SCALABLE EDGE HARDWARE SYSTEM FOR DISTRIBUTED ENERGY RESOURCES

Certain aspects of the present disclosure provide techniques for providing edge hardware system for distributed energy resources. One embodiment of a system includes a core device that is deployed in an edge environment of a site, the core device causing the edge hardware system to communicate with a cloud environment to acquire current optimization and load management set points for a charging station, dispatch the current optimization and load management set points through a local communications protocol via a local network to the charging station, and receive data from the charging station through the local network. In some embodiments, the core device causes the hardware system to communicate the data to the cloud environment via a wide area network and control charge and discharge parameters of an energy asset at the charging station using energy-related inputs.

INTRODUCTION

Aspects of the present disclosure relate to a scalable edge hardware system for distributed energy resources.

Electric vehicles (EVs), including plug-in hybrid and fully electric vehicles, are increasing in popularity around the world. It is expected that the proportion of new EVs sold each year out of the total number of vehicles sold will continue to rise for the foreseeable future. Moreover, while EV operators are primarily non-commercial (e.g., personal vehicles), commercial vehicle operators are increasingly adding EVs to their fleets for all sorts of commercial operations, thus adding to the number of EVs in operation throughout the world.

The shift from internal combustion engine (ICE)-powered vehicles to EVs requires significant supporting infrastructure anywhere EVs are operated. For example, electric vehicle charging stations, sometimes referred to as electric vehicle supply equipment (EVSE), need to be widely distributed so that operators of EVs are able to traverse the existing roadways without issue.

Charging electric vehicles is different from refueling ICE vehicles in many ways. For example, an ICE vehicle simply purchases fuel at a set price. Charging an EV, by contrast, can be complicated in that the actual monetary charge incurred to charge the EV may depend on highly flexible and quickly changing parameters, such as the price of electricity, demand, time of day, charge rate, etc. Other factors may relate to the type of user and/or vehicle being charged. As such, it can be difficult for a charging station to properly charge each vehicle, especially, as the system for managing multiple charging stations grows.

Accordingly, there is a need for a scalable edge hardware system for distributed energy resources.

SUMMARY

Certain aspects of the present disclosure provide techniques for providing edge hardware system for distributed energy resources. One embodiment of a system includes a core device that is deployed in an edge environment of a site, the core device causing the edge hardware system to communicate with a cloud environment to acquire current optimization and load management set points for a charging station, dispatch the current optimization and load management set points through a local communications protocol via a local network to the charging station, and receive data from the charging station through the local network. In some embodiments, the core device causes the hardware system to communicate the data to the cloud environment via a wide area network and control charge and discharge parameters of an energy asset at the charging station using energy-related inputs.

Embodiments of a method include communicating, by a core device, with a cloud environment to acquire current optimization and load management set points for a charging station, dispatching, by the core device, the current optimization and load management set points through a local communications protocol via a local network to the charging station, and receiving, by the core device, data from the charging station through the local network. In some embodiments, the method includes communicating, by the core device, the data to the cloud environment via a wide area network and controlling, by the core device, charge and discharge parameters of an energy asset at the charging station using energy-related inputs, which include at least one of the following: real-time weather data, historical weather data, weather forecast data, tariff data, historical asset energy interval data, forecasted asset energy interval data, real-time asset energy usage data, system constraint data, user preference data, and market-based strategy data.

Embodiments of a non-transitory computer-readable medium include logic that, when executed by a computing device, causes the computing device to communicate with a cloud environment to acquire current optimization and load management set points for a charging station, dispatch the current optimization and load management set points through a local communications protocol via a local network to the charging station, and receive data from the charging station through the local network. In some embodiments, the logic causes the computing device to communicate the data to the cloud environment via a wide area network and control charge and discharge parameters of an energy asset at the charging station using energy-related inputs, which include at least one of the following: real-time weather data, historical weather data, weather forecast data, tariff data, historical asset energy interval data, forecasted asset energy interval data, real-time asset energy usage data, system constraint data, user preference data, and market-based strategy data.

