 20 incorporated by the input apparatus 400A-400N 300 and / or apparatus 400, may be configured to ensure that the expected local load is satisfied through consumption of
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42/74 electricity supplied by the grid up to the associated DCR limit, to ensure that any remaining portion of the expected local load is satisfied through local energy assets and to prevent the loading of the local energy storage system. The apparatus incorporated by the port apparatus 400A-400N 300 and / or apparatus 400 may therefore include means, such as processor 402, communication interface 406 or the like, to cause the expected local load to cause the expected local load is satisfied through the consumption of electricity supplied by the grid up to the associated DCR limit, making any remaining portion of the forecasted local load satisfied by the local energy assets and preventing the loading of the energy storage system.
Single location operation model where a customer does not have authorized local generation to export [0081] A single location operation model in which the AMS system is configured to operate each location optimally according to restrictions that include a no-show period charging (ie battery charging is prohibited during a specific window) and non-export rule (ie, energy from energy assets cannot be exported). When a customer has no local generation, the system is configured to reduce the electricity from the measured energy asset, for example, a meter in the energy asset as a local meter approaches 0 kW. As such, electricity from the energy asset is never exported.
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Single location operation model where a customer has authorized local generation to export [0082] A single location operation model in which the AMS system is configured to operate each location optimally according to restrictions that include a no charge period ( that is, battery charging is prohibited during a specific window) and the non-export rule (that is, the generation of electricity from energy assets, including battery energy, cannot be exported). When the customer has local generation, the system provides that no energy from energy assets is exported by (2) providing meters of local level, level of renewable energy generation and in the inverter and represented by S = L - G - B, instructing reducing battery usage so that battery power is never exported, B <L always. Note that energy from local generation can be exported and, as such, when S is negative and L is zero, B is equal to zero.
Multi-site portfolio operation model [0083] In an example embodiment of the present invention, a computer program system, apparatus or product can be provided to implement or execute a method, process or algorithm to facilitate the optimization of the portfolio of multiple locations, each controlling a plurality of local energy assets and electrical consumption supplied by the grid.
[0084] In an exemplary embodiment, the system comprising the operating platform and a plurality of door devices, each located in a different location, can be configured to use, for example, data
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44/74 meter and billing histories, a library of tariffs and market / weather data to perform local level optimization, for example, by determining that one or more of the plurality of door devices to instruct to perform energy dispatch and at what times, thus reducing the electrical consumption provided by the network.
[0085] Figure 9 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention.
[0086] As shown in block 905 of Figure 9, an apparatus, such as apparatus 20 incorporated by operational platform 300 and / or apparatus 400, can be configured to receive and / or access input data. The input data is described in detail below. Once input data is received, as shown in block 910 of Figure 9, an apparatus, such as apparatus 20, incorporated by operating platform 300 and / or apparatus 400, can be configured to determine, as a function of the input data , a location of at least one of the energy consumers connected to the network to reduce the energy consumption provided by the network.
[0087] In addition to determining which location to reduce the energy consumption provided by the network, the amount of the reduction can be determined. As such, as shown in block 915 of Figure 9, an apparatus, such as apparatus 20 incorporated by operating platform 300 and / or apparatus 400, can be configured to determine an amount of a reduction in energy consumption provided by the network and, in some embodiments, additionally allocate the total reduction through the systems of each energy consumer connected to the grid. After determining where and
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45/74 how much will be the reduction in energy consumption provided by the network, instructions can be generated and sent. As shown in block 920 of Figure 9, an apparatus, such as apparatus 20 incorporated by operating platform 300 and / or apparatus 400, can be configured to transmit a signal to a corresponding port device located at the given location, the signal comprising data indicative of instructions for carrying out local energy dispatch. In some embodiments, the instructions can be configured to replace a previously provided local level schedule and, for example, increase battery usage.
[0088] In another exemplary embodiment, the system, comprising the operating platform and a plurality of door devices, each located in a different location, can be configured to use specific parameters to dynamically modify the schedules at the local level to carry out the optimization of portfolio.
[0089] The dynamic modification of each one or more schedules at the local level can be done according to specific parameters (for example, adhering to a baseline cost under agreement and / or energy saving level, providing new instructions to control the use of local energy assets and electricity consumption provided by the network. In some embodiments, the system may again use, for example, historical meter and billing data, a library of tariffs and market / weather data to perform optimization at the portfolio level and, in some embodiments, subsequently generate schedules at the local level. As described above, schedules at the local level can be
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46/74 provided to the door devices to instruct the use of local energy assets versus consumption of electricity supplied by the network. The door device can be configured to receive schedule data at the local level of the operating platform and implement a load reduction plan according to the schedule data, instructing, for example, the local controller to implement battery dispatch in real time or near real time. Figure 10 is a flow chart showing an exemplary method of operating an example apparatus according to an embodiment of the present invention.
[0090] As shown in block 1005 of Figure 10, an apparatus, such as apparatus 20 incorporated by operational platform 300 and / or apparatus 400, can be configured to receive and / or access input data. In some embodiments, the input data may comprise one or more of the following:
accounts set of all accountsservice in the portfolio intervals set of all time slots for one month no_charge_intervals subset of intervals where the battery cannot charge peak_intervals subset of intervals where the DCR peak is in effect mid._peak._in terval s subset of intervals where the average DCR peak is in effect uni t_capaci ty_kwh (e.g. 400) max_unit_charge_rate maximum rate at which a unitcharges (e.g. 200)
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max_unit_di s charge_rate maximum rate at which a unit discharges (eg 200) charging_efficiency (e.g. 0.90) discharging_efficiency (e.g. 0.95) interval_length_hrs 0.25 project_life number of years to amortize theinstallation / systems costs APR interest rate to amortize theinstallation / system costs
[0091] In some embodiments, the input data may comprise utility dispatch data. For example, data
utility dispatch may include: annual_uti1i ty_rate_kw Utility fee to calculate utility revenue
utility_dispatch_length_h Number of hours in each dispatch
LOL of usefulness
fixed_utility_commitment Utility commitment (kW)
utility_dispatches Set of indexes for dispatching utilities (ex: 1, 2, ..., 20) utility_intervalSd, h Subset of intervals for utility_dispaches, hour h and {1, ..., utility_dispatch_length_hr s}
[0092] In some embodiments, input data comprises demand load management (DCM) data from the host client. For example, host client DCM data can include:
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dem_ra te_kw Demand load for maximum demand peak_dem_rate_kw Demand load for peak peak demand mi d_peak_dem_ra te_kw Demand load for maximum demand at medium peak interval peak_cpp_dcm_di s count_kw Abatement of peak load demand per kW over the capacity reserve level (CRL) (> η 1 mid_peak_cpp_dcm_dis count_kw Abatement of the average peak demand load per kW over CRL (> 0). (0 if not take-or-pay CRL, or not in summer month)
[0093] In some embodiments, input data
comprise cost data of energy. For example, data from
energy costs may include:
cpp__intervals Subset of ranges where the price
critical c ie peak (CPP) is in effect energy__price__kwhi Price energy per kWh in interval i cpp__kwh__rate Price CPP energy highest_jsossible__crl A value greater than any real CRL
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49/74 [0094] In some embodiments, input data may comprise invoice saving data. For example, invoice savings data can include:
bill__savings__lb The minimum% saving on the original invoice that must be aica.nçada, or. the cost will be mcorricio to offset the balance.
