An intelligent local energy management system in local mixed generation facilities to provide grid services

Abstract

An aspect of the present disclosure relates to a local energy management system (LEMS) in a local mixed generation facility to provide grid services and grid service applications. The LEMS generally serves as a local power control agent to facilitate energy management at the local facility level by controlling and leveraging multiple local assets deployed in the local facility and combining multiple generated power from each facility acting as its own virtual power plant to deliver grid services to the grid. In addition, the LEMS has the capability to effectively handle and fulfill the energy and electrical objectives of the grid services, including regulation or demand response objectives from the grid, by communicating operational set points that control the power charging and discharging in each local asset to meet those objectives.

Description

[Technical field]

[0001] Aspects of the present disclosure relate to an intelligent local energy management system for managing, optimizing, and controlling multiple or a mixture of power generation systems in one or more local mixed generation facilities to provide grid services and applications. [Background technology]

[0002] The aggressive trend towards 100% renewable energy in many parts of the country and the world is paving the way for the adaptation and infrastructure of local clean energy systems such as solar, wind, and hydroelectric power systems for use in commercial, residential, and vehicle charging, electricity, and heating applications. This trend is particularly evident in the electric vehicle (EV) industry, where recent market research data indicates that the demand for electric vehicles is expected to grow in the coming years. In turn, the demand and increase for public electric vehicle charging stations is also expected to increase in the coming years. These public EV charging stations are generally equipped with EV chargers or electric vehicle supply equipment (EVSE), which provide power for charging plug-in electric vehicles, including hybrid electric vehicles, fully electric vehicles, and the like. Power to these EV charging stations is primarily delivered by external power generation systems, such as power provided by the grid or other power generation systems, which are capable of sustaining and delivering large amounts of power to these charging stations via local power lines and power cables.

[0003] While EVSEs are widely used and deployed locally at public EV charging stations, other types of power systems that could benefit and enhance both the power and revenue generation capabilities at these local stations are generally not available, especially at the local facility level. For example, fixed energy storage (FES) systems are available as a backup power resource for these charging stations, but have not been widely adopted for other services, such as grid services, despite potentially having a very large power capacity and its ability to store and supply power. This is likely because FES systems operate as a single power source deployed for a specific service, and the entire capacity of the FES is dedicated to that specific service at the local facility level.

[0004] Thus, a need exists for such localized systems and methods for managing, controlling, and leveraging multiple power generation systems or a mixture thereof at one or more local facilities so that the local systems may expand power and revenue capabilities while providing grid services at the local facility level. Summary of the Invention [Means for solving the problem]

[0005] One implementation provides a method for 1) receiving one or more energy or electrical targets from an external entity by a local energy management system (LEMS) communicatively coupled to an external entity, a mixture of local power generating assets at a local facility, and a power grid, the mixture of local power generating assets being electrically coupled to the power grid; 2) receiving incoming raw data from the mixture of power generating assets by the LEMS; 3) generating one or more set points according to the one or more energy or electrical targets and the incoming raw data by the LEMS; 4) communicating, by the LEMS, the one or more set points to the mixture of local power generating assets; 5) performing one or more grid services by meeting the one or more energy or electrical targets by the mixture of local power generating assets; and 6) transferring power between the mixture of local power generating assets and the power grid by the mixture of local power generating assets.

[0006] In some aspects, techniques described herein relate to a method that includes receiving, by a local energy management system (LEMS) communicatively coupled to an external entity, a mixture of local power generating assets at a local facility, and a power grid, one or more energy or electrical targets from an external entity, where the mixture of local power generating assets may be electrically coupled to the power grid; receiving, by the LEMS, incoming raw data from the mixture of power generating assets; generating, by the LEMS, one or more set points according to the one or more energy or electrical targets and the incoming raw data; communicating, by the LEMS, the one or more set points to the mixture of local power generating assets; performing one or more grid services by meeting the one or more energy or electrical targets by the mixture of local power generating assets; and transferring power between the mixture of local power generating assets and the power grid by the mixture of local power generating assets.

[0007] In some aspects, the method may further include converting, by the LEMS, the incoming raw data into a structured protocol format via one or more protocol adapters.

[0008] In some aspects, the incoming raw data may include a plurality of input data and sensed data.

[0009] In some aspects, the external entity may include an aggregation platform, a frequency meter, an energy meter, or a third party system.

[0010] In some aspects, the mix of local power generation assets may include a combination of electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or local generating resources (LGR).

[0011] In some aspects, each LGR may include a solar, wind, and / or hydroelectric generating system.

[0012] In some aspects, each stationary energy storage system may include a battery, a battery pack, a capacitor, and / or an energy storage cell.

[0013] In some aspects, the method may further include converting, by the LEMS, the one or more set points into one or more structured protocol formats adapted to be interpreted by one or more devices in the mixture of local power generation assets.

[0014] In some aspects, the method may further include automatically adjusting one or more operating power settings of the targeted system according to one or more set points received by the targeted system, the targeted system being a component of a mixture of local power generation assets.

[0015] In some aspects, one or more operating power settings can be configured to control the voltage, frequency, and current on the targeted system.

[0016] In some aspects, an external entity can communicate with multiple local energy management systems located at different local facilities, and each local energy management system can be configured to be communicatively coupled to a corresponding mixture of local power generation assets having a configured power topology.

[0017] In some aspects, the techniques described herein relate to a system that includes a local energy management system (LEMS) electrically coupled to a mixture of local power generation assets at a local facility, a power grid, and an external entity, where the LEMS can be configured to receive one or more energy or electrical targets from the external entity, receive incoming raw data from the mixture of power generation assets, generate one or more set points according to the one or more energy or electrical targets and the incoming raw data, and communicate the one or more set points to the mixture of local power generation assets, where the mixture of local power generation assets can be configured to perform one or more grid services to meet the one or more energy or electrical targets, and transfer power between the mixture of local power generation assets and the power grid.

[0018] In some aspects, the LEMS can be further configured to convert incoming raw data into a structured protocol format via one or more protocol adapters.

[0019] In some aspects, the incoming raw data may include a plurality of input data and sensed data.

[0020] In some aspects, the external entity may include an aggregation platform, a frequency meter, an energy meter, or a third party system.

[0021] In some aspects, the mix of local power generation assets may include a combination of electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or local generating resources (LGR).

[0022] In some aspects, each LGR may include a solar, wind, and / or hydroelectric generating system.

[0023] In some aspects, each stationary energy storage system may include a battery, a battery pack, a capacitor, and / or an energy storage cell.

[0024] In some aspects, the LEMS can be configured to convert one or more set points into one or more structured protocol formats that can be adapted to be interpreted by one or more devices in the mixture of local power generation assets.

[0025] In some aspects, the LEMS can be configured to automatically adjust one or more operating power settings of the targeted system according to one or more set points received by the targeted system, which can be a component of a mix of local power generation assets.

[0026] In some aspects, one or more operating power settings can be configured to control the voltage, frequency, and current on the targeted system.

[0027] In some aspects, an external entity can communicate with multiple local energy management systems located at different local facilities, and each local energy management system can be configured to be electrically coupled to a corresponding mixture of local power generation assets having a predetermined power topology.

[0028] In some aspects, techniques described herein relate to a local energy management system electrically coupled to a power grid, a plurality of local power generating assets in a local facility, and an external entity, where the plurality of local power generating assets can be electrically coupled to the power grid. The system can include a plurality of sensors configured to monitor the plurality of local power generating assets and output raw sensor data for the plurality of local power generating assets, one or more inputs configured to receive at least one or more energy or electrical targets from the external entity, and a control system configured to receive the raw sensor data, receive the one or more energy or electrical targets, generate one or more operating parameter set points for the plurality of power generating assets based on the one or more energy or electrical targets and the raw sensor data, and output the one or more operating parameter set points to the plurality of local power generating assets, where the one or more operating parameter settings of the plurality of local power generating assets can be configured to be adjusted in accordance with the one or more operating parameter set points to meet the one or more energy or electrical targets.

[0029] In some aspects, the control system can be further configured to convert the raw sensor data into a structured protocol format via one or more protocol adapters.

[0030] In some aspects, the one or more inputs can be further configured to receive raw input data, and the controller can be configured to generate one or more operating parameter set points further based on the raw input data.

[0031] In some aspects, the external entity may include an aggregation platform, a frequency meter, an energy meter, or a third party system.

[0032] In some aspects, the multiple local power generation assets may include one or more of electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or local generating resources (LGR).

[0033] In some aspects, the LGR may include solar, wind, and / or hydroelectric generating systems.

[0034] In some aspects, the stationary energy storage system may include a battery, a battery pack, a capacitor, and / or an energy storage cell.

[0035] In some aspects, the system can be further configured to convert the one or more operational parameter set points into one or more structured protocol formats, which can be configured to be interpreted by one or more devices in the multiple local power generation assets.

[0036] In some aspects, the system may be further configured to automatically adjust one or more operational parameter settings of the target components of the plurality of local power generation assets in accordance with the one or more set points received by the target components.

[0037] In some aspects, the one or more operating parameter settings can be configured to control the voltage, frequency, and / or current on the target component.

[0038] In some aspects, under adjusted one or more operating parameter settings, the multiple local power generation assets can be configured to transfer power between the multiple local power generation assets and a power grid.

[0039] In some aspects, the external entity may further communicate with a plurality of other local energy management systems located in other different local facilities, each of which may be configured to be electrically coupled to a corresponding plurality of local power generation assets having a predetermined power topology.

[0040] In some aspects, techniques described herein relate to a method of intelligent energy management in a local facility using a local energy management system (LEMS) communicatively coupled to an external entity, a plurality of local power generating assets in the local facility, and a power grid, where the plurality of local power generating assets can be electrically coupled to the power grid. The method can include receiving raw sensor data for the plurality of local power generating assets from a plurality of sensors of the LEMS using a control system of the LEMS, receiving at least one or more energy or electrical targets from an external entity from one or more inputs of the LEMS, generating one or more operating parameter set points for the plurality of local power generating assets based on the one or more energy or electrical targets and the raw sensor data, and outputting the one or more operating parameter set points to the plurality of local power generating assets, where the one or more operating parameter settings of the plurality of local power generating assets are configured to be adjusted in accordance with the one or more operating parameter set points to meet the one or more energy or electrical targets.

[0041] In some aspects, the method may further include converting the raw sensor data into a structured protocol format via one or more protocol adapters.

[0042] In some aspects, the one or more inputs can be further configured to receive raw input data, and generating the one or more operating parameter set points can be further based on the raw input data.

[0043] In some aspects, the external entity may include an aggregation platform, a frequency meter, an energy meter, or a third party system.

[0044] In some aspects, the multiple local power generation assets may include one or more of electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or local generating resources (LGR).

[0045] In some aspects, the LGR may include solar, wind, and / or hydroelectric generating systems.

[0046] In some aspects, the stationary energy storage system may include a battery, a battery pack, a capacitor, and / or an energy storage cell.

[0047] In some aspects, the method may further include converting the one or more operational parameter set points into one or more structured protocol formats, the one or more structured protocol formats may be configured to be interpreted by one or more devices in the multiple local power generation assets.

[0048] In some aspects, the method may further include automatically adjusting one or more operational parameter settings of the target components of the plurality of local power generation assets in accordance with the one or more set points received by the target components.

[0049] In some aspects, the one or more operating parameter settings can be configured to control the voltage, frequency, and / or current on the target component.

[0050] In some aspects, under adjusted one or more operating parameter settings, the multiple local power generation assets can be configured to transfer power between the multiple local power generation assets and a power grid.

[0051] In some aspects, the external entity may further communicate with a plurality of other local energy management systems located in other different local facilities, each of which may be configured to be electrically coupled to a corresponding plurality of local power generation assets having a predetermined power topology.

[0052] In some aspects, techniques described herein relate to a method of intelligently managing and controlling grid services across one or more local power generating facilities, the method including receiving raw data for the multiple local power generating assets at a current state under control of an electronic aggregation platform in electrical communication with multiple local power generating assets at the local facility, the multiple local power generating assets may be electrically coupled to a power grid, calculating one or more energy or electrical targets for the local facility based, at least in part, on the raw data at the current state, generating one or more operating parameter set points for the multiple local power generating assets based, at least in part, on the one or more energy or electrical targets and the raw data, and outputting the one or more operating parameter set points to the multiple local power generating assets, wherein the one or more operating parameter settings of the multiple local power generating assets may be configured to be adjusted in accordance with the one or more operating parameter set points to meet the one or more energy or electrical targets.

[0053] In some aspects, the method may further include converting the raw data into a structured protocol format via one or more protocol adapters.

[0054] In some aspects, the multiple local power generation assets may include one or more of electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or local generating resources (LGR).

[0055] In some aspects, the LGR may include solar, wind, and / or hydroelectric generating systems.

[0056] In some aspects, the stationary energy storage system may include a battery, a battery pack, a capacitor, and / or an energy storage cell.

[0057] In some aspects, the method may further include converting the one or more operational parameter set points into one or more structured protocol formats, the one or more structured protocol formats configured to be interpreted by one or more devices in the plurality of local power generation assets.

[0058] In some aspects, the method may further include automatically adjusting one or more operational parameter settings of the target components of the plurality of local power generation assets in accordance with the one or more set points received by the target components.