Other embodiments provide processing systems configured to perform the aforementioned methods as well as those described herein; non-transitory, computer-readable media comprising instructions that, when executed by a processors of a processing system, cause the processing system to perform the aforementioned methods as well as those described herein; a computer program product embodied on a computer readable storage medium comprising code for performing the aforementioned methods as well as those further described herein; and a processing system comprising means for performing the aforementioned methods as well as those further described herein.

DETAILED DESCRIPTION

Embodiments disclosed herein include systems and methods for providing an edge hardware platform. Some embodiments are configured to forecast, optimize, and control battery charge/discharge parameters using available energy and energy-related inputs, such as, but not limited to, real-time weather data, historical weather data, weather forecast data, tariff data, historical asset energy interval data, forecasted asset energy interval data, real-time asset energy usage data, system constraint data, user (driver, facility manager, etc.) preference data, market-based strategy data, and/or other information. These embodiments may utilize edge-based computing devices, such as a core device, a remote communications device, and/or a sense device that facilitates communication with a charging station, energy asset, and/or cloud environment. With these devices, embodiments provided herein may be configured to control charge and discharge parameters of an energy asset at the charging station using energy-related inputs. The systems and methods for providing an edge hardware platform incorporating the same will be described in more detail, below.

Example Computing Environment for Providing an Edge Hardware Platform

Referring now to the drawings,FIG.1depicts a computing environment for providing an edge hardware platform according to embodiments provided herein. As illustrated, the computing environment includes a network100that is coupled to an edge environment102, a cloud environment104, a software repository106, as well as ancillary devices108. The network100may be configured as any wide area network (WAN, such as the internet, power network, cellular network, etc.) or other network for facilitating communication among the edge environment102, the cloud environment104, the software repository106and ancillary devices108.

Edge environment102may generally be deployed at site110to provide various services, including coordination and optimization of energy assets114, such as charging of electric vehicles (e.g., EV114a) using charging station112and various distributed energy sources (DERs), such as solar installation114b, batter energy storage system (BESS)114c, utility grid connection114d, and generator114e(e.g., an onsite diesel, natural gas, or other type of fueled generator). Generally, the aforementioned DERs may provide energy to the charging station112and/or use energy from the charging station112(e.g., by way of a backflow of energy from EV114ato other aspects of site110). In some embodiments, charging station112may send excess energy back to the battery114cand/or to utility114d. Generally, edge environment102may monitor and/or modify the energy sent to and received from the DERs to optimize various tasks, such as charging of EV114.

Charging station112may utilize various communication protocols, such as open smart charging protocol (OSCP), open charge point interface (OCPI), ISO 15118, OpenADR, etc. and may represent Level 1, Level 2, Level 3, and higher level charging stations, as applicable. Generally, the “level” of a charging station refers to the power level and/or ability to provide electric power to a device being charged.

Edge environment102is configured as an interface between various aspects of site110and network100. In various embodiments, compute resources for performing different functions at a site, such as optimization of EV charging, may be split between local compute resources in edge environment102and remote compute resources, e.g., in cloud environment104ofFIG.1.

Cloud environment104is coupled to the edge environment102via the network100and may be configured for further processing of data, as described herein. WhileFIG.1depicts a single cloud environment104that serves a single edge environment102, this is merely an example, as some embodiments may be configured such that the cloud environment104may serve a plurality of edge environments102that each serve one or more sites110, one or more charging stations112, one or more DERs, and the like.

Software repository106is also coupled to site110via network100. Software repository106may be configured as a platform to program, store, manage, control changes, etc. to software that is implemented in edge environment102and/or cloud environment104. In some embodiments, software repository106may be configured as a proprietary service and/or may be provided by a third-party, such as GitHub™. Additionally, some embodiments may be configured such that the software repository106is provided by the same entity that manages the cloud environment104. As such, these embodiments may be configured such that software repository106and cloud environment104may be combined.