bill___savings ub The maximum% savings from the original invoice that must be achieved. (Larger is allowed, but the model will not seek savings above this [0095] In some embodiments, input data may comprise account-specific data. For example, account-specific data may include:
native_demand_kwi, _the demand for account ae accounts in each time intervals fixed_battery_units ie _the number of battery units for ae accounts init__percent__full accounts (ex .: 0.25) native_capacity_ CRL ~ into force before reservation__level battery to account to and accounts post__battery_fixed_capacity_ CRL in effect after the battery for reservation levels account, ae accounts [0096] In some embodiments, input data may comprise data from native generation loads. For example, native generation load data:
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50/74 native_delivery_dcm_cost _a The pre-optimization generation demand load for ae accounts account native_delivery_energy_cost _a The pre-optimization energy generation cost for ae accounts account [0097] In some embodiments, input data may include data of native delivery charges. For example, native delivery billing data can include:
native_delivery_dcm_cost _a The pre-optimization delivery demand load for ae accounts native_delivery_energy_cost _a The pre-optimization delivery energy cost for ae accounts [0098] In some embodiments, the input data may already understand the demand data maximum observed. For example, observed maximum demand data can include:
observed_max_demand _a The maximum demand observed so far for this month (0 if it is day 1) for ae accounts observed_max_peak_demand _a The maximum peak demand observed for this month (0 if it is day 1) for ae accounts observed_max_mid_peak_demand _a The maximum peak demand average observed so far for
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this month (0 if it's day 1) for e accounts
[0099] In some embodiments, the input data may comprise direct access customer (DA) data or evaluation data contracted by a customer with energy resellers in unregulated markets. For example, DA customer data can include:
long_term_contract_price_kwhi, a The long-term contract
long_term_contract _kw i, _a $ / kWh for interval i and intervals, a and accounts0 kW long-term contract for interval i and intervals, a and accounts long_term_contract_cost _a 0 long-term contract cost (to calculate invoice savings), a and accounts imbalance_price_per_kwhi 0 $ / kWh market imbalance for interval i and intervals
[0100] In some embodiments, input data may comprise battery and generator cost data. In some embodiments, installation costs, maintenance costs, and operating costs can be considered. For example, battery cost data can include:
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ins tall__cos t__per__kwh _a System installation costs for npv calculation for e accounts cycle__tiers _a Set of cycles / year levels for, maintenance and initial costs, for E accounts (eg {50, 100, 150, 2 0 0, 3 65}) initial battery cos ^ per kwh _c , _a Initial capacity cost per kWh installed if at level c E c y c 1 and 11 e r s, E a c c u u t battery inaint cost psr kwhc. _The Maintenance cost of installed capacity / kWh if at level c E cycle tiers, E accounts incentive_jper__w Incentive / subsidy for uncommitted W for utility dispatch (eg $ 1 / W)
[0101] In some embodiments, input data can
understand data related to existing assets. For example,
data relating to existing assets may include:
existing solart, _the kW of solar energy in the
- interval i, for i E intervals, the E
account, s existing ^ windi, _the kW of wind energy in range i, for i E intervals, the E accounts
Petition 870190069613, of 7/22/2019, p. 56/91
53/74 existing_fuelcelli, the kW of fuel cell energy in range i, for i £ intervals, E accounts enlisting kW of generator power in range i, for i E intervals, a. E ιηΐ [0102] In some embodiments, input data may comprise solar energy data to stimulate hypothetical solar installations. For example, solar energy data can include:
solar__gen__per__kwi, _a The generation for 1 kW in the range for, i £ intervals, a. E accounts solar_system_cost_per_kw _a Solar system costs, for E accounts solar_install_costjper__kw _a Solar installation costs, for E accounts solar___cost____per____kwh _a Solar energy cost per kwh, for £ accounts [0103]
In some embodiments, input data may comprise computational data.
For example, computational data may include:
..bl í_gene st na ti erarion and st native deiivery
Petition 870190069613, of 7/22/2019, p. 57/91
54/74 native_peak_max_demanda = maximum native demand at peak intervals, V to 6 accounts native mid peak max demand === maximum native demand at average peak intervals, V to E accounts [0104] As shown in block 1010 of figure 10, an apparatus, such as apparatus 20 incorporated by operating platform 300 and / or apparatus 400, can be configured to calculate variable data.
[0105] On some achievements, data variables can understand and may include: realized_dem and ±, a Vi € intervals, G accounts > 0 kW battery end s tate _a , a Vie intervals, G accounts > 0 kW battery outi.V i G intervals, G accounts 0k W battery ini, _a V i and intervals, a. G accounts > 0 kW so lari, _the V i G intervals, G ci c c u n l. Ξι > 0 kW dumpi _the V i G intervals, G accounts > 0 kW solar namepl until k «a V a and accounts> 0 kW capacity res ervation .1 evela V to G accounts0k W in cycle tie r <- a V c and cycle_tiers, a. G accounts {0.1}
[0106] In some embodiments, variable data may comprise utility dispatch variables. For example, utility dispatch variables can include one or more of the following:
Petition 870190069613, of 7/22/2019, p. 58/91
55/74
utility credit kwi V d G utility_dispatches, h £[1, ..., utility dispatch length hrs},i € utility intervals ^ == 0 utility hourly avq kwa. h V d E utility dispatches, h € {I, ..., utility dispatch length hrs} ~ 0 u t i 1 i t y r e p o r t e d kwa V ci and utility d.i.spatches ~ 0 u t i 1 i t y__p c t__rae t {0.1} utility pctq r (0.1} utility__pct _p _q {0.1} u t i 1 i t yy _ p c t o _ p {0.1} y _r {0.1} y _q __r {0.1} Y _P. „Q (0.1} Yv.P {0.1} [0107] In some embodiments, variable data can
understand energy cost variables. For example, energy cost variables can include:
above_crl_cpp_realized_demandj, _a vje kW cpp intervals, a £ accounts 5 0
max above crl peak real ized_demanda V a £ accounts b 0 kW max_above_crl_mid_peak_ realized__demand V at € accounts> 0 kW is peak max above crl _a Go to £ accounts 1 if(0.1} max.above> is mid peak max above c Va E accounts 1 se(0.1} max.
cLCj-ITlÔ.
max peak realized demand V at £ accounts 0 kW
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56/74 max midjseak realized demand max realized demand bi 1.1 saving s _a bill savings deficit
V a e accounts h 0 kW
V a € accounts b Q kW
V a and accounts> $
V a e accounts> $ [0108] In some embodiments, variable data may include subsidy variables. For example, subsidy variables can include:
subsidy> 0 $ [0109] As shown in block 1015 of Figure 10, a device, such as device 20 incorporated by operating platform 300 and / or device 400, can be configured to perform portfolio optimization by applying models and, in some embodiments , adhering to specific restrictions.