[0059] In some aspects, the one or more operating parameter settings can be configured to control the voltage, frequency, and / or current on the target component.

[0060] In some aspects, under adjusted one or more operating parameter settings, the multiple local power generation assets can be configured to transfer power between the multiple local power generation assets and a power grid.

[0061] In some aspects, the electronic aggregation platform may further be in electrical communication with a local energy management system (LEMS), and the step of generating and outputting the one or more operating parameter set points may be performed by a control system of the LEMS under control of the electronic aggregation platform.

[0062] In some aspects, the LEMS may be physically present at a local facility.

[0063] In some aspects, the LEMS may be off-site on a remote server that is physically separate from the local facility.

[0064] In some aspects, the electronic aggregation platform may further be in electrical communication with a plurality of other local energy management systems located at other different local facilities, each of which may be configured to be electrically coupled to a corresponding plurality of local power generation assets having a predetermined power topology.

[0065] In some aspects, the method may further include determining one or more energy or electrical targets for the local facility at the one or more future states.

[0066] In some aspects, the method may further include calculating one or more operating parameter set points for the local facility at the one or more future states based, at least in part, on the one or more energy or electrical targets for the local facility at the one or more future states.

[0067] In some aspects, the method may further include predicting changes in the local facility at one or more future states based on the raw data at the current state and the dynamic predictive model.

[0068] In some aspects, the change in the local facility in one or more future states may include changes attributable to multiple local power generation assets.

[0069] In some aspects, the change in the local facility in the one or more future states may include a system level change in the local facility.

[0070] The following description and the annexed drawings set forth in detail certain illustrative features of one or more implementations. [Brief description of the drawings]

[0071] The accompanying drawings depict certain aspects of one or more implementations and are therefore not to be considered as limiting the scope of the disclosure.

[0072] [Figure 1] FIG. 1 depicts an example of a power distribution topology having one or more power producer grids electrically coupled to a remote distribution of multiple local mixed generation facilities.

[0073] [Figure 2A] FIG. 2A depicts an example power topology in one local mixed generation facility having a mix of local generation assets.

[0074] [Figure 2B] FIG. 2B depicts an example of a power topology at one of the local mixed generation facilities having a mix of local generation assets.

[0075] [Diagram 3] 3A-3C depict diagrams of a local power generation asset comprising multiple EVSEs at an EVSE charging station.

[0076] [Figure 4] FIG. 4 depicts a diagram of a second local power generation asset comprising a local generating resource and an FES.

[0077] [Diagram 5] FIG. 5 depicts an example power topology in a local mixed generation facility.

[0078] [Figure 6] FIG. 6 depicts an example power topology in a local mixed generation facility.

[0079] [Figure 7] FIG. 7 depicts an example power topology in a local mixed generation facility.

[0080] [Figure 8] FIG. 8 illustrates a block diagram of a Local Energy Management System (LEMS).

[0081] [Figure 9] FIG. 9 depicts the input sub-block of the Local Energy Management System (LEMS).

[0082] [Figure 10] FIG. 10 depicts the sensing sub-block of the Local Energy Management System (LEMS).

[0083] [Figure 11] FIG. 11 depicts multiple sensing points measured by a sensing sub-block of a local energy management system (LEMS).

[0084] [Figure 12] FIG. 12 depicts the data processing sub-block of the Local Energy Management System (LEMS).

[0085] [Figure 13]FIG. 13 depicts the organizational execution and control sub-blocks of the Local Energy Management System (LEMS).

[0086] [Figure 14] FIG. 14 depicts the output sub-block of the Local Energy Management System (LEMS).

[0087] [Figure 15] FIG. 15 depicts a flowchart and method for implementing grid services through a local energy management system (LEMS) and a mixture of local generation assets at one or more local mixed generation facilities.

[0088] [Figure 16] FIG. 16 depicts the LEMS-EVSE local power topology.

[0089] [Figure 17] FIG. 17 depicts the LEMS-LGR local power topology.

[0090] [Figure 18] FIG. 18 depicts the LEMS-FES local power topology.

[0091] [Figure 19] FIG. 19 depicts the LEMS multiple mixed local power topology.

[0092] [Figure 20] FIG. 20 depicts a distributed local asset-power topology controlled and managed by a single LEMS.

[0093] [Figure 21] FIG. 21 depicts a heterogeneous combination of LEMS power topologies in communication with an aggregation platform.

[0094] [Figure 22]FIG. 22 depicts an example of status information obtained by the aggregation platform in the initial state S0 from the local power topology.

[0095] [Figure 23] FIG. 23 depicts the local power topology in a future state S1.

[0096] [Figure 24] FIG. 24 depicts the local power topology at a subsequent future state S2.

[0097] [Diagram 25] FIG. 25 depicts a schematic diagram of multiple states, starting at an initial state S0, by which the aggregation platform may dynamically predict, determine, and calculate set points to meet certain energy or electrical targets.

[0098] To facilitate understanding, the same reference numbers have been used, where possible, to designate like elements that are common to the figures. It is contemplated that elements and features of one implementation may be beneficially incorporated in other implementations without further recitation. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0099] (Detailed Description) 1 illustrates an example of a power distribution topology 100 having one or more power producer grids (101-1-101-n) electrically coupled to remote distribution of multiple local mixed generation facilities (200-1, 200-2, ..., 200-n) across various geographic locations via a transmission system 104 and a distribution system 106, according to one implementation. It should be noted that the local mixed generation facilities (200-1, 200-2, ..., 200-n) are not limited to distribution topology 100 and may be implemented in other types of distribution topologies having configurations that may or may not include combinations of transmission systems, distribution systems, grid systems, and / or microgrid systems with AC, DC, or mixed power systems. It should also be noted that the local mixed generation facilities (200-1, 200-2, ..., 200-n) are maintained, operated, and under the control of a grid service provider that provides one or more grid services to grid operators, distribution companies, higher level aggregation servers, generators, electrical entities, etc.

[0100] The terminology and numerical designations used herein will now be defined with reference to FIG.

[0101] The numerical designation NNN-n, such as 100-1, 200-1, etc., is used throughout this document where "NNN" represents a system level component and "-n" represents a local facility component at a particular location "-n." In addition, the system level reference "NNN" is applicable to local facility component "-n" at each location having the same system level component "NNN."

[0102] Each grid 101 generally refers to an electrical power system from generation to electrical outlet. It includes generators, transmission and distribution lines, transformers, switchgear, and wiring at a "premises" (e.g., a home, building, parking lot, and / or other parking location from the electric meter for that location through the electrical panel to the electrical outlet). Sensors, computational logic, and communications may be located at one or more locations in the grid to monitor functions associated with the grid, and a vehicle's electrical system may satisfy one or more functions with respect to the grid. The power producer grid 101 may be one or more utility-level power producers, such as power plants, to provide grid power. Although shown as a single entity, a power producer may represent multiple power producing entities, such as different types of power plants (e.g., coal, gas, nuclear, hydro, wind, solar, geothermal, and others). Power producers provide power to a grid, including grids of any scale.

[0103] Transmission system 104 generally refers to a transmission grid consisting of a network of power stations, transmission lines, and substations that communicate power within the grid using DC and / or three-phase AC.

[0104] Distribution system 106 generally refers to the last stage of the electric grid that distributes electricity to residential properties, commercial properties, industries, and other end users. Distribution simultaneously delivers power to users on the grid 101 and may reduce the power once delivered to a safe customer usable level.

[0105] A grid-integrated vehicle 108 generally refers to a mobile machine for transporting passengers, cargo, or equipment. A grid-integrated vehicle has an "on-board" energy storage system (such as electrochemical, distillate petroleum product, hydrogen, and / or other storage devices) and a grid connection system for recharging or replenishing the on-board storage device (e.g., battery, capacitor or flywheel, electrolytic hydrogen) with power from the grid 101. A grid-integrated vehicle may also be plugged into the grid 101 (also referred to as a V2G electric vehicle) to provide power from the vehicle's on-board storage device to the grid 101.

[0106] Electric vehicle equipment (EVE) generally refers to the equipment physically located within each grid-integrated vehicle 108 to enable communication and power flow. In an example implementation, the EVE receives EVSE attributes (described below) and controls power flow and grid services to and from the grid-integrated vehicle based on, for example, the EVSE attributes, the state of the vehicle's on-board storage equipment, expected operating requirements, and the driver's desires. The EVE may include a vehicle link (VL), also referred to as a vehicle smart link (VSL), that provides an interface between the EVSE and the grid-integrated vehicle's vehicle management system (VMS), which generally controls the electrical and electronic systems within the grid-integrated vehicle while it is not in use (e.g., while parked in a garage).

[0107] Electric vehicle station equipment (EVSE) generally refers to equipment for interfacing an EVE with the grid 101. The EVSE may be located, for example, in a building or parking garage, near a road, or adjacent to an automated vehicle parking space. An EVE in a grid-integrated vehicle 108 with on-board storage and power delivery and information connections may be connected to the EVSE. The EVSE can store EVSE attributes and transmit the attributes to the EVE or other devices of the grid-integrated vehicle.

[0108] The aggregation platform 115 refers to one or more computer network servers having software, hardware, and management procedures that communicate with any energy load storage or energy production devices, such as, but not limited to, grid-integrated vehicles, directly from the EVE and / or via the EVSE, issue requests to those vehicles for charging, discharging, and other grid functions, and provide grid services to grid operators, distribution companies, higher level aggregation servers, power generators, or other electric entities. The aggregation platform 115 may also receive reports on grid services and charging from the EVE and / or EVSE. An aggregator is a business entity that manages the aggregation server 115. The aggregation platform 115 may manage (control) the power flow to / from the grid-integrated vehicles connected to the grid 101 and aggregate and sell power (e.g., power in megawatts (MW)) to the grid operator. The aggregation platform 115 may also manage information for other entities, including electric charging suppliers, local distribution companies, and others. In yet another implementation, the aggregation platform 115 may include a serverless-based system. A serverless-based system can be based on a microservices-based architecture that can include multiple processing applications and entities operating within a remote or cloud-based network that can include heterogeneous computing systems.

[0109] A local mixed power facility (200-1-200-n) generally refers to a combination of one or more mixed power generation sources that are intelligently managed and controlled by a designated intelligent local energy management system at one or more remote facilities. In operation, each local mixed power facility (200-1-200-n) at each remote facility is configured to receive and supply power from and to the grid 101 via one or more grid-integrated vehicles (108-1-108-n) and local generating resources (113-1-113-n), with each local mixed power facility (200-1-200-n) being meant to represent one or more systems of a similar type. The term "local" refers to being physically and / or logically tied to a facility (200-1-200-n). The local power generating facilities (200-1-200-n) are also referred to as microgrids, which are local generation sources (not necessarily intermingled) and thus can be disconnected from the grid 101 and still have the ability to sustain the energy needs of the facility, but also be coupled to the grid 101 at one or more points and receive power from and / or discharge power to the grid 101.

[0110] EVE attributes generally refer to information describing a grid-integrated vehicle that may be transmitted to the EVSE to which the vehicle is connected, to the aggregation platform 115, or to another grid-integrated vehicle. These may include (1) a unique grid-integrated vehicle ID, (2) permitted billing and other commercial relationships, (3) the vehicle's approvals, such as IEEE 949 certification for anti-islanding, and (4) the vehicle's technical capabilities, including maximum power output, whether it can produce power independent of grid power ("emergency power mode"), and others.

[0111] EVSE attributes are information related to an EVSE, such as its status, location, and other information. EVSE attributes generally refer to information related to an EVSE that is transmitted to the EVE of a grid-integrated vehicle. This may include (1) physical capability characteristics of the EVSE, (2) legal and administrative authorizations, (3) legal and administrative restrictions, (4) a unique EVSE ID, (5) permitted claims and other commercial relationships (in which the EVSE and grid-integrated vehicle participate), (6) grid services that may be approved (permitted) at this particular EVSE location, and / or others.

[0112] An electric charging supplier generally refers to a management entity that manages an EVSE. In one implementation, an EVSE may not have any electric charging supplier. For example, an EVSE in a home garage is used to charge the homeowner's vehicle from the same electrical source used by other appliances in the home. In other implementations, an electric charging supplier may have either real-time or delayed communication with the EVSE and may provide real-time approval for charging to a grid-integrated vehicle that is connected to the grid and may request payment for charging.

[0113] A parking lot operator generally refers to a business or organization that controls a space where a vehicle may be parked, e.g., involving one or more adjacent EVSEs. The parking lot operator may charge for use of its space, require identification prior to parking, and / or barter use of the space in exchange for use of an EVSE.

[0114] Grid operators may include, for example, (1) distribution system operators (DSOs), (2) transmission system operators (TSOs) or independent system operators (ISOs), (3) generators, (4) independent power producers (IPPs), and / or (5) renewable energy operators.