Also depicted inFIG.1are the ancillary devices108. The ancillary devices108may include an operations device108a, an analysis device108b, a mobile device108c, a kiosk108d, and/or other devices. Specifically, the operations device108amay be utilized to monitor and/or alter operations of the environment provided inFIG.1. The analysis device108bmay analyze utilization, operation, charging, and/or other features of the computing environment. The mobile device108cmay represent an administrator device and/or a user device. As a user device, the mobile device108cmay initiate charging, payment, and/or perform other user-specific actions. As an administrator device, the mobile device108cmay perform administrative operations, analysis, and/or perform other actions. The kiosk108dmay be located at one of the charging stations112and/or remote therefrom and may provide user-specific or administrative actions, similar to that of the mobile device108c. In some embodiments, administrators may use the kiosk108dto view information about the site or make changes. As will be understood, the ancillary devices108may each include a processor, a memory component, and/or other hardware and/or software for preforming the functionality provided herein. It should be understood that while the kiosk108dis depicted as being remote from the site110, some embodiments may not be configured in this manner. Specifically, some embodiments may utilize a local kiosk108d, which may communicate via a local network and/or the network100for providing the services described herein.

Example Aspects of an Edge Environment

FIG.2depicts a software configuration for an edge environment, according to embodiments provided herein. Edge environment102may be operatively coupled to aspects of site110, such as charging station112via edge gateway202. Edge environment102further includes an edge cluster208, which is coupled to communication bus210and hardware bus212. Communication bus210is coupled to local cache216, edge session broker218, database server220, cost calculator222, and service interconnect224in this example. Hardware bus212is further coupled to hardware platform226, which may include one or more processors, such as CPU230, storage component232, memory component234, and/or other hardware components. Also coupled to hardware bus212is database228.

Buses210,212may be utilized to facilitate operation of all services that run in edge environment102and communicate with each other via a distributed message streaming system. The coupling of these aforementioned services208-228may be accomplished in one embodiment via a distributed message streaming system, such as NATS.

In the depicted example, charging station112is configured for communication with edge environment102via edge gateway202via a short-range wireless network technology, such as via a ZigBee® PAN. The edge gateway202may be configured to receive data, such as electric charging data, price charge data, vehicle data, etc. from the charging station112and/or vehicles that are being charged via the connection with the site110(ofFIG.1).

In some embodiments, edge gateway202may be configured to abstract data received from aspects of site110(ofFIG.1), such as charging station112, to remove protocol-specific distinctions. For example, a first charging station may utilize a first communication protocol and/or billing protocol and a second charging station may utilize a second communication protocol and/or billing protocol. Edge gateway202may receive data packets from both the first charging station using the first communication protocol and the second charging station using the second communication protocol and may transform the received data into a protocol-agnostic format prior to providing the data to edge cluster208. This allows wide interoperability between edge environment102and various types of hardware (e.g., charging station112) at a site.

Edge cluster208is the central message center in various embodiments. For example, when a user plugs a vehicle into a charging station112, edge cluster208receives data from edge gateway202, parses that data (e.g., to generate access state data) and causes the state data to be sent to the database server220. Edge cluster208also receives the data and creates a session entry, which may be stored in the local cache216. Edge cluster208may additionally send the session entry to the cloud environment104(ofFIG.1) via network100. Edge session broker218may also receive data related to the new session and may query database server220to access additional session data to determine charging characteristics for charging station112.

Edge session broker218may be configured to produce data or signals that are sent to the edge cluster208, which may then be sent to charging station112via edge gateway202. The data or signals may indicate, for example, current delivered over time (e.g., amperes), total energy delivered (e.g., kWh), power delivered over time (e.g., kW), voltage at the charging station over time (e.g., V), charging station state (e.g., connected, disconnect, offline). Charging stations112may report any errors back to edge cluster208via edge gateway202.

Cost calculator222is configured to access pricing data from cloud environment104(ofFIG.1) and may calculate costs incurred based on delivered energy, expected costs prior to charging, idle time interval, parking time interval, etc. An asset interface may also be coupled to the communication bus and may act as an interface between edge environment102and various DERs, such as described above with respect toFIG.1.

Edge cluster208may be configured such that any message received by the edge cluster208may also be sent to the cloud environment104(ofFIG.1) for consumption by a data subscriber in the cloud environment104. For example, if a user of the mobile device108c(inFIG.1) desires to claim a charging session, mobile device108cdoes not need to access edge environment102directly. Instead, mobile device108cmay connect with the cloud environment104(ofFIG.1), which sends a message to the edge cluster208with an instruction to claim the session. Service interconnect224is configured for establishing an HTTP, TCP, and/or other type of communication with the cloud environment104(ofFIG.1) via network100.