[0110] An exemplary model is shown below. Although the model shown below may be a monthly model, one that a person of ordinary skill would appreciate, the models can be used for any period of time (for example, annual, daily or similar).
[0111] Therefore, the model can be configured to maximize:
* (total bill savings + utility revenue-solar energy cost) amortized development cost [0112] Where:
total_bill_savings = 2 _a and _accO unts (bill_savings _a bill_savings_deficit _a )
Petition 870190069613, of 7/22/2019, p. 60/91
57/74 utility_revenue = ((1.05 * y _r ) + utility_pct _q _ _r + (0.5 * utility_pctp_ _q ) + utility_pcto_p - (0.6 * yo_ _P ))) * * (annual_utility_rate_kw / 12) * fixed_utility_commitment) solar_energy_cost ⁼ Sieintervais 2aSaccounts * interval_length_hrs * solar_cost_per_kwh)
Amortized cost: A = P * [(r (1 + r) ^Λ η) / (1 + r) ^Λ (n - 1)] amortized — development — cost = net_development — cost * (APR * (1+ APR) ^A project_life) / ((1+ APR) ^A project_life-l) net — development — cost = battery_development — cost - subsidy + solar_development_cost battery_development_cost = 2 _a eaccounts battery_development_cost _a battery_development_cost _a = (fixed_battery_units _a * unit — capacity_kwh _a + battery_install_maint_cost _a ) V a E accounts battery_install — maint — costa = 2 _c e _cyc i _e _tiersa ((initial_battery_cost_per_kwh _c , a + battery_maint_cost_per_kwh _c , a) * in_cycle_tier _c , _a ) V a E accounts
Petition 870190069613, of 7/22/2019, p. 61/91
58/74 solar_development — cost = 2 _a and _accO unts (solar_nameplate_kw _a * (solar_system_cost_per_kw _a + solar_install_cost_per_kw _a )) [0113] In some embodiments, the models described above may be subject to particular restrictions. For example, models may be subject to invoice savings restrictions. [0114] For example, the model can set a lower limit on saving invoices. If the limit is not reached by the real economy, the deficit variable will assume the deficit.
bill savings _a > native bill _a * bill savings lb + bill savings deficit _a [0115] In some embodiments, the model can be configured to complete invoice savings at an upper limit and current savings, so this will be equal to the minimum: bill savings _a <native billa * bill savings ub bill savingsa. <generation dem savings _a 4- delivery dem savings _a + generation energy cost savings _a + delivery energy cost savings _a [0116] Where, for example, only include the applicable sections for the accounts, as described below.
[0117] Generation of DCM savings:
generation_dcm_savings _a = native_generation_dcm_cost _a (realized_base_generation_dcm_cost _a Petition 870190069613, of 7/22/2019, page 62/91
59/74 realized — peak — generation — dcm_cost _a realized_mid_peak_generation_dcm_costa V a E accounts realized — base_generation_dcm_costa = max_realized — demand * generation_dcm_rate_kw V a E accounts realized — mid — peak — generation_dcm_cost _a = max_mid — peak — realized_d__p_mon_mon-peak-realized-demand_month_month accounts realized_peak_generation_dcm_cost _a = max_peak_realized_demand _a * generation_peak_dcm_rate_kw V to E accounts [0118] DCM savings delivery:
Realized delivery_dcm_savingsa = native_delivery_dcm_costa-base_delivery_dcm_costa realized_peak_delivery_dcm_costa realized_mid_peak_delivery_dcm_costa + Realized-cpp_dcm_peak-discounta + realized_cpp_dcm_mid_peak_discounta Realized-base_delivery_dcm_costa = max_realized-demand E * V delivery_dcm_rate_kw accounts Realized _{peak-to-delivery_dcm_cost} = max_peak_realized-demand E * V accounts delivery_peak_dcm_rate_kw
Petition 870190069613, of 7/22/2019, p. 63/91
60/74 Realized-delivery_dcm_cost _{mid-peak-to-peak} = max_mid-demand Realized _the delivery_monthly_mid_peak_dcm_rate_kw * V E = _the accounts realized_cpp_dcm_peak_discount max_above_crl_peak_realized_demanda peak_cpp_dcm_discount_kw V * E-accounts Realized cpp_dcm_mid-peak _discount-a = mid-peak-max_above_crl —Realized — demand * mid_peak_cpp_dcm_discount_kw V to E accounts [0119] Generation: energy savings:
generation_energy_cost_savingsa = native_generation — energy_costa - long_term_contract — costa
- imbalance_cost V a E accounts imbalance_costa = Sieintervais (realized_demandi, a long_term_contract_kwi, a) * imbalance_price_per_kwhi * interval_length_hrs V a E accounts [0120] Delivery: energy savings delivery energy cost savings _a = native delivery energy costa ^_ energy_cost _a - energy_cost _a - energy_cost _a - energy a E accounts energy_costa = 2iei _n tervais realized_demandi, _a * interval_length_hrs * energy_ price_kwhi V a E accounts energy_cost — adj usta ^- Sie _C pp_intervals (above_crl — Cpp_realized — demandi, a * interval — length_hrs * (cpp_kwh_rate - energy_price) e_price accounts
Petition 870190069613, of 7/22/2019, p. 64/91
61/74 [0121] In some embodiments, the system can be configured to identify the monthly maximum realized total peak demand and average peak:
max_realized-demand> Realized-demandi, Vie intervals, E accounts max_peak_realized_demand _the ú realized_demandi, V i E peak_intervals, E accounts max-mid-peak-Realized-demand ú Realized-demandi, V i E mid_peak_intervals the E accounts [0122] In some embodiments, the system can be configured to set limits below the observed values:
max_realized — demand ú observed — max_demanda Vie intervals, E accounts maX — peak — realized — demand Ú observed — max_peak_demanda V i E peak_intervals, a E accounts max_mid_peak_realized_demanda ú observed_max_mid_peak_demand _a Vie mid_peak_intervals, a E accounts [0123] In some embodiments, The system can be configured to, for example, in months with a take-orpay contract, establish an alternative lower limit for maximum CRL:
max_realized — demand for capacity_reservation — leads V to E accounts maX — peak — realized — demand for capacity_reservation — leads V to E accounts
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62/74 maX — mid — peak — realized — demand> capacity_reservation — level _a V to G accounts [0124]
In some embodiments, the system can be configured to perform calculations above CRL.