[0115] Grid services generally refer to services provided between a grid-integrated vehicle and the grid 101 where power flows through the EVSE. Grid services may include, among many others, (1) local building services such as emergency power, (2) distribution system services such as (i) providing reactive power, (ii) drawing off-peak consumption, (iii) balancing loads on a three-phase system, (iv) providing demand response, (v) providing distribution support (e.g., by postponing consumption or dumping energy when the distribution system is reaching its limits, or by using condition monitoring such as transformer temperature to reduce power through that transformer), and (3) transmission and generation system support such as (i) providing frequency regulation, (ii) providing time regulation, (iii) providing spinning reserve, and / or (4) renewable energy support such as (i) providing wind balancing, (ii) providing ramp rate reduction, (iii) providing energy shifting from solar peaks to load peaks, and (iv) absorbing wind or solar power when it exceeds the load. For example, grid services may include off-peak billing, regulating the quality of grid power, producing power quickly and sufficiently to prevent grid failures or blackouts, and smoothing generation from waxing and waning renewable energy sources such as wind and solar sources.

[0116] A grid location generally refers to an electrical system location to which an EVSE is connected. It may be a hierarchical location (e.g., an electrical position) in the electrical system and may not correspond to a physical location. In an example implementation of the present disclosure, a grid location may be defined based on one or more of: (1) the building circuit to which the EVSE 111 is connected and fused, (2) the overhead service line and meter to which the EVSE is connected, (3) the distribution transformer to which the EVSE is connected, (4) the distribution feeder for the EVSE, (5) the substation for the EVSE, (6) the transmission node for the EVSE, (7) the local distribution company for the EVSE, (8) the transmission system operator for the EVSE, (9) the subarea for the EVSE, and (10) the area, ISO, or TSO for the EVSE. Due to distribution circuit switching (e.g., reconfiguration), intermediate positions in the hierarchical structure may change dynamically, such that, for example, the grid location of an EVSE may dynamically move from one distribution feeder to another as distribution switches are opened and closed, even though the physical location of the EVSE does not change.

[0117] Local Energy Management Systems (LEMS)

[0118] Aspects of the disclosure provide an apparatus, method, processing system, and computer-readable medium for an intelligent local energy management system (LEMS) 210 for managing, optimizing, and controlling power to and from the grid 101 through combining and blending local generating facilities with energy storage and generation systems at each local facility (Facility-1...Facility-n). Each local facility (Facility-1-Facility-n) may be equipped with its own LEMS (210-1-210-n) for managing, controlling, and implementing energy management to and from the grid and executing logic for realizing grid services. To accomplish that, the LEMS 210 is configured to receive and analyze inputs from available resources at the local facility, including, for example, local generation, stationary storage, or power provided by electric vehicles when plugged into an EVSE at an EVSE charging station. These EVSEs can support unidirectional, bidirectional, AC, or DC through power converters. LEMS210 may also receive sensory inputs from all available resources in each local facility and, optionally, intercept energy meter information to monitor different subcomponents at any given time. In addition, LEMS210 may receive inputs and control signals from, and transmit data back to, the aggregation platform to control the local assets to meet the power demand to and from the grid 101. Furthermore, LEMS210 may receive multiple input data from local assets, subcomponents, and external systems to meet the goals of facility 200 to deliver grid services to and from the grid 101. LEMS210 may also determine and generate operating set points based on the input data from the local assets and communicate these set points across different subsystems of the local assets to meet the goals of facility 200. The implementation of the intelligent local energy management system LEMS210 in each local facility (Facility 1-Facility n) is provided in the following sections.

[0119] 2A-2B illustrate an example of a power topology in one of the local mixed power generation facilities 200 having a mixture of local power generation assets ("local assets"). The illustrated power topology also includes internal subsystems, hardware components, and metering devices for communicating condition status, monitoring electrical conditions, transmitting control signals, and delivering and receiving power to and from the grid 101 via power line P0. In the foregoing disclosure, the example power topology depicted in FIGS. 2A-2B in the local mixed power generation facility 200 provides a general representation of the system level configuration applicable to each power generation facility (200-1 in FIG. 2A and 200-1-200-n in FIG. 2B). A legend is depicted in the upper right corner of FIGS. 2A-2B illustrating line patterns, arrows, and other reference objects indicating sensing paths, communication lines, power lines, control paths, and flow directions within the local mixed power generation facility 200. Examples of network communication lines and control paths may be implemented wirelessly, such as wireless adapters and antennas, or through wired connections, such as, but not limited to, network cabling, fiber optic lines, twisted pairs, or coaxial cables. In addition, other network equipment (not shown), including, but not limited to, network controllers, switches, hubs, routers, access points, and repeaters, are provided in the system to handle communication, interaction, and mediation of data transmission between devices over the computer network. Examples of power lines (P1, P2, P3) in facility 200 may be implemented over AC and / or DC power lines with various degrees of voltage lines, such as low voltage lines, medium voltage lines, high voltage lines, and extra high voltage lines.

[0120] A non-limiting example of how a local energy management system (LEMS) 210 functions in the local mixed power plant 200 will be described with reference to FIG. 2A. In the illustrated example, the LEMS 210 is physically located within the plant. The LEMS 210 communicates with and is under the control of an aggregation platform 115, which intelligently manages and controls multiple grid services across the local mixed power plant 200. A number of local power generation assets in the local mixed power plant 200 communicate with and are under the control of the LEMS 210. In the illustrated example, one group of local power generation assets includes four EVSEs (EVSE1...4) located at a public EVSE charging station 111. The EVSE1-4 utilize on-board batteries from electric vehicles (EVs) 108 (see FIG. 1) that plug into the EVSE1-4. The EVSE1-4 can communicate power to and from the grid 101 via power lines (P0, P1, and P2). Under control of LEMS 210, EVSEs 1-4 can charge batteries from plugged-in electric vehicles by communicating power from grid 101 via power lines P0, P1, and P2. Under control of LEMS 210, one or more of EVSEs 1-4 can also discharge batteries from plugged-in electric vehicles by communicating power to grid 101 via power lines P0, P1, and P2. Alternatively, power discharged from the EVs can be provided to Building 1 and / or Building 2, which can be managed by a Facilities Management System (FMS) 301. LEMS 210 can query the FMS system 301 to determine the amount of power provided by the EVs to Building 1 and / or Building 2.

[0121] In the illustrated example, LEMS 210 can query the EVSEs and / or FMS system 301 in local facility 200 to determine the following: EVSE1 is bidirectional with a plugged-in V2G electric vehicle (EV). In one non-limiting example, the combination of plugged-in EV and EVSE1 has a power capacity of -40 kW charging and 40 kW discharging. The power capacity may limit the maximum capacity of the EV and / or EVSE. The EV plugged in at EVSE1 is currently charging at -20 kW and charging is controllable. EVSE2 is bidirectional with a plugged-in V2G EV. Charging of the EV plugged in at EVSE2 is not controllable due to the user's mobility needs. The EV plugged in at EVSE2 is currently charging at -60 kW. In other words, EVSE2 is acting as a load with a -60 kW power draw. EVSE3 is unidirectional with the plugged-in EV. Discharging is not applicable since EVSE3 is unidirectional. The combination of plugged-in EV and EVSE3 has a power capacity of -240kW charging. The EV plugged-in at EVSE3 is currently charging at -120kW and charging is controllable. EVSE4 is available without a plugged-in EV.

[0122] In the illustrated example of FIG. 2A, another local power generation asset includes a unidirectional local generating resource (LGR) 113 for producing DC power that is regulated via a DC / DC converter 218 and then subsequently captured and stored in a fixed energy storage (FES) system 220. The FES system 220 provides a local power source to the facility 200 for delivering and receiving bidirectional power to and from the grid 101 via power lines (P0, P3) via an inverter 224 and the power distribution system 106. The FES system 220 includes a battery that is electrically connected to the FES control system. In the illustrated example, the LEMS 210 queries the LGR 113 and determines that the LGR 113 is generating 20 kW, which is fed to the FES system 220 and is not being used to power the local facility in this example. The LEMS 210 can query the FES system 220 and determine that the FES system 220 is at a state of charge (SOC) of 98%. The SOC enables the LEMS 220 to determine the dispatch and prioritization of the asset (i.e., the FES system 220) relative to other system components.

[0123] Other subcomponents that operate to support power generation in facility 200 include transformer 214, inverter 224, battery controller 222, DC / DC power converter 218, and sensing meters, including energy meter Em and frequency meter Fm. In the illustrated example, LEMS 210 queries the other subcomponents and determines that inverter 224 has a power capacity of 30 kW discharge and is in an idle state. LEMS 210 further determines that other loads in facility 200 are drawing power from grid 101 at -60 kW, which is not controllable.

[0124] Based on all the queries, the LEMS 210 can calculate that the flexibility capacity of the facility 200 is -210 kW charging (up) and 170 kW discharging (down). The flexibility capacity can provide a range of setpoints for the entire local mixed generation facility 200. The LEMS 210 can determine that the energy meter Em indicates a reading of -260 kW import drawn from the grid. This reading is consistent with the capacities described above, i.e., -20 kW on EVSE1, -60 kW on EVSE2, -120 kW on EVSE3, and the sum of other loads of -60 kW.

[0125] The LEMS 210 may receive a flexibility target of -180 kW charging (up) from the aggregator 115, in other words, receive -180 kW more from the grid. To meet the target, the LEMS 210 may dynamically adjust the operating parameters of the components in the facility 200 based on the query (i.e., sensed data). For example, the LEMS 210 may send the following command to the EVSE 3: -120 kW to -40 kW. After adjusting the operating parameters, the meter then reflects a new reading of -180 kW import (-260 + - (-80)), which is -80 kW less than the original -260 kW import from the grid, and thus, the flexibility target of -180 kW is met. Alternatively, the LEMS 210 may send different commands to adjust the operating parameters differently to meet the target, e.g., 30 kW discharge to the battery controller 222 and -70 kW charge to the EVSE 3. When there are different ways in which the LEMS 210 may adjust operating parameters to meet the goals, the prioritization is based on the need for movement, load shedding, and / or efficiency and response time. In some implementations, the need for movement may have the highest priority, followed by load shedding, then efficiency and response time. Other factors and / or orders for prioritization are also possible.

[0126] 2B, each local mixed power generation facility 200-1-200-n may include 1) a local energy management system (LEMS) 210 in communication with and under control of an aggregation platform 115 that intelligently manages and controls multiple grid services across one or more local mixed power generation facilities (200-1-200-n), and 2) multiple local power generation assets in communication with and under control of the LEMS 210. In one aspect, the LEMS 210 can relay information to the aggregation platform 115 to forecast, optimize, dispatch, monitor, and command grid services. In another aspect, the LEMS 210 can leverage storage from a combination of local power generation assets, which can be co-optimized locally at the local facility. The mix of these local power generation assets at each facility 200 includes: 1) multiple EVSEs (EVSE1...) located at public EVSE charging stations 111 for communicating power to and from the grid 101 via power lines (P0, P1, and P2) utilizing on-board storage devices (e.g., batteries) from electric vehicles 108 plugged into the EVSEs... n1) a first local power generation asset consisting of a unidirectional local generating resource (LGR) 113 for producing DC power that is regulated via a DC / DC converter 218 and then subsequently captured and stored in a fixed energy storage (FES) system 220. The FES system 220 provides a secondary local power source to the facility 200-1 for delivering and receiving bidirectional power to and from the grid 101 via power lines (P0, P3) via an inverter 224 and a power distribution system 106-1. In some implementations, the FES system 220 may include multiple energy storage devices (e.g., batteries, battery packs, capacitors, and other types of energy storage cells), all electrically connected to an FES control system. In this manner, collocated energy storage devices may be modularly added to the FES system without the need for redundant control equipment. In one aspect, the LEMS 210 may be physically located within the facility. In another aspect, the LEMS 210 may reside in a remote or cloud server management system that is off-site and physically separate from the local facility. Other subcomponents that operate to support power generation at the facility 200 include one or more transformers 214, one or more inverters 224, a battery controller 222, a power converter 218, and sensing meters (Em, Fm).

[0127] 3A-3C illustrate one implementation of multiple EVSEs 110 disposed in an EVSE charging station 111 for communicating power to and from a grid 101 via grid power lines (P0-P2). n3 illustrates a diagram of a first local asset consisting of a grid 101 and a battery 214. The first local asset may have various types of charging infrastructure for delivering and receiving power to and from the grid 101. For example, the charging infrastructure may include an EVSE with a unidirectional (one-way) EV charger as shown in FIG. 3A, a bidirectional (two-way) EV charger as shown in FIG. 3B, or a mixture of unidirectional and bidirectional EV chargers as shown in FIG. 3C. When an electric vehicle EV 108 is plugged into an EVSE equipped with a unidirectional EV charger, electricity flows in one direction from the grid 101 to the electric vehicle EV 108 via the transformer 214 to charge the battery in the electric vehicle 108. For an EVSE equipped with a bidirectional EV charger, electricity flows in two directions between the grid 101 and the electric vehicle EV 108 to either charge the battery or discharge power from the battery back to the grid 101 through the transformer 214. In FIG. 3C, an EVSE 1 at an EVSE charging station 111... n includes a combination of charging infrastructure that supports both unidirectional and bidirectional EV chargers. For example, a first set of EVSEs (EVSE1...3) in charging station 111 may have a bidirectional charger, enabling both charging and discharging capabilities for EV-connected vehicles, while a second set of EVSEs (EVSE4... n ) has a unidirectional charger that only enables the charging capability of an EV vehicle when plugged into a unidirectional charging station.