Hardware platform226represents any hardware for facilitating the processes and actions described herein. Specifically, CPU230may represent one or more types of processing device configured for executing instructions. Storage component232may be configured as long term storage, such as a hard drive or the like. Memory component234may include any of various types or read access memory or the like. Database228may be configured for additional storage and may be housed with the other hardware and/or elsewhere. Examples of different hardware platforms that may be deployed in edge environment102are described further below with respect toFIGS.4A-4C.

Hardware Configurations for Edge Environment

FIGS.3A-3Cdepict example hardware configurations for the edge environment102, according to embodiments provided herein. Specifically,FIG.3Adepicts a charging solution. As illustrated, the charging station112is coupled to a local network300via core device302. The local network300may include any local area network, Ethernet, PAN, etc. The core device302may be physically installed within communications range of the chargers in the charging station112. A sense device304may be installed, for example, in an electrical room or in another enclosure with electrical equipment of the charging station112and/or one or more energy assets114to monitor the main metering point for the local utility point of common coupling. This enables algorithms to provide the optimal dispatch of EV charging power, subject to local energy rates and the vehicles currently charging. In the case that there are vehicles308using EV chargers that out of communications range of the core device302, such as a sub-level of a parking garage, a remote communications device306are included as required. Also included at the site110is a meter314for communicating energy with the utility114d.

In the embodiment ofFIG.3A, the core device302is the central processing device and serves as the communications hub. The core device302may provide optimization, load management, communication coordination, and data historian services. The core device302communicates with the cloud environment104via cellular modem, wired internet service provider (ISP), and/or other communications medium to get current optimization and load management set points for charging stations112and other assets, such as via an optimization algorithm that may be stored locally and/or at the cloud environment104. It will be understood however, that some embodiments may be configured such that the core device302performs optimization locally. Regardless, the core device302dispatches these set points, through a local communications protocol (e.g., Wi-Fi) and/or via the remote communications device306to reach locations that are distant or hard to reach, such as charging stations with a core device302and/or sense device304at sub-levels of a parking garage or a rooftop solar inverter. The core device302additionally collects data directly from distributed energy resources and power measurement devices or through cloud-based communications with the network100.

Power and energy metering data may be collected via the sense device304. The sense device304may include a smart meter with support for multiple single- and three-phase loads with a local historian and Ethernet communication back to the device via the local network300. The sensing device may also incorporate support for additional devices running on the edge including but not limited to thermocouple wiring, weather stations, temperature sensors, pyranometers, etc. It should be noted that additional sense devices304and remote communication devices306can be added to handle a variety of situations, such as a separate subpanel for energy metering of a new solar or for monitoring of a new inverter associated with a rooftop solar installation.

FIG.3Bdepicts a solar application where the core device302and the sense device304are installed in the facility's electrical room or other common area. The sense device304can monitor the main metering point for the local utility as well as the solar production at tie-in breakers for the solar device114b. The remote communications device306may be installed in a position to communicate directly with the solar device114band report the data received from the solar device114bto the core device302. Accordingly, the core device302, the sense device304, and the remote communications device306depicted inFIG.3Bmay perform similar functions as those devices depicted inFIG.3A.

FIG.3Cdepicts a battery application where the core device302and the sense device304is physically installed near a battery114cstorage installation. In cases where the battery114cis near the point of common coupling with the utility114d, a single sense device304acan monitor the full site. In cases where there is a significant distance to the metering point for the utility114d, a second sense device304b(or a plurality of sensing devices304b) may be installed near the utility meter, such as the electrical room.

Example Hardware Configurations for Core, Sense, and Remote Devices

FIGS.4A-4Cdepict hardware that may be utilized for the devices fromFIGS.3A-3C, according to embodiments provided herein. Specifically,FIG.4Adepicts hardware components that may be present in a core device302. In some embodiments, the core device302is the “brain” where the energy optimization and adaptive load management functions are executed and dispatched. As illustrated, the core device302may include a computing device402, a communication adapter404(or more than one), a network switch406, a wireless communication adapter408, a PAN coordinator410(e.g., a short-range network or other PAN coordinator), and a power supply412. As will be understood, the computing device may include a processor, memory, and/or other components that a normal, specific purpose machine may utilize. In some embodiments, the computing device402may include powerline communication (PLC) infrastructure, while some embodiments may utilize retail and/or micro-industrial computer components for optimization, load management, communication coordination, and/or historian services.