[0125] For example, if the demand made is above CRL in a cpp range, above_crl_cpp_realized — demandj will be equal to the portion that is above it. Otherwise, it will be zero.
above_crl_cpp_realized_demandj, _a > realized_demandj, _a capacity_reservation_level _a V j E cpp_intervals, V a E accounts [0126] In some embodiments, the system can be configured to perform peak calculation.
max_above_crl_peak_realized_demand _a > max_peak_realized_demand _a
- capacity_reservation_level _to V to E accounts max_above_crl — peak — realized — demand d max_peak_realized — demand
- capacity_reservation — levela + highest — possible_cri * (1
- is_peak_max_above_crl _a ) V to E accounts max_above_crl — peak — realized — demand native_peak_max_demanda * is_peak_max_above_crl _to V a E accounts [0127] In some embodiments, the system can be configured to perform average peak calculations.
max_above_crl — mid — peak — realized — demand maX — mid — peak — realized — demand capacity_reservation_level _a V to E accounts
Petition 870190069613, of 7/22/2019, p. 66/91
63/74 max_above_crl — mid — peak — realized — demand <
max_mid — peak — realized — demand capacity_reservation — levela + highest — possible_crl * (1 is_mid_peak_max_above_crl _a ) V a E accounts max_above_crl_mid_peak_realized_demanda native_mid_peak_max_demanda * is_mid_peak_max_above_crl _a
V to E accounts [0128] In some embodiments, the models described above may be subject to particular restrictions. For example, models may be subject to utility restrictions.
[0129] In some embodiments, the system can be configured to capture the kW that can be counted for utility credit.
KWI-utility_credit <2a and _Acco unts fixed_battery_units _the max_unit_discharge_rate V * D is utility_dispatches H, and {1, ..., utility_dispatch_length_hrs}, i.e. utility_intervalsd, utility_credit KWI-h <2a and _Acco unts ± native_demand_kw _the realized- demands, _a V d E utility_dispatches, h E {1,
..., utility_dispatch — length — hrs}, i E utility_intervalsd, h [0130] In some embodiments, the system can be configured to identify the utility credit for this hour, without allowing any fluctuation.
Petition 870190069613, of 7/22/2019, p. 67/91
64/74 utility hourly avg kwd, h, _s = utility credit kwq, _s V s G scenarios, d E utility_dispatches ₃ , h E {1, ..., utility_dispatch_length_hrs}, i E utility_intervalsd, h, s [0131] In some embodiments, the system can be configured to identify the minimum time for each dispatch, utility reported kwq d utility hourly avg kwd, h V d G utility_dispatches, h G {1, ..., utility_dispatch_length_hrs} [0132] In some embodiments, the system can be configured to compute the percentage of known utility and determine the payment of utility or penalty imposed: utility — pct — met = Tde _u tiiity_dispatches uti 1 ity_reported_kwq / (fixed_utility_commitment * | utility_dispatches |) [0133] should be from:
yr + yq_r + yp_q + yo_p = 1 [0134] Turn off the indicators above the percentage reached. The objective function will ensure that as high as possible is switched on. utility_pct_met h 1.05 * y _r utility_pct_met h 0.75 * (y _r + y _q _r) utility_pct_met h 0.60 * (y _r + yq_r + y _P _q)
Petition 870190069613, of 7/22/2019, p. 68/91
65/74 [0135] Force the utility_pct variables to zero if the indicator is not on, otherwise the objective will be to direct them.
uti 1 ity_pctq_r ú 1.05 * y _q _ _r utility_pctp_ _q <0.7 5 * y _p _ _q utility_pcto_p ú 0.60 * yo_ _P [0136] Fill in these monthly variables utility_pct in the% of current monthly utility found.
uti 1 ity_pctq_ _r ú utility_ pct_met utility_pct _p _q d utility_ pct_met utility_pcto_p ú utility_ pct_met [0137] In some embodiments, the system can be configured to perform a battery cost calculation.
[0138] In some embodiments, the subsidy cannot exceed the useless contracted kW multiplied by the subsidy by kW.
subsidy d ^ accounts (fixed_ba11ery_units _a ) * max_unit — discharge_rate - fixed_utility_commitment) * subsidy_per_w * 1000 [0139] In some embodiments, the system can be configured to ensure that the system is at exactly one level to meet system guarantees.
Σc6cycle_tiersa ί n_cycle_tier _c , _a = 1 V to E accounts
Petition 870190069613, of 7/22/2019, p. 69/91
66/74 [0140] In some embodiments, the system can be configured to identify what level we are at. The left side is the actual number of cycles. One of the level identifiers must activate if the number of cycles exceeds the layer. This also ensures that the maximum permissible cycles are not exceeded in accordance with the energy asset warranty terms.
€i € intervals battery_ini, _a / (fixed_battery_units _a * unit — capacity_kwh) * 12 <c + (max_possible_cycles - c) * 2c'ε {cycle_tiersa c '> c) ί n_cycle_tier _C ', _a V c E cycle_tiers, a E accounts [0141] In some embodiments, the models described above may be subject to particular restrictions. For example, models may be subject to different restrictions.