[0128] In operation, the LEMS 210 can query the EVSEs in the local facility 200 and dynamically adjust operating parameters based on the charging infrastructure and electric vehicles present in the local facility. For example, the LEMS 210 can query the EVSEs ... dynamically adjust operating parameters based on the charging infrastructure and the electric vehicles present in the local facility. nThe LEMS 210 may determine whether some EVSEs may be curtailed while other EVSEs may not be curtailed. The LEMS 210 may also handle some EVSEs with bidirectional EV charging capability and operate in a unidirectional mode based on the type of electric vehicle EV 108 connected to it. This includes some electric vehicles 108 that do not have on-board equipment to support bidirectional power flow and are therefore treated as unidirectional assets by the LEMS 210 from the EVSE perspective. In another case, the LEMS 210 determines EVSE set points for controlling the power flow of certain EVSEs with bidirectional EV chargers and operates them in either a bidirectional or unidirectional power flow mode for the purpose of meeting the power supply and load demands of the grid 101.

[0129] 4 illustrates a diagram of another local power generation asset comprising a local generation resource LGR 113 and an FES 220 according to one implementation. The local generation resource LGR 113 provides another local power source to the local facility 200, generating and supplying unidirectional power that is captured and stored within the FES system 220. Exemplary local generation resources LGR 113 include, but are not limited to, solar, wind, geothermal, and hydro-generated sources. The FES system 220 may include any type of energy storage device, such as batteries, battery packs, capacitors, and other types of energy storage cells, all electrically connected to an internal FES control system. The facility 200 may include other components for converting and conditioning the power generated by the LGR 113, such as a power converter 218, a battery controller 222, and an inverter 224. For example, battery controller 222 may receive commands from LEMS 210 via communication and control line C1 to control the charging and discharging modes of stationary battery 220, while inverter 224 is configured to convert and regulate (AC / DC or DC / AC) current flow to and from the stationary battery of FES system 220. In one implementation, battery controller 222 may receive commands from LEMS 210 to cause the stationary battery to receive power from grid 101 via inverter 224, thus acting as a load to implement a demand-based grid service, or provide power to grid 101 via power line P0, thus implementing a supply-based grid service. In another implementation, the local generation resource 113 is coupled to the FES system 220 via a power converter 218 and receives signals from the battery controller 222 or the LEMS 210 via communication and control lines (C2, C3), thereby converting the unregulated power produced by the LGR 113 into regulated DC power that is fed to and directly charges one or more stationary batteries of the FES system 220.

[0130] FIG. 5 illustrates a power topology in one of the local mixed generation facilities 200 for delivering and receiving power to and from the grid 101. The power topology example of FIG. 5 can incorporate any of the features of the other power topology examples disclosed herein, the differences being described with reference to FIG. 5. In this power topology, the LGR 113 is applied to the input side (input) of the transformer 214 via a DC / AC inverter 217 and is electrically coupled thereto to provide unidirectional AC power to both the transformer 214 and the stationary battery 220 (via an inverter 224). This unidirectional power supplying LGR 113 is controlled by the LEMS 210 to broker the power provided by the LGR 113 to the facility 200 according to a determined set point based on the power supply and demand requirements of the grid 101. Implementations of this power topology may be applied to and integrated into existing local generation facilities. Features of different power topology examples disclosed herein can be incorporated into another power topology example.

[0131] FIG. 6 illustrates a power topology in a local mixed power generation facility 200 for delivering and receiving power to and from the grid 101. The power topology example of FIG. 6 can incorporate any of the features of the other power topology examples disclosed herein, with the differences being described with reference to FIG. 6. In this implementation, the LGR 113 and power converter 219 are applied to the output side (output) of a transformer 214 with a direct connection to an EVSE, and can directly provide unidirectional DC power to the output side of the transformer 214 (or the input side of the EVSE) via the power converter 219. In other implementations, the local mixed power generation facility 200 may be configured to support multiple transformers and / or inverters operating within the local facility. In all power topologies described herein, the LEMS 210 is configured to receive input parameters from all local assets, including, for example, transformers, LGRs, inverters, batteries, etc., via a communication network that describes the topology and electrical connections of these local assets in order to effectively manage, control, and optimize each local asset according to set points and targets required from the facility 200. In one instance, for example, LEMS 210 may generate a dynamic query mechanism for transmitting a request signal to each local asset in facility 200 to request the configuration, layout, and / or electrical connection configuration for each local asset to determine and recognize the current configuration and available assets in the power topology of facility 200. The dynamic query mechanism may be generated by a combination of software, firmware, and hardware components contained within the system architecture of LEMS 210, as described in the following sections.

[0132] FIG. 7 illustrates a power topology in a local mixed generation facility 200 for delivering and receiving power to and from the grid 101. The power topology example of FIG. 7 can incorporate any of the features of the other power topology examples disclosed herein, the differences being described with reference to FIG. 7. In the above implementation, bidirectional power is configured to flow to and from the grid 101 via the power lines (P0, P3) through the inverter 224 and the power distribution system 106-1. In contrast to the previous implementation, a power line (P4) may be placed directly between the transformer 214 and the inverter 224, allowing bidirectional power to flow between the transformer 214 and the battery 220, thereby indirectly bypassing the power distribution system 106-1. Advantageously, the power topology is configured in a manner whereby the inverter 224 voltage does not need to match a grid voltage having a much higher voltage rating (e.g., 12 KVAC), which would also require a larger inverter voltage rating to match the grid voltage rating. However, in this implementation, a much lower inverter voltage rating (e.g., 480 VAC) is used when connected directly to the transformer 214 instead of the grid 101, allowing for a lower inverter rating, thereby reducing costs in expensive capital equipment.

[0133] 8 illustrates a block diagram of a local energy management system (LEMS) 210 operating in each local mixed power facility 200, according to one implementation. The LEMS 210 in each local facility (Facilities 1...n) consists of several subsystems for intelligently managing, optimizing, and controlling the local assets in the local mixed power facility 200 based on the power topology, facility configuration, available assets at the local facility, supply and load demand conditions between the local facility and the grid, operating conditions of the mixed local assets (e.g., EVSE and LGR 113) at any given time, and external demands between the aggregation platform 115 and the local mixed power facility 200. In one aspect, the LEMS 210 may include: 1) an input sub-block 210-1 having multiple input connections from internal and external sources; 2) a sensing sub-block 210-2 having real-time monitoring detectors for sensing current flow and voltages in various internal power sources (e.g., EVSE and LGR); 3) a data processing sub-block 210-3 having protocol adapters for analyzing and processing data received by the input and sensing blocks (210-1, 210-2); 4) an execution and control sub-block 210-4 for executing commands and generating one or more signals to control and optimize local assets (e.g., EVSE and LGR); and 5) an output sub-block 210-5 having multiple output ports for providing communication links and control paths between the LEMS 210, the internal power sources (e.g., EVSE and LGR), and the aggregation platform 115. In operation, LEMS 210 is configured at input sub-block 210-1 to receive and transmit data from and to local power assets (e.g., EVSE and LGR), including commands from aggregation platform 115. Additionally, LEMS 210 can receive and analyze data from metrology sensors (Em, Fm) via sensing sub-block 210-2.Based on data inputs received from local power assets and measurement sensors (Em, Fm), the LEMS 210 processes the received data via data processing sub-block 210-3, generates and executes control signals via control sub-block 210-4, and then transmits the control signals to adjacent power components via output sub-block 210-5, thereby optimizing and leveraging the local power storage generated by the mixed local assets (EVSE and LGR 113) to provide grid services to and from the grid 101. Advantageously, the LEMS 210 provides an intelligent local power management system at each local facility that effectively co-optimizes the local assets and leverages the local power storage generated by these assets to moderate grid-based services to and from the grid 101.

[0134] FIG. 9 illustrates an input sub-block 210-1 of the local energy management system (LEMS) 210 according to an implementation. The input sub-block 210-1 may comprise an input interface unit having multiple data communication links and channels for receiving input signals conveying input data from local assets and external systems available at the facility level. The input interface unit in the input sub-block 210-1 may be configured to receive analog signals, receive digital signals, receive analog signals and convert them to digital signals (or vice versa). The input data received at the input interface unit may be pre-conditioned, raw data. The input interface unit may convert the raw or input data (i1...i8) into an appropriate format and structured to be interpreted by the LEMS 210. Entity sources generating input data (i1...i8) to the LEMS 210 include, for example, EVSE, LGR 113, metering devices, etc., while other sources of input data are provided by external systems such as aggregation platform 115, third party data service providers, grid utility operators, distribution system operators (DSOs), building management systems, or other grid operating sources coupled to the facility 200. The types of input data received at the input sub-block 210-1 may include, but are not limited to, local profile data, status data, capacity data, controllability data, error data, information data, and measurement data of all local assets and external systems connected to the local facility 200. The data format of the input data may include, but is not limited to, data of different types of communication protocols such as TCP / IP, 802.11, MODBUS, IEC, CAN-BUS, USB, etc., based on the input device and system sending the data to the LEMS 210. Table 1.0 below provides a list of some exemplary input data received at the input sub-block 210-1.

[0135] [Table 1-1] [Table 1-2] [Table 1-3] [Table 1-4]

[0136] All input data received at input sub-block 210-1 is subsequently routed to data processing sub-block 210-3 for further evaluation, formatting, and processing by LEMS 210. Table 1.0 provides some examples of input data received by LEMS 210, but is not limited to those input data and may include other inputs based on future monitoring and control requirements of LEMS 210 and facility 200. Also note that the power capacity inputs, power transfers, and energy flow directions shown in Table 1.0 are not limited to active power and may also apply to reactive power. In one aspect, power capacity inputs may include, but are not limited to, charge and discharge, active power, reactive power, or any input device connected therein as it relates to power. Measurements of active power inputs are generally captured in KVA or VA or kilovolt-amperes, while reactive power measurements are captured in VAR, mVAR, or kVAR.

[0137] FIG. 10 illustrates the sensing sub-block 210-2 of the LEMS 210 having multiple sensing points (s1-s7) according to one implementation, while FIG. 11 illustrates the relative locations of these sensing points (s1-s9) in the local facility 200. The sensing sub-block 210-2 receives metering data from different sensing meters that are coupled to local assets and subsystems within its control area. In one aspect, the metering data reported by the sensing sub-block 210-2 effectively provides the LEMS 210 with additional situational awareness of the facility 200, including real-time feedback, electrical measurements, and status conditions of all local assets and subsystems captured and reported by the different sensing meters. These sensing meters may include, for example, frequency meters (Fm) and energy meters (Em), which may be applied to the sensing points (s1-s9) of the facility 200 as shown in FIG. 11. Additionally, the facility 200 includes multiple frequency meters (Fm1...Fm2) at sensing points (s1-s9) for sensing and measuring both frequency and energy data of local assets and subsystems at these points. n ) and energy meters (Em1...Em n ). Examples of electrical measurements captured and reported at the sensing points (s1-s9) include voltages at different phases (single-phase, three-phase), currents, and instantaneous power including, but not limited to, active power, reactive power, power capacity, power output, grid frequency, phase rotation, and power factor. In particular, power capacity includes both charging (up) and discharging (down) of the battery.

[0138] The sensing sub-block 210-2 may also receive metering data from other sensing devices such as vehicle or asset presence sensors located at the EVSE station 111, which may include, but are not limited to, vehicle sensor switches, cameras, PIR motion sensors, underground induction loops, radar, lasers, or air-filled rubber hoses that may detect if a vehicle has parked at the EVSE station 111. The sensing sub-block 210-2 may also receive weather data from local weather sensor devices, including temperature, wind speed, wind direction, precipitation, air pressure, and relative humidity at the local facility. The weather data may be captured by sensors physically present at the local level or provided by a third party or external weather data provider. In addition, the sensing sub-block 210-2 may receive date and time, sun angle, sunrise, sunset, and moon phase, and other environmental phase data to correlate the time series data with the power and energy data as determined by the LEMS 210. In one implementation, the different sensing meters may include stand-alone meters located along the communication path, the sensing path, or the power line between the local asset and the LEMS 210. In another implementation, each local asset may have an on-board sensing meter to directly capture and report its current status and internal readings to the LEMS 210. All metering data received in sub-block 210-2 is transmitted to data processing sub-block 210-3 for further processing and processed by orchestration executive control sub-block 210-4 to provide metering data of all local assets and external systems connected to the local facility 200. Additionally, orchestration executive control sub-block 210-4 may control the duration, frequency, and flow of metering data by the energy meters and may have an accuracy and refresh rate to understand how often readings are expected to be updated.

[0139] FIG. 12 illustrates the data processing sub-block 210-3 of the local energy management system (LEMS) 210 according to one implementation. In one aspect, the data processing sub-block 210-3 facilitates the conversion of all raw data (input data i1...i8 and metered data s1...s9) received by the LEMS 210, consolidating and converting the raw data into a structured format that is interpreted and processed by the orchestration execution control sub-block 210-4. For example, the facility 200 may have multiple input devices and sensing meters with different communication protocols (e.g., data formats, data packets, flow control, error handling, ACK, header information, etc.) that need to be interpreted by the LEMS 210. The data processing sub-block 210-3 may include one or more protocol adapters (Pa1...Pa2) as shown in FIG. 12. n ) to allow handling of different types of data formats and communication protocols. Examples of protocols handled and adapted by the data processing sub-block 210-3 include, but are not limited to, TCP / IP, 802.11, MODBUS, IEC, CAN-BUS, and USB. Once the data processing sub-block 210-3 converts the raw data into a common language for the orchestration execution and control sub-block 210-4, decision trees and algorithms are formulated and then executed by the LEMS 210 to create operational setpoints based on the processed input data, measurement data, and targets. Furthermore, the data processing sub-block 210-3 facilitates the conversion of these operational setpoints as determined by the orchestration execution and control sub-block 210-4 into the appropriate protocol having a formatted data structure that can be interpreted by the local power generation assets, subsystems, subcomponents, and devices in the local facility.