The communication adapter404may be configured to convert between various communication protocols and/or media, such as Modubus RTU (RS485) to Modbus TCP (Ethernet) or Ethernet IP (RJ45) to Ethernet Optical (SFP), etc. The network switch406may be configured for routing of network traffic, and may be configured as an Ethernet switch for communication to other nodes (e.g., the sense device304, the remote communications device306, and/or other core device302), distributed energy resources, and/or energy based management systems.

The wireless communication adapter408may include a cellular modem, internet modem, Wi-Fi access point, etc. for facilitating wireless communications to the internet or other wide area network. Similarly, the PAN coordinator410may be configured to create and/or join communication connections with other devices. This may include a ZigBee® coordinator, Bluetooth device, and/or other device for performing this function. The power supply412may be configured as a battery power, connection to external power, etc.

Similarly, some embodiments may be configured such that the core device302determines that the core device302is communicatively disconnected from the network100. Accordingly, the core device may be configured to store data and direct operation of the charging station112via the stored data until communication is restored to the network100.

Some embodiments may be configured with a plurality of charging stations112that utilize different communication protocols, billing protocols, etc. In these embodiments, the core device302may be configured to communicate with a first charging station via a first protocol and a second charging station via a second protocol, such as via the edge gateway202(FIG.2).

In some embodiments, the core device302may be configured to sense a grid power failure (e.g., from the utility114d) and change modes based on the grid power failure. The mode change may include utilizing a different power source (e.g., solar device114b, battery114c, generator114e, etc.), rationing energy, etc.

In some embodiments, the core device302may receive telematics data from a vehicle114aat the charging station112and may be configured to utilize the telematics data for optimization.

It should be understood that in some embodiments, the computing device402may be embodied as the depiction of the edge environment102fromFIG.2. Specifically, the core device302may be configured as the central computing device of the edge environment and thus may provide the processing and workflow described with reference toFIG.2. Some embodiments are not so limited.

FIG.4Bdepicts hardware components of the sense device304fromFIGS.3A-3C. The sense device304may be configured as a smart-metering component for collection and storage of energy asset data, including but not limited to measurements such as temperature, voltage, current, power, solar irradiance, wind speed, etc. The sense device304may include a smart meter with a plurality of channels of measurement that may comprise single-phase circuits and/or three-phase circuits. The sense device304may communicate meter data back to the core device302from meter locations such as electrical rooms, rooftop solar installations, EV chargers, and subpanels. These embodiments may be optimized for ease of installation and reduced intrusion to the site. Power over Ethernet (POE) sourced from the core device302suffices for most installations. The sense device304may transmit data back to the core device302via a network switch418(e.g., a first network switch). While the sense device304may include a power supply422, in some embodiments, the sense device304may optimized to utilize minimal power and utilize PoE for at least some applications.

As illustrated inFIG.4B, the sense device304includes a power meter414, a communication adapter416, a network switch418, and may include a PAN coordinator420, and a power supply422. The power supply422may include a power interface for providing power to the sense device304. The power meter414may be utilized for monitoring single-phase and three-phase loads of power. The communication adapter416may be utilized for facilitating communications between the sense device304and other devices. In some embodiments, the network switch418may and/or sense device be a PoE enabled switch for communication. Similarly, the PAN coordinator420may create and/or join personal area networks, such as via Zigbee, Bluetooth, and the like.

As illustrated inFIG.4C, the remote communications device306is a network-connectivity extension, primarily for EV charging or solar monitoring locations where Zigbee®, Wi-Fi, Ethernet, and/or other wireless communication signals are being extended to remote or difficult-to-reach locations such as remote subpanels, parking garage levels, or rooftop inverters. Some embodiments are optimized for ease of installation and reduced intrusion to the site where PoE suffices for most installations from the core device302. The remote communications device306may be configured to transmit data back to the core device302via the network switch.