[0142] In some embodiments, the system can be configured to capture the demand made.
realize_demandi a = native_demand_kwi, _the - battery_outi _the solaria - solaria existing - existing windi _the ^_ existing_fuelcelli, the - existing_enginei _a + battery_ini _a + dumpi, Vie intervals, E accounts [0143] In some embodiments, the The system can be configured to connect the solar nameplate and the curve to the interval variables.
solaria = solar_nameplate_kw _a * solar_gen_per_kwi, _a V i E intervals, a E accounts
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67/74 [0144] In some embodiments, the system can be configured to prevent loading during no-load intervals, except from allowed assets listed on the right.
battery_ini, d Solari, _A + existing_solari _a + existing_windi _a + existing_fuelcelli _a + existing_enginei, Vie no_charge_intervals, E accounts [0145] In some embodiments, the system may be configured to prevent the battery is charged (discharged) faster than the maximum charge (discharge) rate.
battery_ini, _a <fixed_battery_units _a * max_unit_charge_rate V i E intervals, a accounts battery_outi, _a d fixed_battery_units _a * max_unit_discharge_rate Vie intervals, a accounts [0146] In some embodiments, the system can be configured to prevent export to the network.
battery_outi _the native_demand_kw ± d, Vie intervals, and the accounts [0147] In some embodiments, the system may be configured to prevent the battery state of exceeding the battery capacity.
battery_end_statei, _a d fixed_battery_units * unit_capacity_kwh Vie intervals, a E accounts
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68/74 [0148] In some embodiments, the system can be configured to define the relationship between the battery output and the battery end_states.
battery_end_stateo.a = fixed_battery_units * _a * unit_capacity_kwh init_percent_full interval_length_hrs * _a + ((battery_ino _the charging_efficiency *) - (battery_outo, _A / discharging_efficiency)) V-E accounts battery_end statei _the battery_ = end_ statei-i, _the interval + —Length — hrs * ((battery_ini, _a * charging_efficiency) - (battery_outi, _a / discharging_efficiency)) Vie {1, 2, ..., | intervals | -1}, E accounts [0149] In some embodiments, the The system can be configured to set the battery's final state equal to the battery's initial state.
battery_end_state | interv _a is ii, _a = f ixed_battery_units _a * unit_capacity_kwh * init_percent_full _a V a E accounts [0150] In some embodiments, the system can be configured to optionally keep battery_units or CRL constant.
capacity_reservation_level _a = post_battery_fixed_capacity_reservation_level _a V a E accounts [0151] In some embodiments, the system can be configured to run the Model, for example, monthly, to
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69/74 each potential utility commitment and number of battery units per account.
[0152] As shown in block 1020 of Figure 10, an apparatus, such as apparatus 20 incorporated by operating platform 300 and / or apparatus 400, can be configured to provide schedules at the local level for each of the pluralities of door devices affected to facilitate control of the use of local energy assets and electrical consumption provided by the grid.
[0153] Figure 11 shows a diagram that illustrates a specific embodiment of multilocal portfolio optimization. The system can be configured to perform optimization at the local level in each of a plurality of locations. That is, for example, on an hourly (or more frequent) basis, a portfolio optimization algorithm can be executed, generating optimized dispatch instructions and sending DCR schedules to controllable asset systems each time it is executed. The algorithm can use forecast data for each location and the expected asset availability based on the forecast, location outage data, reflecting the latest status information for the port components, in addition to local controller / drive problems, ability to current and projected assets, contract and installation data, reflecting contract / territory combinations, port ID and installed capacity, load forecast data, historical interval data (15 minutes), local operational load data (1 minute) and generating resolved sets of dispatch instructions again to achieve maximum dispatch in each of the following contract / territory combinations. That
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70/74 will ensure that the system is prepared to meet the request for maximum dispatch, for example, the system / utility company, with updated data for a given day. This part of the process can be conceptualized as the aggregation methodology.
[0154] The system can then receive a dispatch signal from the utility system. For example, through a private tunnel on the public internet, to connect to the utility system, the operational platform can receive a signal for dispatching the event. In some embodiments, under contract, events can be dispatched as described above, for example, up to the maximum amount of capacity required for each respective contract. In other embodiments, the event signals may include the wholesale market geographic region, load aggregation point or zone composed of certain transmission substations, etc., contract ID, MW, Start Time and Duration. After receiving a dispatch signal, the system can then have, for example, a predefined time period (for example, 20 minutes) from the point of the utility signal to obtain a complete battery response.
[0155] After receiving the dispatch signal, the system can then execute the portfolio optimization process described above again. The system can then be configured to record on battery schedules. That is, the results of processing the event can cause the system to update the schedule information for the relevant units to be dispatched.
[0156] In each location, the system can cause a door reading, for example, every 0.5 to 5 minutes. In particular, each
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71/74 port device in the field may be asked to search the cloud platform to pull or receive updated battery schedules over a RESTful API or other secure transfer mechanisms, including publishing / subscription methods. These ports can be connected to the internet via a 4G / LTE cell modem on the port device. The door unit can store the complete schedule locally, with updated dispatch instructions for the event period. At the start time of a certain period of time or event, the door apparatus can record to the energy asset controller for the next event.
[0157] Figures 5, 6, 9 and 10 show flowcharts of exemplary operations performed by a method, apparatus and computer program product in accordance with an embodiment of the present invention. It will be understood that each block of the flowcharts and combinations of blocks in the flowcharts can be implemented by various means, such as hardware, firmware, processor, circuits and / or other device associated with the execution of software, including one or more computer program instructions. For example, one or more of the procedures described above can be incorporated by computer program instructions. In this regard, computer program instructions that incorporate the procedures described above can be stored by an apparatus 406 memory employing an embodiment of the present invention and performed by a processor 404 on the apparatus. As will be appreciated, any of these computer program instructions can be loaded onto a computer or other programmable device (for example, hardware) to produce a machine, so that the
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72/74 resulting computer or other programmable device provides the implementation of the functions specified in the block (s) of the flowchart. These computer program instructions can also be stored in a non-transitory computer-readable storage memory that can direct a computer or other programmable device to function in a particular way, so that the instructions stored in the computer-readable storage memory produce a manufacturing article, the execution of which implements the function specified in the block (s) of the flowchart. Computer program instructions can also be loaded onto a computer or other programmable device to cause a series of operations to be performed on the computer or another programmable device to produce a computer-implemented process, such that instructions executed on the computer or another programmable device provides operations to implement the functions specified in the flowchart block (s). As such, the operations of Figures 5, 6, 9 and 10, when performed, convert a computer or processing circuit into a particular machine configured to perform an example embodiment of the present invention. Therefore, the operations of Figures 5, 6, 9 and 10 define an algorithm for configuring a computer or processing to perform an example embodiment. In some cases, a general purpose computer may be provided with a processor instance that runs the algorithms of Figures 5, 6, 9 and 10 to transform the general purpose computer into a particular machine configured to perform an example embodiment.
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73/74 [0158] Consequently, the flowchart blocks support combinations of means to perform the specified functions and combinations of operations to perform the specified functions. It will also be understood that one or more blocks of flowcharts and combinations of blocks in flowcharts can be implemented by special purpose hardware-based computer systems that perform the specified functions or special purpose hardware combinations and computer instructions.
[0159] In some embodiments, some of the operations described here can be modified or also amplified as described below. In addition, in some embodiments, additional optional operations may also be included as shown by the blocks that have a dashed outline in Figures 5, 6, 9 and 10. It should be appreciated that each of the modifications, optional additions or amplifications below may be included with the above operations alone or in combination with any other among the features described here.