[0140] The protocol adapters described herein may be implemented through custom algorithms or programming code having procedures, functions, and routines for receiving, handling, converting, and communicating the specific protocols processed by data processing sub-block 210-3. A pseudocode example of a protocol adapter procedure is provided below in Table 2.0.

[0141] [Table 2-1] [Table 2-2]

[0142] 13 illustrates the orchestration execution and control sub-block 210-4 of the local energy management system (LEMS) 210 according to one implementation. The orchestration execution and control sub-block 210-4 comprises one or more microprocessors 210-4A for executing a set of instructions that generate, determine, and communicate operational setpoint commands to each local asset and sub-component, thereby controlling each local asset to meet goals in the local facility 200. Other microprocessor components for supporting data processing in the sub-block 210-4 and executing these instructions include, for example and without limitation, a microcontroller 210-4B, a read / write memory 210-4C, a control bus 210-4D, a data bus 210-4E, an I / O 210-4F, and an interface 210-4G, which facilitate the exchange of data with the other sub-blocks (input sub-block 210-1 and sensing sub-block 210-2) to provide setpoint commands for the LEMS 210. The setpoint commands can be based on real-time power constraints and local asset configurations (controllable / non-controllable, power capacity, SoC, etc.) received by LEMS 210 at input sub-block 210-1 and sensing sub-block 210-2. For example, orchestration executive control sub-block 210-4 of LEMS 210 may receive and analyze formatted input and measurement data from data processing sub-block 210-3, and based on goals for facility 200, orchestration executive control sub-block 210-4 formulates, determines, and then generates one or more setpoints and control signals that are subsequently communicated to the mix of local assets (EVSE, FES, LGR, FMS) and subcomponents to meet the goals of facility 200. In other embodiments, set points, instructions, commands, and goals of the systems described herein may be determined and executed by aggregation platform 115, which acts as a backup system to LEMS 210 and enables facility 200 to operate and control local assets instead of LEMS 210, thereby bypassing LEMS 210.

[0143] Energy or electrical targets received by LEMS210 at a local facility, facility subsystem, or facility subcomponent are defined herein as one or more desired energy or electrical targets, including, but not limited to, power factor, voltage, current, frequency, reactive / active power, energy, and / or phase angle, having a supply or demand requirement (e.g., charging or discharging) in response to grid conditions. In one case, the target may be initiated by an external entity, such as the aggregation platform 115 or an external system (third-party system), and then communicated to LEMS210 for further processing of the target. In another case, the target may be determined internally by LEMS210 based on conditions at the local facility as determined by input and sensed data. In response to the target received by LEMS210, operational set points are determined based on real-time power conditions and power configuration at the local facility, and subsequently communicated to local assets (EVSE, LGR) and subcomponents via data and control signals transmitted over communication and control lines. These set points are thus configured to dynamically and automatically adjust the operating states and power delivery settings of one or more of the local assets (EVSE, LGR) and subcomponents to meet the goals at the local facility. Exemplary operating states include, but are not limited to, enabling or disabling power, regulating or throttling charging or discharging power, or any other power settings, all within the limits of power capacity and availability of each local asset. In the case of an EVSE, these constraints may also include the mobility needs of the user. For example, one goal received by the LEMS 210 may include discharging 100 kW of power from the grid 101 to the local facility, while another goal may include delivering 200 kW of charge generated by the local facility to the grid 101.In either case, operational set points are developed by the LEMS 210 (or an external entity) according to their given targets (e.g., 100 kW discharge or 200 kW charge) and then communicated to the local assets and subcomponents to automatically adjust their operational states and power charge and discharge control settings based on these set points to meet these targets. Another target can include meeting power delivery requirements in relation to deviations in grid supply and demand conditions. Still other targets can include meeting target energy consumption or target power limits that should not be exceeded, meeting grid balance requirements as determined by the aggregation platform 115, and meeting power requirements for any grid services from the grid 101, such as voltage regulation demands or other metering data as measured by metering sensors (Em, Fm), and sending this metering data to the LEMS 210 to dynamically respond to certain power deviations in the grid 101. Additionally, the aggregation platform 115 may group operational setpoints into group functions and divide multiple targets into groups of setpoints and controls based on input data it receives from the grid 101, which are communicated to one or more local mixed power generation facilities (200-1, 200-2, ..., 200-n).

[0144] In another example, the aggregation platform 115 may have a goal for discharging 200 kW of power to the grid 101 at the local facility 200-1. In this example, there are multiple EVs at the EVSE station 111 charging at -300 kW while a surplus of 100 kW of solar power is being discharged by the battery generated by the LGR 113. In response to this goal, the LEMS 210 determines, generates, and communicates operational set points to the battery in the FES system 220 to enable it to discharge the battery at 500 kW based on the input and sensory data it receives from all the local assets (EVSE, battery, LGR, and FES system). At these operational set points, the goal is thereby achieved by leveraging and aggregating power from the mixed local assets (EVSE, LGR). In other cases, the aggregation platform 115 may implement energy management for billing savings and revenue generation purposes by monitoring and controlling all of the facilities (200-1, 200-2, ..., 200-n) and limiting the subsystems in each local facility to certain power thresholds so that they collectively do not exceed these thresholds. The ideal energy settings across all the local facilities (200-1, 200-2, ..., 200-n) may be calculated by one or more optimization algorithms implemented and executed by the aggregation platform 115, an external entity, or any other third party system.

[0145] In another case, the aggregation platform 115 may respond to frequency deviations at the local facility level by monitoring frequency in real time and generating and communicating frequency targets at the local facility. Based on the frequency targets and current input and metering data measured at the local facility, the LEMS 210 or aggregation platform 115 may determine, generate, and communicate operational set points to the local assets and dynamically adjust them to meet the frequency targets at the local facility. In calculating these operational set points, the LEMS 210 may consider various conditions at each local asset, such as different loads, battery capacity, charge state, the amount of energy available at the local facility by summing all energy devices, and whether those energy devices are controllable at any given time and, if so, the degree to which they are controllable. In addition, the LEMS 210 may consider other conditions at the local facility to make its calculations, including energy capacity conditions, such as power capacity to charge and power capacity to discharge.

[0146] Exemplary pseudocode for calculating and determining set points by the LEMS is provided below in Table 3.0.

[0147] [Table 3-1] [Table 3-2]

[0148] An example of the communication of set point commands to automatically control power settings on a targeted system to meet a goal is provided below in Table 4.0.

[0149] [Table 4-1] [Table 4-2] [Table 4-3]

[0150] All methods, functions, and procedures described herein may be implemented through one or more device-level, component-level, or system-level programming languages, including, but not limited to, C, C++, C#, Java, Python, ADA, assembly language, Verilog, VHDL, and the like. Additionally, while the foregoing goals are described in some detail with specific reference to various embodiments of LEMS 210 and aggregation server 115, it is not intended to limit LEMS 210 to these particular goals, implementations that determine these goals, or any specific alternatives thereof.

[0151] FIG. 14 illustrates an output sub-block 210-5 of a local energy management system (LEMS) 210 according to an implementation. The output sub-block 210-5 may comprise an output interface unit having multiple data communication links and channels for transmitting output signals carrying output data generated and communicated by the LEMS 210 to local assets, subcomponents, and external systems available at the facility level. The output interface unit may be configured to transmit analog signals, transmit digital signals, transmit analog signals and convert to digital signals (or vice versa), with the output data converted (via the data processing sub-block 210-3) into one or more protocol formats communicatively adapted and interpreted by the local assets, subcomponents, and external systems available at the facility level. In one aspect, the output data in the output sub-block 210-5 contains one or more operating setpoint commands for controlling and setting each local asset, including, for example, reduced commands or charge / discharge commands. In another aspect, the output data in output sub-block 210-5 may contain messaging information that provides system and asset information and device status information that is reported to the aggregation platform 115 or external systems.

[0152] In one embodiment, after the output sub-block 210-5 receives the setpoint commands from the orchestration execution control sub-block 210-4, the setpoint commands are then separated and routed to each local asset or external system via the communication and control link Lcc to dynamically configure and control local assets and sub-components (e.g., LGR, EVSE, battery controller, etc.) or to communicate messaging information to an external system (e.g., aggregation platform, third party system). n) in the output sub-block 210-5. For example, the output sub-block 210-5 may receive power and current setpoint commands from the orchestration executive control sub-block 210-4 at ports o3 and o4 and route these setpoint commands to the LGRs and EVSEs over the communication and control link Lcc to cause these assets to scale back, scale back, or reduce power generation based on the goals of the facility 200. In another embodiment, the output sub-block 210-5 may route the setpoint commands to the output ports o1...o4 in order to shed load. n In yet another embodiment, the LEMS 210 does not participate in the process of making energy calculations or determining operational set points, but acts only as a pass-through device. In this case, the aggregator platform 115 has full control to determine and generate all operational set points in the facility 200. Those operational set points are then relayed to the local assets in each local facility and may be on either the AC or DC side. The operational set points of the aggregator platform 115 may include power, current, or curtailment set points that are relayed to each local asset and bypass the LEMS 210. In other cases, the power may be active power, reactive power, or a combination of active and reactive power.

[0153] In another embodiment, the orchestration execution control sub-block 210-4 may need to generate and transmit status, energy capacity, control, and other messaging information from time to time to the aggregator platform 115 or other external entity to report the status and configuration settings of the local assets at the local facility. This messaging information may be transmitted from the orchestration execution control sub-block 210-4 to the aggregator platform 115 via output port o1 of the output sub-block 210-5. The messaging information may include facility status data that informs the aggregator platform 115 of the current conditions at the local facility 200 in real time, both at the aggregate level, facility level, and local asset level, and may provide the aggregator platform 115 with applicable visibility of the entire facility 200, including events at the local asset level, if needed. For example, the LEMS 210 may capture and record one or more EVs 108 with EV identification data (e.g., EV ID, arrival / departure time, charging capacity, charging mode i.e. unidirectional / bidirectional, etc.) at the EVSE station 111, charging at one or more EVSEs, and having dynamic and unpredictable arrival and departure times. This EV identification data may be routed from the LEMS 210 to the aggregator platform 115 via an aggregated output port (o1) contained within the output sub-block 210-5. Once received by the aggregator platform 115, accumulation of statistical data, performance data, and facility analysis correlation data can be gleaned from the EV identification data to further optimize the power generation produced at the local facility.

[0154] LEMS Facility Level Operational Example - Goals Set by the Aggregation Platform

[0155] A step-by-step operational overview of the LEMS 210 in one of the local facilities 200-1 is discussed in this section and in FIG. 2A. In one example, the LEMS 200 may communicate its power energy capacity to the aggregation platform 115 via energy capacity messaging data routed through an aggregation platform output port o1 located in a sub-block 210-5 of the LEMS 210. Based on this power energy capacity available in the local facility 200-1, the aggregation platform 115 may select the local facility 200-1 according to one or more goals for grid service. In response to the selection, the aggregation platform 115 generates and communicates a goal (or command) to the LEMS 210 in the local facility 200-1, instructing it to discharge 100 kW of power to the grid 101. Before the LEMS 210 receives any targets from the aggregation platform 115, it already knows the charging state, activity, controllability, charging capacity, and availability of any and all local assets (EVSE, LGR, inverters, transformers, etc.) in the local facility based on the input data and metering data received in the input sub-block 210-1 and the sensing sub-block 210-2, respectively. In other words, based on the input data and metering data in the sensing points (s1-s7) received and analyzed by the LEMS 210, it can determine exactly what each local asset is doing and whether these local assets and sub-components are controllable, and if so, the degree to which they can be controlled. Furthermore, the LEMS 210 can determine the current state in the local facility, including local asset availability, asset control status, asset configuration, power capacity, and energy flow state in each local asset.

[0156] After the LEMS 210 receives the target from the aggregation platform 115, it takes the input data and metering data and determines that additional power resources (e.g., one or more EVs 108) are available at the EVSE charging station 111 at time t0. From the input data received at time t0, the LEMS 210 also determines that EVSE1 is unidirectional, EVSEs 2, 3 are bidirectional, and EVSEs 4-n are empty. From the input data it receives from the input sub-block 210-1, the LEMS 210 determines that EVSE2 is bidirectional but not controllable and is discharging at 50 kW, EVSE1 is unidirectional, controllable, and charging at -10 kW, while EVSE3 is idle with no EVs present or connected. In addition, the LEMS 210 has also determined, based on the sensing data measured at the sensing points (s4, s5, s8) in the sensing sub-block 210-2, that there is 200 kW of power generation available from the LGR 113, the battery 220 is at 60% SOC, and the inverter 224 is capable of handling up to 1 MW of power. The LGR 113 provides power to the EVSE via the FES and the battery 220.