Specifically, the remote communications device306may include a wireless access point424, a communication adapter426, a network switch428(e.g., a second network switch), and may include a PAN coordinator430, and a power supply432. The wireless access point424may be configured to extend wireless communication signals to chargers and/or other intelligent electronic devices. The communication adapter426may be configured for facilitating communications between the remote communications device306and other devices. The network switch428may be configured as a PoE Ethernet switch and/or other network switch for communicating with the core device302. The PAN coordinator430may be configured to create and/or join personal area networks, such as via Zigbee®, Bluetooth®, and the like. The power supply432may include a power interface for providing power to the sense device304. It should be understood that while the remote communications device306is depicted with a power supply432, this is one example. As described above, power to one or more components may be provided via a PoE Ethernet switch and/or via other mechanism.

It should be understood that the embodiments ofFIGS.4A-4Cutilize PAN coordinators410,420,430in each of the core device302, sense device304, and remote communication device306. As such, each of the PAN coordinators410,420,430utilize individual PAN networks, typically, at sites that have networks out of range of each other or too many devices for a single coordinator. Thus, the computing device402(and/or other computing device described herein) may be configured to manage all of the PAN coordinators410,420,430, such as using a USB hub extension. Additionally, the cloud environment104keeps relationships of paired devices up to date for load management and dispatch.

Example Components of Cloud Environment

FIG.5depicts a cloud environment104for providing an edge hardware platform, according to embodiments provided herein. As illustrated, the network100may couple to the cloud environment104via a service interconnect502that corresponds with the service interconnect224fromFIG.2. Similar to the service interconnect224fromFIG.2, the service interconnect502may be configured to facilitate an HTTP, TPC, and/or other communication portal through the network100to the edge environment102for the exchange of data between the edge environment102and the cloud environment104. The service interconnect224is also coupled to a communication bus504, which facilitates communication among various components ofFIG.5. Also connected to the communication bus504are a NATS connector506, a database server508, a session manager510, a cache512, and a collection of services and application programming interfaces (APIs)514. The API514may include a pricing API516, a connections API518, a site API520, a customer's API522, and a topology API524. The API514may be implemented by the hardware platform530. The hardware bus526is coupled to a NATS cloud cluster528, as well as a hardware platform530and a database532. The hardware platform530may include a CPU534, a storage component536, and a memory component538.

The API514is a component of the cloud environment104. As such, the API514and sub-components516-524may cause storage of and/or process site information, site topology, customers, connections to panels, constraints of panels, pricing information of each site, local forecasting services, optimization services, controller services, and caching services, etc. The API514may also serve as a mobile backend by storing personal information of charge users (e.g., email, charging preferences, payment preferences, privileges, access, fleet information, etc.). The API514may additionally store peak charging configurations, data related to meter setup, etc.

When a vehicle is plugged into a charging station112(FIG.1), the edge session broker218(FIG.2) communicates connection information to the API514. The connection information may include vehicle information, user information, charge station information, etc. The API514then creates a charge session object, which is stored in the cache512. The cache512sends the session data, along with topology constraints and the charge session object to the edge environment102. The NATS connector506may additionally cause the NATS cloud cluster528to maintain the charge session object for retrieval by an interested party. As the session continues, the session manager510may be utilized to alter constraints of the session, which may cause the NATS cloud cluster528to update the charge session object.

When a user claims a previously created session with the mobile device108cthe database server508may create a database entry with the charge session, driver, along with energy request, willingness to pay, electricity purchased, etc. The NATS connector506may update the NATS cloud cluster528with the database entry. This data may then be sent to the edge environment102. When the charge session ends (e.g., the vehicle is unplugged), that action will be added to the database entry and the database entry may be moved from a current sessions list to a completed sessions list.

As indicated above, the hardware platform530may represent hardware that may be utilized to execute the components described regardingFIG.5. As such, the CPU534may be configured as any processing unit for receiving and executing computer-readable instructions. The storage component536may be configured as any hard drive or other local storage device. The memory component538may be configured as any type of RAM, ROM, registers, etc. or the like.

Example Process for Controlling Charge and Discharge Parameters of an Energy Asset

FIG.6depicts a flowchart for controlling charge and discharge parameters of an energy asset114, according to embodiments provided herein.