Portable Asset Mounted Energy Asset System [0160] In one embodiment of the present invention, the energy asset system described above can be mounted on a portable platform, for example, at a customer site, which allows for quick and easy installation , when necessary, the ability to relocate equipment. Figure 12 illustrates a diagram of a portable platform mounted energy asset system that can be supplied according to some embodiments of the present invention. In particular, embodiments of the present invention can provide a portable asset energy asset system (e.g., energy storage systems,
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74/74 diesel generators, gas turbines or similar) comprising electronic means of energy and communications. The energy asset system on a portable platform can include communication equipment, as described above, which allows remote monitoring and dispatch, an open architecture in which all components are packaged to support the elements.
[0161] Many modifications and other embodiments of the inventions presented here will remind a technician in the subject to which these inventions belong having the benefit of the teachings presented in the preceding descriptions and in the associated drawings. Therefore, it is to be understood that inventions should not be limited to the specific embodiments disclosed and that the modifications and other embodiments are intended to be included in the scope of the appended claims.
[0162] Furthermore, although the preceding descriptions and associated drawings describe example embodiments in the context of certain combinations of examples of elements and / or functions, it should be appreciated that different combinations of elements and / or functions can be provided by alternative embodiments without departing from the scope of the attached claims. In this regard, for example, different combinations of elements and / or functions other than those explained above are also contemplated as well as can be implemented in some of the attached claims. Although specific terms are used here, they are used only in a generic and descriptive sense and not for the purpose of limitation.

权利要求:
Claims (48)
[1]
1. System characterized by comprising: a platform device and a local door device, the platform device comprising at least one processor and at least one memory including computer program code, at least one memory and the program code of computer configured with the processor to make the device:
calculate local load curves indicating a customer's predicted local load in each of a plurality of day periods as a function of one or more of the historical meter and billing data, taking into account other existing local generation resources, and market or climatic data, for each of one or more clients with local energy assets within a given portfolio aggregation;
perform portfolio level optimization as a function of local load curves and a tariff library, portfolio level optimization configured to segment local load curves according to tariff periods and other location level restrictions, for each segment, calculate and issue a maximum energy consumption limit;
manages a set of schedules at the local level, as a function of portfolio-level optimization and one or more local constraints, the set of schedules at the local level configured to be supplied to a door appliance to facilitate the use of local assets from energy instead of the consumption of energy supplied by the grid; and the door apparatus comprising at least one processor and at least one memory including computer program code, at least one memory and the program code of
Petition 870190048576, of May 23, 2019, p. 10/29
[2]
2/17 computer configured to, with the processor, make the device:
receive the schedule at a local level from the platform device and store that schedule locally at a local level;
at a departure time for a given segment, provide instructions to facilitate the control of local assets in real time or close to real time.
2. System according to claim 1, characterized by the fact that local energy assets comprise energy storage resources and restrictions at the local level include instructions on charging and discharging batteries.
[3]
3. System according to claim 2, characterized by the fact that the computer program code configured to facilitate the control of local assets additionally comprises computer program code configured to, with the processor, make the device:
during a segment in which a customer's tariff or rate is less than a predefined limit and restrictions at the local level allow the charge, cause the predicted local charge to be satisfied by consuming the energy supplied by the network and enabling the loading of energy storage resources to the extent that the predicted local load does not meet the programmed maximum limit.
[4]
4. System according to claim 2, characterized by the fact that the computer program code configured to facilitate the control of local assets additionally comprises computer program code configured to, with the processor, make the device:
during a segment in which a customer's rate or fee is less than a pre-defined limit and level restrictions
Petition 870190048576, of May 23, 2019, p. 11/29
3/17 local do not allow the load, make the expected local load be satisfied by consuming the energy supplied by the network and disabling the load of the energy storage resources.
[5]
5. System according to claim 2, characterized by the fact that the computer program code configured to facilitate the control of local assets additionally comprises computer program code configured to, with the processor, make the device:
during a segment the tariff or customer rate is higher than a pre-defined limit and the restrictions at the local level do not allow the load, make the predicted local load be satisfied by consuming the energy supplied by the network up to a limit programmed maximum and causing any remaining part of the expected local load to be satisfied via electricity generation from the local energy asset and preventing the loading of energy storage resources.
[6]
6. System according to claim 2, characterized by the fact that the computer program code configured to facilitate the control of local assets additionally comprises computer program code configured to, with the processor, make the device:
avoid net exports to the electricity grid caused by the generation of electricity from the local energy asset, if such a local restriction exists from utility, interconnection, or other regulations.
[7]
7. System according to claim 2, characterized by the fact that the energy storage resources comprise battery systems.
Petition 870190048576, of May 23, 2019, p. 12/29
4/17
[8]
8. System according to claim 1, characterized by the fact that the computer program code configured to facilitate the control of local assets additionally comprises computer program code configured to, with the processor, make the device:
avoid the net export to the electric grid caused by the user of the local energy assets, if such local restriction exists based on utility, interconnection requirements or other regulations.
[9]
9. System according to claim 1, characterized by the fact that the local energy assets comprise one or more of renewable or non-renewable fuel generators or turbines.
[10]
10. Method characterized by understanding:
calculate local load curves indicating a customer's expected local load in each of a plurality of day periods as a function of one or more of the historical meter and billing data, taking into account other existing local generation resources, and market or climatic data, for each of one or more clients with local energy assets within a given portfolio aggregation;
perform portfolio level optimization as a function of local load curves and a tariff library, portfolio level optimization configured to segment local load curves according to tariff periods and other restrictions at the local level, and to each segment, calculate and issue a maximum energy consumption limit;
generate a set level schedules local, as a function of optimization at portfolio level and one or more restrictions locations, the set of timelines at the local level configured to be supplied to an appliance door to
Petition 870190048576, of May 23, 2019, p. 13/29
5/17 facilitate the use of local energy assets instead of the consumption of energy supplied by the grid; and transmitting the schedule at the local level to a door device; and make it possible, at the start of a given segment, to control local assets in real time or close to real time.
[11]
11. Method according to claim 10, characterized in that the local energy assets comprise energy storage resources and the restrictions at local level comprise instructions on charging and discharging batteries.
[12]
12. Method according to claim 11, characterized by the fact that the control of local assets also comprises:
during a segment in which a customer's tariff or rate is less than a predefined limit and restrictions at the local level allow the charge, make the predicted local charge to be satisfied by consuming the energy supplied by the network and enabling the loading of energy storage resources to the extent that the predicted local load does not meet the programmed maximum limit.