[0157] In this local facility, for example, a total load of -160kW is being consumed from one or more of its assets, including -10kW from EVSE1, -50kW from EVSE2, and -100kW reported by FMS 301 for buildings 1 and 2. When 200kW of power is discharged to FES 220 through inverter 224, generated by LGR 113, the power level seen on the energy meter (Em) is now the sum of -160kW and 200kW (or 40kW), which is available and injected into the grid. Since the aggregation platform 115 has a target of 100kW and 40kW is seen on the energy meter (Em), a total of 60kW discharge (100kW target - 40kW at Em) remains to meet the aggregation platform 115 target for grid services. To meet the remaining 60 kW target, LEMS 210 can analyze all input data and sensory data from the local assets and subcomponents at the local facility, determine which local assets are controllable and which are not, determine preferred operational set points for each local asset and subcomponent, and then communicate these set points to modify the operational settings of the local assets and subcomponents. In this example, EVSE2 is bidirectional and not controllable, EVSE1 is unidirectional, controllable, and charging at 10 kW, while EVSE3 is also bidirectional but idle (no vehicle present and not charging). Because EVSE1 is controllable, LEMS 210 can initiate a set point command to EVSE1 to reduce the 10 kW charge drawn by EVSE1 to 0 kW, providing an additional 10 kW at the local facility of the 60 kW requested by aggregation platform 115. Additionally, LEMS 210 may initiate commands to inverter 224 and battery 220 to increase its discharge by 50 kW (for a total of 250 kW discharge) to provide a total power delivery target requirement of 100 kW by aggregation platform 115 for grid services.

[0158] As shown in the above example, the local facility operates in a dynamic environment where electric vehicles EV are plugged into the EVSE station 111 at different times of the day with dynamic arrival and departure times at the local facility. In this dynamic environment, the LEMS 210 can continuously track in real time the current state and conditions at the local facility, the number and type of EVs plugged into the EVSE station 111, whether these EVs are controllable or non-controllable, the amount of energy capacity available from each EV at the EVSE station 111, and the charging and discharging conditions at the local facility. Based on the current state of the environment at the local facility, the LEMS 210 can control and make the necessary power adjustments via set points for each controllable local asset at the local facility to meet the goals defined by the aggregation platform for grid service demand.

[0159] System Power Capacity Limits - Continuous Monitoring

[0160] In some cases, local assets (EVSEs and LGRs) may have limited power supply or load capacity that may limit their ability to meet certain goals of the aggregation platform 115. For example, the aggregation platform 115 may send set points to the LEMS 210 at the local facility and request the LEMS 210 to update the operational settings of each local asset to meet the predetermined goals. However, based on the capacity limitations of the local assets at the local facility, the LEMS 210 reports to the aggregation platform 115 that the set point conditions cannot be applied to the local assets at the local facility due to the current power capacity constraints of one or more local assets (e.g., depleted or fully charged energy devices).

[0161] The LEMS 210 continuously monitors and queries the local assets via the input block 210-1 and the sensing sub-block 210-2, calculates the current power capacity at the local facility, updates the status information, and reports to the aggregation platform 115. The reporting of the status information to the aggregation platform 115 may be performed on a predefined schedule, at set time intervals, or in real time. By continuously monitoring the local facility, the LEMS 210 has real-time awareness and management over the controllable local assets and subcomponents and determines the appropriate set points to meet the power supply and / or demand requirements defined by the aggregation platform 115. For example, if the LGR 113-1 in the local facility 200-1 comprises a solar panel power generation system, the power provided by the LGR 113-1 is constantly changing due to weather conditions and other temporary obstructions (e.g., time of day, sun angle, clouds, aircraft, balloons, or other air traffic obstructions). Due to these potential obstructions, power generation from LGR 113-1 may immediately and temporarily decrease, reducing the power capacity for this local asset at the local facility. The reduction in power generation for this particular asset is immediately detected by LEMS 210-1, which reports the reduced power capacity at the local facility 210-1 to aggregation platform 115. In response, aggregation platform 115 can dynamically transmit and allocate the targets to other LEMS (210-2, 210-3, ..., 210-n) located at other facilities (200-2, 200-3, ..., 200-n) and automatically adjust the power settings to the targeted systems to meet the targets and satisfy the supply and load requirements for grid services.

[0162] Fault Handling Example - Loss of communication with one or more local assets

[0163] In some cases, failures and loss of communication between one or more local assets and the LEMS 210 may occur when the local assets are in an error state or are unreachable via the communication network. For certain failure conditions, the LEMS 210 can leverage the energy meter (Em) to estimate the power capacity from the local assets that cannot directly communicate with the LEMS 210. For example, in the case where the EVSE 4 and the LGR 113 are both operational but have lost communication with the LEMS 210, the power capacity from these local assets can be extrapolated by calculating the power difference measured between the remaining local assets (EVSE 1-3...n, FES systems) that are still in communication with the LEMS 210 and the energy meter (Em). In other words, the LEMS 210 can extrapolate the power capacity measurements of the EVSE 4 and the LGR 113 by subtracting the power capacity measured at the available energy meter (Em) from the cumulative power capacity at the other available local assets, even though it cannot directly control or communicate with the lost asset. Furthermore, the LEMS 210 can adjust the setpoints for all controllable local assets in the local plant and apply these extrapolated power capacity measurements for optimization across the local plant.

[0164] An exemplary method for implementing grid services with LEMS

[0165] 15 illustrates a method 1500 for implementing grid services by a mixture of LEMS 210 and local power generation assets to meet one or more goals in a local mixed generation facility. Method 1500 begins at step 1502 with receiving, by LEMS 210, one or more goals from an external entity, including but not limited to aggregation platform 115, an external third party, or an external system. As described herein above, the goals may generally define electrical targets (power factor, current, reactive / active power, etc.) of the local facility having power supply or demand requirements (e.g., charging or discharging) responsive to grid conditions. Examples of some goals are also described with respect to Table 4.0 presented earlier in this disclosure. It should be noted that while step 1500 refers to implementing a single LEMS at one of the local mixed generation facilities, method 1500 may further include multiple LEMS (210-1, 210-2, ... 210-n) as described above with respect to FIG. 1 operating at different local facilities (200-1, 200-2, ... 200-n) and implementing multiple grid services simultaneously or at different times according to goals received at each local facility.

[0166] Method 1500 proceeds to step 1504 of receiving incoming raw data by LEMS 210, including, but not limited to, 1) input data from local assets, subcomponents, and external entities, and 2) sensory data from metering devices operating within system 200 at the local facility. In general, the input data and sensory data can provide LEMS 210 with status, capability, and operational data from all local assets, subcomponents, and metering devices, which may be measured in real time or as historical data based on network and communication status, and provide LEMS 210 with operational awareness of all local power generation assets and devices located at the local facility. Examples of input data and sensory data discussed above are also described with respect to Table 1.0 and Figures 9-11. In addition, the input data may receive command and instruction data from external entities, such as aggregation platform 115, to which LEMS 210 may initiate an appropriate response, such as eliciting one or more commands to one or more local power generation assets under its reach and control. Additionally, the LEMS 210 may receive request data from external entities, including, but not limited to, system identification data, system configuration, system availability, system capability data, or system status updates, enabling the external entity (e.g., the aggregation platform 115) to determine commands that are appropriate for a given local facility 200 based on its configuration, availability, power capabilities, etc.

[0167] Method 1500 then proceeds to step 1506, in which LEMS 210 converts the incoming raw data into a structured format via one or more protocol adapters. In some embodiments, converting the incoming raw data is performed by data processing sub-block 210-3, which facilitates the conversion of all raw data received by LEMS 210 (input data i1...i8 and measurement data s1...s9) and consolidates and converts the raw data into a structured format that is interpreted and processed by orchestration executive control sub-block 210-4. In other embodiments, data processing sub-block 210-3 also facilitates the conversion of operational set points determined by orchestration executive control sub-block 210-4 into an appropriate protocol having a formatted data structure that can be interpreted by local power generation assets, subsystems, subcomponents, and devices at the local facility. Examples of data processing sub-block 210-3 and protocol adapters discussed in this section are also provided in Table 2.0 and FIG. 12 presented previously in this disclosure.

[0168] Method 1500 then proceeds to step 1508 of generating, by LEMS 210, one or more set points based on the one or more goals and the incoming raw data. As noted above, the generating step may generally include calculating and determining a set point command or a group of commands according to the one or more goals and the incoming raw data. Data processing and execution of these set point commands are handled by orchestration execution control sub-block 210-4 of LEMS 210. Implementations and examples of the orchestration execution control sub-block 210-4 and set point commands discussed in this section are also provided in Table 3.0 and FIG. 13 presented previously in this disclosure.

[0169] Method 1500 then proceeds to step 1510, where LEMS 210 communicates one or more set points to one or more local power generation assets, subcomponents, or devices. Once the set points are determined by orchestration execution control subblock 210-4, data processing subblock 210-3 may further facilitate conversion of these set points into an appropriate protocol having a formatted data structure that can be interpreted by the targeted systems (e.g., local power generation assets, subsystems, subcomponents, and devices) in the local facility. Once communicated, these set point commands may automatically adjust the operating power settings of each targeted system at one or more operating set points as determined by LEMS 210. Implementations and examples of communication of set points to targeted systems discussed in this section are also provided in Table 4.0 presented previously in this disclosure.

[0170] Method 1500 then proceeds to step 1512 of implementing one or more grid services to meet one or more goals with the mixture of local power generation assets. In response to automatically adjusting the operating power settings of each targeted system, the goals defined by the external entity may be achieved by leveraging and aggregating the charging and discharging of power from the mixture and combination of local power generation assets.

[0171] The method 1500 then proceeds to step 1514 of transferring power between the blend of local power generation assets and the power grid by the blend of local power generation assets, thereby satisfying one or more goals at the local mixed power generation facility.

[0172] In another embodiment, implementing grid services may include, but is not limited to, implementing energy management for billing savings and revenue generation purposes by monitoring and controlling all of the facilities (200-1, 200-2, ..., 200-n) and limiting the subsystems in each local facility to certain power thresholds so that they collectively do not exceed these thresholds. As noted above, a notable benefit of LEMS 210 is its ability to utilize loads, supplies, and power capacity from a mixture of local power generation assets, including, but not limited to, EVSE systems, LGR systems, FES systems, and facility management systems (FMS).

[0173] LEMS power topology scheme

[0174] 16-20 illustrate other possible power topologies in which the LEMS 210 may operate, manage, and control one or more groups of local power generation assets. Each power topology presented in the figures demonstrates various configurations of local power generation assets and LEMS that may operate at a given local facility. These power topologies may allow facility planners flexibility and several options to design and select an appropriate power configuration to meet local facility conditions and constraints, such as any facility regulations, ordinances, or other factors that may prevent the use of certain local power generation assets (e.g., EVSE, LGR systems, or FES systems) to be present at the local facility. Additionally, such power topologies and configurations are not intended to be limitations on the scope, design, number of local power generation assets and / or LEMS applied at each facility, or the interconnection, method, or application that facilitates power transfer and communication to and from the grid.

[0175] FIG. 16 depicts an EVSE local power topology at a local facility 1 (200-1) having multiple EVSE stations 111(1-N) in communication with and under the control of a LEMS 210. For example, at a local facility 1, the system 200 and LEMS 210 may leverage the use of a multi-EVSE system to supply and meet goals determined by the aggregation platform 115. Each EVSE station 111(1-N) may be assigned a fixed number of EVSEs (EVSE1... n ). The aggregation platform 115 associated with the LEMS 210 may identify the EVSE power topology and power delivery capabilities based on its configuration (i.e., a LEMS-only system) and enable coordinated targets to be communicated to the facility. For example, because a multi-EVSE system can support both supply and load demands, the aggregation platform 115 may transmit targets including a set of charging and discharging instructions to the LEMS 210, which in response generates and communicates set point commands to one or more EVSEs.

[0176] FIG. 17 depicts an LGR local power topology at a local facility 2 (200-2) having multiple LGR systems 113 in communication with and under the control of a LEMS 210. In a multi-LGR configuration, the system 200 and LEMS 210 may effectively manage and control multiple local generation resources (LGRs 113-1...113-N), including, but not limited to, a mixture and combination of solar, wind, geothermal, and hydro-generated sources. A LEM-LGR system may have a fixed number of LGRs based on space availability and zoning regulations at the local facility. An aggregation platform 115 associated with the LEMS 210 may identify the LGR power topology and power delivery capabilities based on its configuration (i.e., LGR-only system) and allow coordinated goals to be communicated to the facility. For example, because the LGR system may only support supply demand, the aggregation platform 115 may transmit a goal including a set of charging instructions to the LEMS 210, which in turn generates and transmits setpoint commands to one or more LGRs.

