A network-constrained energy management system for electric vehicle point charging and scheduling

Abstract

A network-constrained energy management system for electric vehicle (EV) site charging and scheduling. In one embodiment, a power schedule is received from an economic dispatch application of a charging site comprising an EV charging station and distributed energy resources. The power schedule may be simulated on a distribution network model of the charging site according to a load flow analysis to determine if any grid code violations have occurred. In response to detection of a violation, a constraint may be generated for each violating node, and the economic dispatch application may be re-run with the constraints to generate a new power schedule until no violations are detected. If all load demands cannot be met by the power schedule, the charging schedule may be adjusted to ensure that critical energy requirements are met. The final power and charging schedule may be used to schedule and control power generation and charging at the charging site.

Description

[Technical field]

[0001] Government Licensing Rights This invention was made with Government support under Contract No. DOE-OE0000896 awarded by the U.S. Department of Energy. The Government has certain rights in this invention.

[0002] background FIELD OF THEINVENTION FIELD OF THE DISCLOSURE

[0002] Embodiments described herein relate generally to energy management systems, and more particularly, to energy management systems that utilize network constraints for charging and power scheduling at electric vehicle (EV) stations. [Background technology]

[0003] 2. Description of Related Art The increased use of EVs in an effort to reduce greenhouse gases has resulted in an increased deployment of EV charging stations. An EV depot may comprise a distribution network that includes several EV charging stations, ancillary loads, and distributed energy resources (DERs) such as energy storage. Each EV charging station comprises one or more chargers configured to supply electricity to connected electric vehicles (e.g., buses, cars, utility trucks, etc.). The distribution network may be managed by an energy management system (EMS) that is generally configured to reduce the cost of electricity consumption.

[0004] Distribution networks should maintain certain levels of voltage and current to avoid violations that may affect not only the connected loads but also the stability of the grid to which the distribution network is connected. The possibility of violations increases when distributed energy resources (DERs) are integrated into EV sites. When distributed energy resources include renewable energy resources (e.g., solar generators, wind generators, geothermal generators, hydroelectric generators, fuel cells, etc.), EMSs generally prioritize utilizing maximum generation from renewable energy resources because renewable energy resources have a lower unit cost.

[0005] However, as the use of renewable energy resources increases, the probability of violations such as overvoltages in the distribution network also increases. In addition, as the EV load increases, the probability of violations such as overvoltages in the distribution network also increases. An EMS that attempts to minimize the cost of electricity in the distribution network without considering the possibility of voltage or current violations in the distribution network may result in penalties for violations and potentially the collapse of the distribution network. Summary of the Invention [Problem to be solved by the invention]

[0006] overview Thus, disclosed are systems, methods, and non-transitory computer-readable media for preventing violations in an EV site power distribution network. Embodiments may also shift loads to ensure critical energy requirements are met. [Means for solving the problem]

[0007] In one embodiment, the method includes receiving, for each of one or more iterations, a power schedule from an economic dispatch application for a charging station with one or more distributed energy resources, the power schedule specifying power to be output from the one or more distributed energy resources to service the charging schedule for loads at the charging station; simulating the power schedule on a distribution network model of the charging station to determine whether at least one node in the distribution network model generates a violation during the simulation; in response to a determination that at least one node in the distribution network model generates a violation during the simulation, generating constraints for at least one node in the distribution network model determined to generate a violation during the simulation; initiating a re-execution of the economic dispatch application updated with the generated constraints to generate a new power schedule for the next iteration; if no node in the distribution network model is determined to generate a violation during the simulation, outputting the power schedule; and scheduling power generation by the distributed energy resources and charging of the loads at the charging station based on the outputted power schedule. The power generation and charging of the loads may be further based on the charging schedule. The violation can be a voltage violation (eg, overvoltage or undervoltage) or a current violation (eg, overcurrent or undercurrent).