[13]
13. Method according to claim 11, characterized by the fact that the control of local assets also comprises:
during a segment in which a customer's tariff or rate is less than a pre-defined limit, restrictions at the local level do not allow the load, make the predicted local load to be satisfied by consuming the energy supplied by the network and disabling the loading of energy storage resources.
Petition 870190048576, of May 23, 2019, p. 14/29
6/17
[14]
14. Method according to claim 11, characterized by the fact that the control of local assets also comprises:
during a segment in which a customer's tariff or rate is greater than a predefined limit and restrictions at the local level do not allow the load, to ensure that the expected local load is met by consuming the energy supplied by the network up to a programmed maximum limit and causing any remaining part of the expected local load to be satisfied via electricity generation from the local energy asset and preventing the loading of energy storage resources.
[15]
15. Method according to claim 11, characterized by the fact that the control of local assets also comprises:
avoid net export to the electricity grid caused by the generation of electricity from the local energy asset, if such a local restriction exists based on utility, interconnection, or other regulations.
[16]
16. Method according to claim 11, characterized in that the energy storage resources comprise battery systems.
[17]
17. Method according to claim 10, characterized by the fact that it further comprises:
avoid net export to the electricity grid caused by the user of local energy assets, if such local restriction exists based on utility, interconnection, or other regulations.
[18]
18. Method according to claim 10, characterized by the fact that the local energy assets comprise one or more of renewable or non-renewable fuel generators or turbines.
Petition 870190048576, of May 23, 2019, p. 15/29
7/17
[19]
19. Computer program product characterized by comprising at least one non-transitory computer-readable storage medium with computer executable program code instructions stored therein, computer executable program code instructions comprising program code instructions for:
calculate local load curves indicating the expected local load of a customer in each of a plurality of day periods as a function of one or more of the meter and billing historical data, taking into account other existing local generation resources, and market or climatic data, for each of one or more clients with local energy assets within a given portfolio aggregation;
perform portfolio level optimization as a function of local load curves and a tariff library, portfolio level optimization configured to segment local load curves according to tariff periods and other restrictions at the local level, and for each segment, calculate and issue a maximum energy consumption limit;
generate a set of schedules at the local level, as a function of portfolio-level optimization and one or more local restrictions, the set of schedules at the local level configured to be supplied to a door appliance to facilitate the use of local assets from energy instead of the consumption of energy supplied by the grid; and transmitting the schedule at the local level to a door device; and make it possible, at the start of a given segment, to control local assets in real time or close to real time.
Petition 870190048576, of May 23, 2019, p. 16/29
8/17
[20]
20. Computer program product according to claim 19, characterized in that the local energy assets comprise energy storage resources and the restrictions at the local level comprise instructions on charging and discharging batteries.
[21]
21. Computer program product according to claim 20, characterized in that the computer program code configured to facilitate the control of local assets further comprises program code instructions for:
during a segment in which a customer's tariff or rate is less than a predefined limit and restrictions at the local level allow the charge, make the predicted local charge to be satisfied by consuming the energy supplied by the network and enabling the loading of energy storage resources to the extent that the predicted local load does not meet the programmed maximum limit.
[22]
22. Computer program product according to claim 20, characterized in that the computer program code configured to facilitate the control of local assets further comprises program code instructions for:
during a segment in which a customer's tariff or rate is less than a pre-defined limit, restrictions at the local level do not allow the load, make the predicted local load to be satisfied by consuming the energy supplied by the network and disabling the loading of energy storage resources.
[23]
23. Computer program product according to claim 20, characterized by the fact that the code of
Petition 870190048576, of May 23, 2019, p. 17/29
9/17 computer program configured to facilitate the control of local assets also includes program code instructions for:
during a segment in which a customer's tariff or rate is greater than a predefined limit and restrictions at the local level do not allow the load, to ensure that the expected local load is met by consuming the energy supplied by the network up to a programmed maximum limit and causing any remaining part of the expected local load to be satisfied via electricity generation from the local energy asset and preventing the loading of energy storage resources.
[24]
24. Computer program product according to claim 20, characterized in that the computer program code configured to facilitate the control of local assets further comprises program code instructions for:
avoid net export to the electricity grid caused by the generation of electricity from the local energy asset, if such a local restriction exists based on utility, interconnection, or other regulations.
[25]
25. Computer program product according to claim 20, characterized by the fact that energy storage resources comprise battery systems.
[26]
26. Computer program product according to claim 19, characterized in that the computer program code configured to facilitate the control of local assets further comprises program code instructions for:
avoid net export to the electricity grid caused by the user of local energy assets, if such a local restriction
Petition 870190048576, of May 23, 2019, p. 18/29
10/17 exist from utility, interconnection, or other regulations requirements.
[27]
27. Computer program product according to claim 19, characterized by the fact that the local energy assets comprise one or more generators or turbines with renewable or non-renewable fuel.
[28]
28. System configured to perform fleet-level management to reduce consumption of energy supplied by the network with a firm reduction in capacity, the system characterized by comprising:
a platform device and a plurality of door devices, the plurality of door devices comprising at least one first door device located in a first location, the first location being in the location of a power consumer connected to the electrical network and the second door appliance located at a second location, the second location being at a different location than the power consumer connected to the mains or at a different power consumer connected to the mains, each of the plurality of door appliances configured to control an asset local energy comprising at least one energy device asset, to control the use of local energy, rather than consumption of energy supplied by the grid;
the platform device comprising at least one processor and at least one memory including computer program code, at least one memory and the computer program code configured to, with the processor, cause the device to:
receive or access input data;
Petition 870190048576, of May 23, 2019, p. 19/29
11/17 determine, as a function of the input data, a location of each energy consumer connected to the power grid in which to reduce the consumption of energy supplied by the network;
determine a reduction amount of energy consumption provided by the network, and also allocate a total reduction through the systems of each energy consumer connected to the electricity network;
transmit a signal to each corresponding port device located at the specified location, the signal comprising indicative data of instructions for carrying out energy dispatch at the location.
[29]
29. System according to claim 28, characterized by the fact that the instructions are configured to replace a schedule at a local level previously provided and increase the use of the local energy asset.
[30]
30. System according to claim 28, characterized by the fact that at least one memory and the computer program code are additionally configured to, with the processor, make the device:
receive from a utility request, the utility request comprising at least one geographical area or a set of substations and the period of time in which to reduce consumption of energy supplied by the grid; and perform fleet level optimization to determine which one or more of the plurality of door devices instruct to perform energy dispatch on site and at what times, thereby reducing the consumption of energy supplied by the network in consideration of export restrictions liquid where applicable; and
Petition 870190048576, of May 23, 2019, p. 20/29
12/17 provide one or more schedules at the local level for each of a plurality of affected door devices to facilitate control of the use of local energy assets and the consumption of energy supplied by the network.