As illustrated in block650, current optimization and load management set points may be acquired for a charging station112. In block652, current optimization and load management set points may be acquired through a local communications protocol via a local network300to the charging station112. In block654, data may be received from the charging station112through the local network300. In block656, the data may be communicated to the cloud environment104via a wide area network, such as the network100. In block658, the core device104may control charge and discharge parameters of an energy asset114at the charging station112using energy-related inputs. As described above, the energy-related inputs may include real-time weather data, historical weather data, weather forecast data, tariff data, historical asset energy interval data, forecasted asset energy interval data, real-time asset energy usage data, system constraint data, user preference data, market-based strategy data, and/or other data.

In block660, energy asset data may be received, including at least one of the following: temperature, voltage, current, power, solar irradiance, meter data, and wind speed. In block662, at least a portion of the energy asset data may be communicated to the core device. In block664, wireless communication signals to the energy asset may be extended. In block668, communications may be facilitated between the remote communications device and at least one of the following: the core device and the sense device. In block670, a communication may be established with at least one of the following via the wide area network: the cloud environment, a software repository, an operations device, an analysis device, a mobile device, and a kiosk.

Example Processing System for Extending Network Coordination of Short-Range Networks to Remote Devices

FIG.7depicts an example processing system700configured to perform the methods described herein.

Processing system700includes one or more processors702. Generally, a processor702is configured to execute computer-executable instructions (e.g., software code) to perform various functions, as described herein.

Processing system700further includes a network interface704, which generally provides data access to any sort of data network, including personal area networks (PANs), local area networks (LANs), wide area networks (WANs), the Internet, and the like.

Processing system700further includes input(s) and output(s)706, which generally provide means for providing data to and from processing system700, such as via connection to computing device peripherals, including user interface peripherals.

Processing system700further includes a memory710comprising various components. In this example, memory710includes a network coordinator control component721, an association component722, a transmitting component723, a receiving component724, a determining component733, device association data725, network data726, set point data727, sensing data728, and network configuration data729.

Processing system700may be implemented in various ways. For example, processing system700may be implemented as a computing device402within core device302, described above with respect toFIGS.3and4. Note that in various implementations, aspects may be omitted, added, or substituted from processing system700.