[0008] The method may further include using at least one hardware processor to: determine whether the output power schedule satisfies all loads in the charging schedule; in response to determining that the output power schedule does not satisfy all loads in the charging schedule, adjust a charging schedule for one or more loads based on a priority assigned to the one or more loads; initiate a re-execution of the economic dispatch application with the adjusted charging schedule followed by at least one additional iteration; and if it is determined that the output power schedule satisfies all loads in the charging schedule, output the output power schedule as a final power schedule, wherein scheduling of generation by distributed energy resources and charging of the loads at the charging stations is based on the final power schedule. Modifying the charging schedule may include reducing an amount at least one load having a lower priority than at least one other load is charged. Modifying the charging schedule may include shifting a time at which the at least one load is charged. Modifying the charging schedule for the one or more loads based on a priority assigned to the one or more loads may include adjusting a charging amount or a charging time of each of the one or more loads to prioritize critical loads over non-critical loads.

[0009] The load at the charging station may include an electric vehicle. The one or more distributed energy resources may include one or more of a solar generator, a wind generator, a fuel cell, a thermal power plant, a hydroelectric power plant, a gasoline generator, or a battery.

[0010] Scheduling generation by distributed energy resources may include controlling at least one of the one or more distributed energy resources to output power during one or more scheduled time periods and not to output power outside the one or more scheduled time periods. Scheduling charging of a load at a charging location may include controlling at least one charging station to output power to a connected load during the one or more scheduled time periods and not to output power outside the one or more scheduled time periods.

[0011] The at least one constraint for at least one node in the power distribution network may define a voltage range within which the voltage of the at least one node must be maintained across all changes in power setpoint during a power schedule. The voltage violation may be a violation of a grid code that defines a voltage requirement that the charging station must meet.

[0012] The simulation may include a load flow analysis for the power distribution network model. The power schedule may include set points for one or more nodes in the power distribution network model, and a load flow analysis may be performed for each of the set points in the power schedule.

[0013] Any of the disclosed methods may be implemented individually or in any combination in executable software modules of a processor-based system, such as a server, and / or in executable instructions stored on a non-transitory computer-readable medium.

[0014] BRIEF DESCRIPTION OF THE DRAWINGS The details of the present embodiments, both as to their structure and operation, can be learned in part by study of the accompanying drawings, in which like reference numerals refer to like parts and in which: [Brief description of the drawings]

[0015] [Figure 1]FIG. 1 illustrates an exemplary infrastructure in which one or more of the processes described herein may be implemented, according to one embodiment. [Diagram 2] FIG. 1 illustrates an exemplary processing system in which one or more of the processes described herein may be performed, according to one embodiment. [Diagram 3] FIG. 1 illustrates an exemplary power distribution network for an EV site, according to one embodiment. [Figure 4] FIG. 1 illustrates a process for preventing violations in an EV-site power distribution network while ensuring critical energy requirements are met, according to one embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Detailed Description In one embodiment, a system, method, and non-transitory computer-readable medium are disclosed for preventing violations of grid codes in an EV-based power distribution network and, optionally, ensuring that critical energy requirements are met. After reading this description, it will be apparent to one skilled in the art how to implement the present invention in various alternative embodiments and applications. However, while various embodiments of the present invention are described herein, it is understood that these embodiments are presented for purposes of example and illustration only, and are not limiting. Thus, this detailed description of various embodiments should not be construed as limiting the scope or breadth of the present invention as set forth in the appended claims.

[0017] 1. System Overview 1.1. Infrastructure FIG. 1 illustrates an exemplary infrastructure in which one or more of the disclosed processes may be implemented, according to one embodiment. The infrastructure may include an energy management system (EMS) 110 (e.g., comprising one or more servers) that hosts and / or executes one or more of the various functions, processes, methods, and / or software modules described herein. The EMS 110 may comprise a dedicated server, or alternatively, a cloud instance utilizing shared resources of one or more servers. These servers or cloud instances may be co-located and / or geographically distributed. The EMS 110 may also include or be communicatively connected to software 112 and / or one or more databases 114. Additionally, the EMS 110 may be communicatively connected to one or more user systems 130 and / or EV bases 140 via one or more networks 120.