[31]
31. System according to claim 30, characterized by the fact that optimization at the fleet level comprises:
maximize a sum of total invoice savings across all accounts and utility revenue less amortized development cost.
[32]
32. System according to claim 30, characterized by the fact that the optimization at the fleet level is a function of an amount of bill savings for each of the energy consumers connected to the network.
[33]
33. System according to claim 30, characterized by the fact that optimization at the fleet level is a function of utility revenue, utility revenue being a function of an amount of energy dispatched on site.
[34]
34. System according to claim 30, characterized by the fact that optimization at the fleet level is a function of a development cost, the development cost being a function of one or more of the cost of the local energy storage system , installation cost, maintenance cost and operating cost.
[35]
35. Method to perform fleet-level management to reduce consumption of energy supplied by the network with a firm capacity reduction, the method characterized by comprising:
receive or access input data from a plurality of door devices, the plurality of
Petition 870190048576, of May 23, 2019, p. 21/29
13/17 door comprising at least one first door appliance located in a first location, the first location being in the location of an energy consumer connected to the power grid and the second door appliance located in a second location, the second location being in a different location of the power consumer connected to the mains or a different power consumer connected to the mains, each of the plurality of door devices configured to control a local power asset comprising at least one power device asset, for control the use of local energy, instead of consumption of energy supplied by the grid;
determine, as a function of the input data, a location for each energy consumer connected to the power grid in which to reduce the consumption of energy supplied by the network;
determine a quantity of energy consumption reduction provided by the network, and also allocate a total reduction through the systems of each energy consumer connected to the electrical network;
transmitting a signal to each corresponding port device located at the given location, the signal comprising indicative data of instructions for carrying out energy dispatch at the location.
[36]
36. Method according to claim 35, characterized by the fact that the instructions are configured to replace a previously provided local level schedule and increase the use of the local energy asset.
[37]
37. Method according to claim 35, characterized by the fact that it further comprises:
receive a utility request, the utility request comprising at least one geographic area or a
Petition 870190048576, of May 23, 2019, p. 22/29
14/17 set of substations and the time period in which to reduce consumption of energy supplied by the grid; and perform fleet-level optimization to determine which one or more of the plurality of door devices instruct to execute energy dispatch on site and at what times, thereby reducing the consumption of energy supplied by the network in consideration of net export restrictions where applicable; and provide one or more schedules at the local level for each of a plurality of affected door devices to facilitate control of the use of local energy assets and the consumption of energy supplied by the network.
[38]
38. Method according to claim 37, characterized by the fact that optimization at the fleet level comprises:
maximize a sum of total invoice savings across all accounts and utility revenue less amortized development cost.
[39]
39. Method according to claim 37, characterized by the fact that the optimization at the fleet level is a function of an amount of bill savings for each of the energy consumers connected to the network.
[40]
40. Method according to claim 37, characterized by the fact that optimization at the fleet level is a function of utility revenue, utility revenue being a function of an amount of energy dispatched on site.
[41]
41. Method according to claim 37, characterized by the fact that optimization at the fleet level is a function of a development cost, the development cost being a function of one or more of the cost of the local storage system
Petition 870190048576, of May 23, 2019, p. 23/29
15/17 energy, installation cost, maintenance cost and operating cost.
[42]
42. Computer program product perform fleet-level management to reduce consumption of energy supplied by the network with a firm capacity reduction, the computer program product characterized by comprising at least one non-transitory computer-readable storage medium with instructions of computer executable program code stored therein, computer executable program code instructions comprising program code instructions for:
receiving or accessing input data from a plurality of door devices, the plurality of door devices comprising at least one first door device located in a first location, the first location being in the location of a power consumer connected to the network electrical and the second door appliance located at a second location, the second location being at a different location than the power consumer connected to the electrical network or at a different energy consumer connected to the electrical network, each of the plurality of door appliances configured to control a local energy asset comprising at least one energy device asset, to control the use of local energy, rather than the consumption of energy supplied by the grid;
determine, as a function of the input data, a location for each energy consumer connected to the power grid in which to reduce the consumption of energy supplied by the network;
determine a quantity of energy consumption reduction provided by the network, and also allocate a total reduction through the systems of each energy consumer connected to the electrical network;
Petition 870190048576, of May 23, 2019, p. 24/29
16/17 transmit a signal to each corresponding door device located at the given location, the signal comprising indicative data of instructions for carrying out energy dispatch at the location.
[43]
43. The computer program product according to claim 42, characterized by the fact that the instructions are configured to replace a previously provided local level schedule and increase the use of the local energy asset.
[44]
44. The computer program product according to claim 42, characterized in that the computer executable program code instructions additionally comprise program code instructions for:
receive a utility request, a utility request comprising at least one geographic area or a set of substations and the time period in which to reduce consumption of energy supplied by the grid; and perform fleet level optimization to determine which one or more of the plurality of door appliances instruct to perform energy dispatch on site and at what times, thereby reducing the consumption of energy supplied by the network in consideration of net export restrictions where applicable; and providing one or more schedules at the local level for each of a plurality of affected door devices to facilitate control of the use of local energy assets and the consumption of energy supplied by the network.
[45]
45. Computer program product according to claim 44, characterized by the fact that optimization at the fleet level comprises:
Petition 870190048576, of May 23, 2019, p. 25/29
17/17 maximize a sum of total invoice savings across all accounts and utility revenue less amortized development cost.
[46]
46. Computer program product according to claim 44, characterized by the fact that optimization at the fleet level is a function of an amount of bill savings for each of the energy consumers connected to the network.
[47]
47. Computer program product according to claim 44, characterized by the fact that optimization at the fleet level is a function of utility revenue, utility revenue being a function of an amount of energy dispatched on site.
[48]
48. Computer program product according to claim 44, characterized by the fact that optimization at the fleet level is a function of a development cost, the development cost being a function of one or more of the local system cost energy storage costs, installation costs, maintenance costs and operating costs.

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同族专利:

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公开号 | 公开日

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GB201908936D0|2019-08-07|

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US9645596B1|2017-05-09|

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WO2018096424A1|2018-05-31|

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US10275842B2|2019-04-30|

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GB2571883A|2019-09-11|

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US20180144414A1|2018-05-24|

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AU2017364328A1|2019-07-11|

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AU2017364328B2|2022-01-27|

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法律状态:
2020-01-14| B25G| Requested change of headquarter approved|Owner name: ADVANCED MICROGRID SOLUTIONS, INC (US) |

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2021-10-05| B350| Update of information on the portal [chapter 15.35 patent gazette]|

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