Example Clauses

Implementation examples are described in the following numbered clauses:Clause 1: An edge hardware system for distributed energy resources comprising: a core device that is deployed in an edge environment of a site, the core device including a computing device with a processor and a memory component, the memory component storing a logic that when executed by the processor causes the edge hardware system configured to: communicate with a cloud environment to acquire current optimization and load management set points for a charging station; dispatch the current optimization and load management set points through a local communications protocol via a local network to the charging station; receive data from the charging station through the local network; communicate the data to the cloud environment via a wide area network; and control charge and discharge parameters of an energy asset at the charging station using energy-related inputs, which include at least one of the following: real-time weather data, historical weather data, weather forecast data, tariff data, historical asset energy interval data, forecasted asset energy interval data, real-time asset energy usage data, system constraint data, user preference data, and market-based strategy data.Clause 2: The edge hardware system of Clause 1, further comprising a sense device that includes a first network switch and a communication adapter configured to: receive, via the communication adapter, energy asset data including at least one of the following: temperature, voltage, current, power, solar irradiance, meter data, and wind speed; and communicate at least a portion of the energy asset data to the core device via the first network switch.Clause 3: The edge hardware system of any of Clauses 1-2, wherein the sense device further includes: a power meter; and a power supply.Clause 4: The edge hardware system of any of Clauses 1-3, further comprising a remote communications device that includes a wireless access point, a communication adapter, a second network switch, and a power supply, wherein the wireless access point is configured to extend wireless communication signals to the energy asset, wherein the communication adapter is configured to facilitate communications between the remote communications device and at least one of the following: the core device or a sense device.Clause 5: The edge hardware system of any of Clauses 1-4, wherein the edge environment is coupled to the energy asset at the site, wherein the energy asset includes at least one of the following: a vehicle, a solar device, a battery, a utility, or a generator.Clause 6: The edge hardware system of any of Clauses 1-5, wherein the edge environment communicates with at least one of the following via the wide area network: the cloud environment, a software repository, an operations device, an analysis device, a mobile device, and a kiosk.Clause 7: The edge hardware system of any of Clauses 1-6, wherein the core device is disconnected from the wide area network.Clause 8: The edge hardware system of any of Clauses 1-7, wherein the core device executes an optimization algorithm locally.Clause 9: The edge hardware system of any of Clauses 1-8, wherein the charging station operates via a first protocol, wherein the core device controls a different charging station that operates via a second protocol.Clause 10: The edge hardware system of any of Clauses 1-9, wherein the core device receives data from local sensors for authenticating users.Clause 11: The edge hardware system of any of Clauses 1-10, wherein the core device receives telematics data from a vehicle at the charging station and utilizes the telematics data for optimization.Clause 12: The edge hardware system of any of Clauses 1-11, wherein the core device senses a grid power failure and changes modes based on the grid power failure.Clause 13: The edge hardware system of any of Clauses 1-2, wherein the core device includes at least one of the following: a power supply, a backup battery, and a power over Ethernet (PoE) connection.Clause 14: A method for managing distributed energy resources comprising: communicating, by a core device, with a cloud environment to acquire current optimization and load management set points for a charging station; dispatching, by the core device, the current optimization and load management set points through a local communications protocol via a local network to the charging station; receiving, by the core device, data from the charging station through the local network; communicating, by the core device, the data to the cloud environment via a wide area network; and controlling, by the core device, charge and discharge parameters of an energy asset at the charging station using energy-related inputs, which include at least one of the following: real-time weather data, historical weather data, weather forecast data, tariff data, historical asset energy interval data, forecasted asset energy interval data, real-time asset energy usage data, system constraint data, user preference data, and market-based strategy data.Clause 15. The method of Clause 14, further comprising: receiving, by a sense device, energy asset data including at least one of the following: temperature, voltage, current, power, solar irradiance, meter data, and wind speed; and communicating, by the sense device, at least a portion of the energy asset data to the core device via a first network switch.Clause 16: The method of any of Clauses 14-15, further comprising: extending, by a remote communications device, wireless communication signals to the energy asset; and facilitating, by the remote communications device, communications between the remote communications device and at least one of the following: the core device and the sense device.Clause 17: The method of any of Clauses 14-16, further comprising communicating with at least one of the following via the wide area network: the cloud environment, a software repository, an operations device, an analysis device, a mobile device, and a kiosk.Clause 18: A non-transitory computer-readable medium for managing distributed energy resources that includes logic that, when executed by a computing device, causes the computing device to perform at least the following: communicate with a cloud environment to acquire current optimization and load management set points for a charging station; dispatch the current optimization and load management set points through a local communications protocol via a local network to the charging station; receive data from the charging station through the local network; communicate the data to the cloud environment via a wide area network; and control charge and discharge parameters of an energy asset at the charging station using energy-related inputs, which include at least one of the following: real-time weather data, historical weather data, weather forecast data, tariff data, historical asset energy interval data, forecasted asset energy interval data, real-time asset energy usage data, system constraint data, user preference data, and market-based strategy data.Clause 19: The non-transitory computer-readable medium of Clause 18, wherein the logic further causes the computing device to perform at least the following: receive energy asset data including at least one of the following: temperature, voltage, current, power, solar irradiance, meter data, and wind speed; and communicate at least a portion of the energy asset data to a core device via a first network switch.Clause 20: The non-transitory computer-readable medium of any of clause 18-19, wherein the logic further causes the computing device to perform at least the following: extend wireless communication signals to the energy asset; and facilitate communications between a remote communications device and at least one of the following: the core device and a sense device.Clause 21. A processing system, comprising: a memory comprising computer-executable instructions; and a processor configured to execute the computer-executable instructions and cause the processing system to perform a method in accordance with any one of claims14-17.Clause 22: A processing system, comprising means for performing a method in accordance with any one of Clauses 14-17.Clause 23: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed by a processor of a processing system, cause the processing system to perform a method in accordance with any one of Clauses 14-17.Clause 24: A computer program product embodied on a computer-readable storage medium comprising code for performing a method in accordance with any one of Clauses 14-17.

Additional Considerations