[0177] FIG. 18 depicts an FES local power topology at a local facility 3 (200-3) having multiple FES systems 220 in communication with and under the control of the LEMS 210. In a multi-FES configuration, the system 200 and the LEMS 210 may effectively manage and control multiple fixed energy storage systems (FES 220-1...220-N), including, but not limited to, a mixture and combination of fixed energy systems of various footprints, power capacities, and performance capabilities. The LEM-FES system may have a fixed number of FES based on space availability and zoning regulations at the local facility. The aggregation platform 115 associated with the LEMS 210 may identify the FES power topology and power delivery capabilities based on its configuration (i.e., FES-only system) and allow coordinated targets to be communicated to the facility. For example, as the FES system can support supply and load demands, the aggregation platform 115 may transmit targets including a set of charge and discharge instructions to the LEMS 210, which in response generates and delivers setpoint commands to one or more FESs (220-1...220-N).

[0178] FIG. 19 depicts a multiple mixed local power topology at local facility 4 (200-4) having multiple groups of various types of local power generation assets in communication with and under the control of LEMS 210. In a multiple mixed mode configuration, system 200 and LEMS 210 may effectively manage and control an array of EVSE, FES, and LGR, including, but not limited to, a mixture and combination of EVSE, FES, and LGR with various footprints, sizes, power capacities, and performance capabilities. A LEM-multiplex mixed mode system may have a fixed quantity of power generation assets based on space availability and zoning regulations at the local facility. The aggregation platform 115 associated with LEMS 210 may identify the LEM-multiplex mixed mode topology and power delivery capabilities based on its configuration (i.e., multiple mixed mode system) and enable custom goals to be communicated to the local facility. Additionally, because multiple mixed modes can support an infinite number of supply and load demands, the aggregation platform 115 may transmit targets including groups of charge and discharge commands to the LEMS 210, which in response generates and delivers setpoint commands or group functions of setpoint commands to each of one or more local power generation assets in the facility.

[0179] FIG. 20 depicts a distributed local asset (DLA) power topology controlled and managed by a LEMS 210. In a DLA power topology, a single LEMS 210 may control a group of local power generation assets spread across a local facility 5 (200-5). The local facility is not limited in size and may span across various distances, and the groups of local power generation assets may be separated by either a few feet or miles within the local facility. For example, some exemplary local facilities may include medium to large areas such as, but not limited to, university campuses, shopping and town centers, community centers, municipal agencies, government facilities, and the like. An aggregation platform 115 associated with the LEMS 210 may identify the DLA power topology and power delivery capabilities based on its configuration (i.e., DLA system) and enable custom objectives to be communicated to the local facility. Additionally, because the DLA power topology can support an infinite number of supply and load demands, the aggregation platform 115 may transmit targets including groups of charge and discharge commands to the LEMS 210, which in response generates and delivers setpoint commands or group functions of setpoint commands to one or more each of the local power generation assets in the facility.

[0180] FIG. 21 depicts a heterogeneous combination of LEMS power topologies in communication with the aggregation platform 115. In this embodiment, the aggregation platform 115 may generate target commands to the LEMS for each power topology, including, but not limited to, an EVSE local power topology, an LGR local power topology, an FES local power topology, a multiple mixed local power topology, and a distributed local asset (DLA) power topology. In another embodiment, a group of EVSEs in another local facility (200-6) may directly communicate with and be controlled by the aggregation platform 115. Each power topology in those individual facilities may support a myriad of supply and load demands from the grid 101. The aggregation platform 115 associated with each LEMS 210 may identify and obtain the type of power topology scheme and power delivery capabilities in each facility based on the data received at the input sub-block 210-1 of each LEMS 210. Based on the power topology scheme, the power supply and load capabilities in each power topology, an array of custom targets may be communicated by the aggregation platform 115 to each power topology. These targets may include groups of charge and discharge commands that are coordinated for each LEMS 210, which in response generates and delivers setpoint commands or group functions of setpoint commands to one or more each of the local power generation assets at the local facility level.

[0181] The foregoing power topologies presented herein provide examples of several possible internal configurations and layout schemes of the LEMS, local power generation assets, subcomponents, devices, and interconnections therein in one or more local mixed power generation facilities. However, such examples are not meant to be limiting in scope in terms of the number, size, capacity, geographic location, interconnections, or nature of the local assets, systems, subsystems, and / or devices operating in each facility. In addition, the power topologies described above may include other variations, combinations, and numbers of local assets (EVSE, FES, LGR). Furthermore, the LEMS may operate with other types of local power generation systems, including, but not limited to, facility management systems (FMS), thermal power generation systems, and fuel cell systems, regardless of size, location, or power capacity.

[0182] Dynamic and synergistic system and method for controlling combinations of local power topologies - Patents.com

[0183] In another embodiment, a dynamic and synergistic system and method for applying forward probability based learning performed by an external entity (e.g., aggregation platform 115) can control a combination of local power topologies with controllable local power generation assets (EVs, EVSEs, batteries, LGRs) at different facility locations and communicate real-time status information from one or more EVSEs to an external entity, whereby set points are determined and communicated to each EVSE at the local level to satisfy goals and grid service requirements.

[0184] According to the control authority governing each power topology, the external entity may apply and / or negotiate operational control of one or more EVSEs with the LEMS in each local facility. In some power topologies, the external entity may have full authority of the LEMS in some local facilities, allowing the external entity to have complete power management over the local assets in these local facilities. In other power topologies, the LEMS may be under the authority of another external party, through which the external entity must communicate set points to the local assets in these other facilities and negotiate control prior to adjusting power settings. In either case, once control of the local EVSE is established by the external entity, set points are communicated to the local EVSE to change its operating power state and satisfy one or more operating conditions related to the goals and grid service requirements. It is noted that the power topologies discussed above are applicable but are not limited to the power topologies presented in Figures 1, 2, 5-7, 16-21.

[0185] Overall, the power generation and storage capabilities and capacities in each power topology may vary over short time periods, and the power dynamics at the local facility level have variable states depending on the availability of EVs in the EVSE, the charging / discharging status of the EVs, the charging mode of the EVs (unidirectional or bidirectional), and the available power capacity of the EVs. Figures 22-23 depict examples of possible states within each local power topology. For example, Figure 22 illustrates a combination of local power topologies (200-1-200-6) in an initial state S0 at time T0, where the aggregation platform 115 may obtain all status information in real time from the EVs connected to the EVSE in each local facility, including, but not limited to, EV power capacity, EV availability, EV charging mode, etc. Based on the initial state S0, the aggregation platform 115 may forecast and predict the future power generation and storage capabilities in each local facility and generate an array of set point models that may be applied to the local power generation assets located in each local facility to meet the goals and grid service requirements. For example, in the initial state S0 shown in Figure 22, the aggregation platform 115 may communicate with each local power topology (200-1-200-6) to obtain real-time status information of the local power generation assets at each local facility. This embodiment is further illustrated in Table 4.0, which provides status information for each local asset (e.g., EV) obtained by the aggregation platform 115 in the initial state S0.

[0186] [Table 5-1] [Table 5-2]

[0187] Table 4.0 and FIG. 22 depict an example of status information obtained by the aggregation platform 115 at the initial state S0 from the local power topology, showing the facility identification number, power topology type, availability of EV assets (E1-E17), EV power capacity, and EV mode capability. From the status information at the initial state S0, the aggregation platform 115 can generate and apply set points (SP1-SP6) to one or more targeted systems (e.g., EVs) to adjust one or more power settings and / or power operating modes to satisfy one or more objectives (PO1-PO6) at each facility level (200-1-200-6) and to satisfy the objectives for the entire power topology. Additionally, the aggregation platform 115 can perform a myriad of calculations based on possible future states (S1, S2, ..., SN) to determine set points that produce the objectives at those future states.

[0188] FIG. 23 illustrates the combinations of local power topologies (200-1-200-6) in possible future state S1 at time T1, where T1>T0. In future state S1, many possible events may affect the power dynamics at each local facility, including, but not limited to, local asset (EV, EVSE) availability, EV power capacity, and EV mode capability. Table 5.0 depicts new events in some of the local facilities that affect the power dynamics in future state S1. For example, these events may include changes in local asset availability (EV3, EV5: available, EV16: unavailable), EV power capacity changes (EV6: -1kW, EV8: -3kW), and EV mode capability changes (EV1:UNI->BI, EV3:BI, EV8:BI->UNI).

[0189] [Table 6]

[0190] FIG. 24 illustrates the combination of local power topologies (200-1-200-6) in a possible future state S2 at time T2, where time T2>T1. In addition to changes due to individual local assets (e.g., EV1-EV17), system level changes in local facilities may occur that may increase or decrease the power dynamics of the entire power topology. For example, as shown in FIG. 24 and Table 6.0, power availability at local facility 1 (200-1) is no longer available and is available to the aggregation platform 115 for grid services.

[0191] [Table 7]

[0192] It should be noted that the states S0-S2 disclosed above present only a few examples of the myriad of states that affect the power dynamics in each local power topology and the entire power topology as a whole. Based on the initial state S0 and the dynamic prediction models and methods, the aggregation platform 115 can take into account the myriad of power dynamics to determine targets for the local power topologies in future states.

[0193] 25 depicts a schematic diagram of multiple states starting at an initial state S0 whereby the aggregation platform 115 may dynamically predict, determine, and calculate set points to meet energy or electricity objectives, including, but not limited to, objectives based on grid-wide level conditions, local level conditions, best mix of EVSEs, maximum revenue generation, different planning horizons, and / or other grid service requirements. In addition, future states S1, S2, ...SN generally depend on the power setting changes made by the aggregation platform 115 in previous states and any events affecting changes in power dynamics at each local facility. Furthermore, the aggregation platform 115 may implement and perform forward probability-based learning and perform permutations of future states to calculate set points to achieve one or more desired grid service objectives.

[0194] Some LEMS advantages

[0195] An advantage of LEMS210 is its intelligent awareness and ability to facilitate energy management at the local facility level by controlling and leveraging a mixture of local assets (EVSE and LGR) deployed at the local facility and combining the mixture of generated power from each facility acting as its own virtual power plant to deliver grid services to grid 101. In addition, LEMS210 has the ability to effectively handle and fulfill grid service goals, including regulation or demand response goals from grid 101, by communicating operational set points that control power charging and discharging at each local asset to meet those goals. In another advantage, LEMS210 has the ability to calculate set points to the power capacity needed in real time at the local facility based on the input data and sensory data it receives from the local assets and subcomponents. In addition, goals for grid services may be measured before or after the sensing meter, providing LEMS210 with multiple targets to develop, generate, and then communicate operational set points to the local assets in response to those goals. Additionally, LEMS 210 can coordinate local assets that are controllable and, in some cases, obtain input data from local assets that are not controllable, and make decisions and generate set points that affect local assets (both controllable and non-controllable) to meet goals at the local facility 200. Grid services can be affected by loads on the grid resulting from power consumed by residential dwellings, commercial buildings, and industrial facilities, or excess power on the grid resulting from power provided by solar power, wind power, or other generating sources, thereby determining goals on a per facility basis. Overall, LEMS 210 can facilitate energy management at the local facility level for the purposes of billing savings and revenue generation at each local facility (200-1-200-n) to effectively meet the dynamic nature and goals of grid services in response to loads and excess demands on the grid 101. Additional Considerations

[0196] The foregoing description is provided to enable any person skilled in the art to practice various implementations described herein. The embodiments discussed herein are not limitations of the scope, applicability, or implementations described in the claims. Various modifications of these implementations will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other implementations. For example, changes may be made in the functions and arrangements of elements discussed without departing from the scope of the disclosure. Various embodiments may omit, substitute, or add various procedures or components, as appropriate. For example, the methods described may be performed in different orders than those described, and various steps may be added, omitted, or combined. Also, features described with respect to some embodiments may be combined in some other embodiments. For example, an apparatus may be implemented, or a method may be practiced, using any number of aspects described herein. In addition, the scope of the disclosure is intended to cover such apparatus or methods practiced using other structure, functionality, or structure and functionality in addition to or other than the various aspects of the disclosure described herein. It should be understood that any aspect of the disclosure disclosed herein may be embodied by one or more elements of a claim.

[0197] As used herein, the word "exemplary" means "serving as an example, instance, or illustration." Any aspect described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects.

[0198] As used herein, phrases referring to "at least one of" a list of items refer to any combination of those items, including single members. By way of example, "at least one of a, b, or c" is intended to cover a, b, c, ab, ac, bc, and abc, and any combination with multiples of the same element (e.g., aa, aaa, aab, aac, abb, acc, bb, bbb, bbc, cc, and ccc, or any other permutation of a, b, and c).

[0199] As used herein, the term "determining" encompasses a wide variety of actions. For example, "determining" may include calculating, computing, processing, deriving, investigating, looking up (e.g., looking up in a table, database, or another data structure), ascertaining, and the like. "Determining" may also include receiving (e.g., receiving information), accessing (e.g., accessing data in a memory), and the like. "Determining" may also include resolving, selecting, choosing, establishing, and the like.

[0200] The methods disclosed herein include one or more steps or actions for achieving the method. Method steps and / or actions may be interchanged with one another without departing from the scope of the claims. In other words, unless a specific order of steps or actions is specified, the order and / or use of specific steps and / or actions may be modified without departing from the scope of the claims. Furthermore, various operations of the methods described above may be performed by any suitable means capable of performing the corresponding functions. The means may include various hardware and / or software components and / or modules, including, but not limited to, circuits, application specific integrated circuits (ASICs), or processors. Generally, where operations illustrated in a figure exist, those operations may have corresponding counterparts of means+function components with similar numbering.

[0201] The following claims are not intended to be limited to the implementations set forth herein, but are to be accorded full scope consistent with the claim language. Within the claims, reference to an element in the singular is not intended to mean "one and only," unless specifically so recited, but rather, "one or more." The term "several" refers to one or more, unless specifically recited otherwise. No claim element is to be construed under the provisions of 35 USC §112(f) unless the element is expressly recited using the phrase "means for," or, in the case of a method claim, the element is recited using the phrase "step for." All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later become known to those of skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Also, nothing disclosed herein is intended to be made available to the public, whether or not such disclosure is expressly recited in the claims.

Claims

1. It is a method, An external entity, a mixture of local power generation assets in a local facility, and a local energy management system (LEMS) communicatively coupled to the power grid, receive one or more energy or electrical targets from the external entity, wherein the mixture of local power generation assets is electrically coupled to the power grid. The LEMS receives incoming raw data from the mixture of power generation assets, The LEMS generates one or more setpoints according to the one or more energy or electrical targets and the incoming raw data, The LEMS transmits the one or more setpoints to the mixture of local power generation assets, The mixture of local power generation assets provides one or more grid services by satisfying one or more energy or electricity targets, The mixture of local power generation assets transfers power between the mixture of local power generation assets and the power grid. Methods that include...

2. The method according to claim 1, further comprising the LEMS converting the incoming raw data into a structured protocol format via one or more protocol adapters.

3. The method according to claim 1, wherein the incoming raw data comprises a plurality of input data and sensing data.

4. The method according to claim 1, wherein the external entity comprises an aggregation platform, a frequency meter, an energy meter, or a third-party system.

5. The method according to claim 1, wherein the mixture of local power generation assets comprises a combination of electric vehicle station equipment (EVSE), a fixed energy storage system (FES), and / or locally generated resources (LGR).

6. The method according to claim 5, wherein each LGR comprises a solar, wind, and / or hydroelectric power generation system.

7. The method according to claim 5, wherein each stationary energy storage system comprises a battery, a battery pack, a capacitor, and / or an energy storage cell.

8. The method according to claim 1, further comprising the LEMS converting the one or more setpoints into one or more structured protocol formats, the one or more structured protocol formats being adapted to be interpreted by one or more devices in the mixture of local power generation assets.

9. The method according to claim 1, further comprising automatically adjusting one or more operating power settings of the targeting system according to one or more setpoints received by the targeting system, wherein the targeting system is a component of the mixture of local power generation assets.

10. The method according to claim 9, wherein the one or more operating power settings are configured to control voltage, frequency, and current on the targeting system.

11. The method according to claim 1, wherein the external entity communicates with a plurality of local energy management systems located in different local facilities, and each local energy management system is configured to be communicably coupled to a corresponding mixture of local power generation assets having a configured power topology.

12. It is a system, A local facility comprises a mixture of local power generation assets, a power grid, and a local energy management system (LEMS) electrically coupled to an external entity. The aforementioned LEMS is Receiving one or more energy or electrical targets from the aforementioned external entity, Receiving incoming raw data from the mixture of the aforementioned power generation assets, To generate one or more setpoints according to the one or more energy or electrical targets and the incoming raw data, Transmitting the one or more set points to the mixture of local power generation assets It is configured to do the following: The mixture of the aforementioned local power generation assets is To implement one or more grid services in order to meet one or more of the aforementioned energy or electricity targets, Transferring power between the mixture of local power generation assets and the power grid A system configured to perform the following actions.

13. The system according to claim 12, wherein the LEMS is further configured to convert the incoming raw data into a structured protocol format via one or more protocol adapters.

14. The system according to claim 12, wherein the incoming raw data comprises a plurality of input data and sensing data.

15. The system according to claim 12, wherein the external entity comprises an aggregation platform, a frequency meter, an energy meter, or a third-party system.

16. The system according to claim 12, wherein the mixture of local power generation assets comprises a combination of electric vehicle station equipment (EVSE), a fixed energy storage system (FES), and / or locally generated resources (LGR).

17. The system according to claim 16, wherein each LGR comprises a solar, wind, and / or hydroelectric power generation system.

18. The system according to claim 16, wherein each fixed energy storage system comprises a battery, a battery pack, a capacitor, and / or an energy storage cell.

19. The system according to claim 12, wherein the LEMS is configured to convert the one or more setpoints into one or more structured protocol formats, and the one or more structured protocol formats are adapted to be interpreted by one or more devices in the mixture of local power generation assets.

20. The system according to claim 12, wherein the LEMS is configured to automatically adjust one or more operating power settings of the targeting system according to one or more setpoints received by the targeting system, and the targeting system is a component of the mixture of local power generation assets.

21. The system according to claim 20, wherein the one or more operating power settings are configured to control voltage, frequency, and current on the targeting system.

22. The system according to claim 12, wherein the external entity communicates with a plurality of local energy management systems located in different local facilities, and each local energy management system is configured to be electrically coupled to a corresponding mixture of local power generation assets having a predetermined power topology.

23. A local energy management system electrically coupled to a power grid, a plurality of local power generation assets in a local facility, and an external entity, wherein the plurality of local power generation assets are electrically coupled to the power grid, and the system is Multiple sensors configured to monitor the multiple local power generation assets and output raw sensor data for the multiple local power generation assets, One or more inputs configured to receive at least one energy or electrical target from the external entity, A control system, wherein the control system is Receiving the aforementioned raw sensor data, Receiving one or more of the aforementioned energy or electrical targets, Based on the one or more energy or electricity targets and the raw sensor data, generate one or more operating parameter setpoints for the multiple power generation assets, The one or more operating parameter setting points are output to the plurality of local power generation assets, wherein the one or more operating parameter settings of the plurality of local power generation assets are configured to be adjusted according to the one or more operating parameter setting points in order to satisfy the one or more energy or electrical targets. A control system configured to perform the following actions A system that includes these features.

24. The system according to claim 23, wherein the control system is further configured to convert the raw sensor data into a structured protocol format via one or more protocol adapters.

25. The system according to claim 23 or 24, wherein the one or more inputs are further configured to receive raw input data, and the controller is configured to generate the one or more operating parameter setpoints based on the raw input data.

26. The system according to claim 23 or 24, wherein the external entity comprises an aggregation platform, a frequency meter, an energy meter, or a third-party system.

27. The system according to claim 23 or 24, wherein the plurality of local power generation assets comprises one or more of the following: electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or locally generated resources (LGR).

28. The system according to claim 27, wherein the LGR comprises a solar, wind, and / or hydroelectric power generation system.

29. The system according to claim 27, wherein the fixed energy storage system comprises a battery, a battery pack, a capacitor, and / or an energy storage cell.

30. The system according to claim 23 or 24, further configured to convert the one or more operating parameter setpoints into one or more structured protocol formats, the one or more structured protocol formats being configured to be interpreted by one or more devices in the plurality of local power generation assets.

31. The system according to claim 23 or 24, further configured to automatically adjust the operating parameter settings of one or more target components of the plurality of local power generation assets according to the one or more setpoints received by the target components.

32. The system according to claim 31, wherein the one or more operating parameter settings are configured to control voltage, frequency, and / or current on the target component.

33. The system according to claim 23 or 24, wherein, under the adjusted settings of one or more operating parameters, the plurality of local power generation assets are configured to transfer power between the plurality of local power generation assets and the power grid.

34. The system according to claim 23 or 24, wherein the external entity further communicates with a plurality of other local energy management systems located in other different local facilities, each of which is configured to be electrically coupled to a plurality of corresponding local power generation assets having a predetermined power topology.

35. A method for intelligent energy management in a local facility using an external entity, multiple local power generation assets in the local facility, and a local energy management system (LEMS) that is communicatively coupled to the power grid, wherein the multiple local power generation assets are electrically coupled to the power grid, and the method Using the LEMS control system, The LEMS receives raw sensor data for the multiple local power generation assets from multiple sensors, The LEMS receives at least one or more energy or electrical targets from the external entity through one or more inputs, Based on the one or more energy or electrical targets and the raw sensor data, generate one or more operating parameter setpoints for the plurality of local power generation assets, The one or more operating parameter setting points are output to the plurality of local power generation assets, wherein the one or more operating parameter settings of the plurality of local power generation assets are configured to be adjusted according to the one or more operating parameter setting points in order to satisfy the one or more energy or electrical targets. Methods that include...

36. The method according to claim 35, further comprising converting the raw sensor data into a structured protocol format via one or more protocol adapters.

37. The method according to claim 35 or 36, wherein the one or more inputs are further configured to receive raw input data, and the one or more operating parameter setpoints are further generated based on the raw input data.

38. The method according to claim 35 or 36, wherein the external entity comprises an aggregation platform, a frequency meter, an energy meter, or a third-party system.

39. The method according to claim 35 or 36, wherein the plurality of local power generation assets comprises one or more of the following: electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or locally generated resources (LGR).

40. The method according to claim 39, wherein the LGR comprises a solar, wind, and / or hydroelectric power generation system.

41. The method according to claim 39, wherein the fixed energy storage system comprises a battery, a battery pack, a capacitor, and / or an energy storage cell.

42. The method according to claim 35 or 36, further comprising converting the one or more operational parameter setting points into one or more structured protocol formats, wherein the one or more structured protocol formats are configured to be interpreted by one or more devices in the plurality of local power generation assets.

43. The method according to claim 35 or 36, further comprising automatically adjusting the operating parameter settings of one or more target components of the plurality of local power generation assets according to the one or more setpoints received by the target component.

44. The method according to claim 43, wherein the one or more operating parameter settings are configured to control voltage, frequency, and / or current on the target component.

45. The method according to claim 35 or 36, wherein, under the adjusted settings of one or more operating parameters, the plurality of local power generation assets are configured to transfer power between the plurality of local power generation assets and the power grid.

46. The method according to claim 35 or 36, wherein the external entity further communicates with a plurality of other local energy management systems located in other different local facilities, each of which is configured to be electrically coupled to a plurality of corresponding local power generation assets having a predetermined power topology.

47. A method for intelligently managing and controlling grid services across one or more local power generation facilities, wherein the method is: Control of an electronically integrated platform that telecommunicates with multiple local power generation assets at a local facility, wherein the multiple local power generation assets are electrically coupled to the power grid and under control. Receiving raw data for the aforementioned multiple local power generation assets in their current state, Calculating one or more energy or electrical targets for the local facility based at least partially on the raw data in the current state, Based on the one or more energy or electricity targets and the raw data, generate one or more operating parameter setting points for the plurality of local power generation assets, The one or more operating parameter setting points are output to the plurality of local power generation assets, wherein the one or more operating parameter settings of the plurality of local power generation assets are configured to be adjusted according to the one or more operating parameter setting points in order to satisfy the one or more energy or electrical targets. Methods that include...

48. The method according to claim 47, further comprising converting the raw data into a structured protocol format via one or more protocol adapters.

49. The method according to claim 47 or 48, wherein the plurality of local power generation assets comprises one or more of the following: electric vehicle station equipment (EVSE), fixed energy storage systems (FES), and / or locally generated resources (LGR).

50. The method according to claim 49, wherein the LGR comprises a solar, wind, and / or hydroelectric power generation system.

51. The method according to claim 49, wherein the fixed energy storage system comprises a battery, a battery pack, a capacitor, and / or an energy storage cell.

52. The method according to claim 47 or 48, further comprising converting the one or more operational parameter setting points into one or more structured protocol formats, wherein the one or more structured protocol formats are configured to be interpreted by one or more devices in the plurality of local power generation assets.

53. The method according to claim 47 or 48, further comprising automatically adjusting the operating parameter settings of one or more target components of the plurality of local power generation assets according to the one or more setpoints received by the target component.

54. The method according to claim 53, wherein the one or more operating parameter settings are configured to control voltage, frequency, and / or current on the target component.

55. The method according to claim 47 or 48, wherein, under the adjusted settings of one or more operating parameters, the plurality of local power generation assets are configured to transfer power between the plurality of local power generation assets and the power grid.

56. The method according to claim 47 or 48, wherein the electronically integrated platform further communicates with a local energy management system (LEMS), and the generation and output of one or more operating parameter setpoints is performed by the control system of the LEMS under the control of the electronically integrated platform.

57. The method according to claim 56, wherein the LEMS is physically present in the local facility.

58. The method according to claim 56, wherein the LEMS is located off-site in a remote server that is physically separated from the local facility.

59. The method according to claim 56, wherein the electronically integrated platform further telecommunicates with a plurality of other local energy management systems located in other different local facilities, and each of the other local energy management systems is configured to be electrically coupled to a plurality of corresponding local power generation assets having a predetermined power topology.

60. The method according to claim 47 or 48, further comprising determining one or more energy or electrical targets for the local facility in one or more future states.

61. The method of claim 60, further comprising calculating one or more operating parameter setpoints for the local facility in one or more future states, based at least in part on the one or more energy or electrical targets for the local facility in one or more future states.

62. The method according to claim 60, further comprising predicting changes in the local facility in one or more future states based on the raw data in the current state and a dynamic prediction model.

63. The method according to claim 62, wherein the changes in the local facility in one or more future states include changes resulting from the plurality of local power generation assets.

64. The method according to claim 62, wherein the changes in the local facility in the one or more future states include system-level changes in the local facility.

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