[0018] The network 120 may include the Internet, and the EMS 110 may communicate with the user systems 130 and / or the EV bases 140 over the Internet using standard transmission protocols such as HyperText Transfer Protocol (HTTP), HTTP Secure (HTTPS), File Transfer Protocol (FTP), FTP Secure (FTPS), Secure Shell FTP (SFTP), eXtensible Messaging and Presence Protocol (XMPP), Open Field Message Bus (OpenFMB), IEEE Smart Energy Profile Application Protocol (IEEE 2030.5), as well as proprietary protocols. Although the EMS 110 is shown as being connected to the various systems through a single set of networks 120, it should be understood that the EMS 110 may be connected to the various systems through a different set of one or more networks. For example, platform 110 may be connected to a subset of user systems 130 and / or EV locations 140 via the Internet, but may be connected to one or more other user systems 130 and / or EV locations 140 via an intranet. Additionally, while only a small number of user systems 130 and EV locations 140, one instance of software 112, and one set of databases 114 are shown, it should be understood that the infrastructure may comprise any number of user systems, EV locations, software instances, and databases.

[0019] The user system 130 may comprise any type of computing device capable of wired and / or wireless communication, including, but not limited to, a desktop computer, a laptop computer, a tablet computer, a smart phone or other mobile phone, a server, a game console, a television, a set-top box, an electronic kiosk, a point of sale terminal, an embedded controller, a programmable logic controller (PLC), and the like. However, it is generally contemplated that the user system 130 comprises a personal computer, a mobile device, or a workstation through which an agent of the operator of the EV site 140 can interact with the EMS 110. These interactions may include inputting data (e.g., parameters for configuring one or more of the processes described herein) and / or receiving data (e.g., output of one or more of the processes described herein) via a graphical user interface provided by the EMS 110 or a system between the EMS 110 and the user system 130. A graphical user interface may comprise a screen (e.g., a web page) that includes a combination of content and elements such as text, images, video, animations, references (e.g., hyperlinks), frames, inputs (e.g., text boxes, text areas, check boxes, radio buttons, drop-down menus, buttons, forms, etc.), scripts (e.g., JavaScript), etc., including elements that include or are derived from data stored in one or more databases (e.g., database 114).

[0020] The EMS 110 may execute software 112 including one or more software modules that implement one or more of the disclosed processes. Additionally, the EMS 110 may comprise, be communicatively coupled to, or otherwise have access to one or more databases 114 that store data input to and / or output from one or more of the disclosed processes. Any suitable database (including cloud-based databases, proprietary databases, and unstructured databases) may be utilized, including, but not limited to, MySQL®, Oracle™, IBM®™, Microsoft SQL™, Access™, PostgreSQL™, and the like.

[0021] 1.2. Exemplary Processing Device 2 is a block diagram illustrating an example wired or wireless system 200 that may be used in connection with various embodiments described herein. For example, system 200 may be used as or in conjunction with one or more of the functions, processes, or methods described herein (e.g., for storing and / or executing software 112), and may represent components of EMS 110, user system 130, EV base 140, and / or other processing devices described herein. System 200 may be a server or any conventional personal computer, or any other processor-enabled device capable of wired or wireless data communication. Other computer systems and / or architectures may also be used, as will be apparent to one skilled in the art.

[0022] The system 200 preferably includes one or more processors 210. The processor 210 may comprise a central processing unit (CPU). Additional processors may be provided, such as a graphics processing unit (GPU), auxiliary processors for managing input / output, auxiliary processors for performing floating point operations, dedicated microprocessors with architecture suitable for fast execution of signal processing algorithms (e.g., digital signal processors), processors lower in the main processing system (e.g., back-end processors), additional microprocessors or controllers for dual or multi-processor systems, and / or co-processors. Such auxiliary processors may be separate processors or may be integrated with the processor 210. Examples of processors that may be used with system 200 include, but are not limited to, any processor available from Intel Corporation of Santa Clara, California (e.g., Pentium™, Core i7™, Xeon™, etc.), any processor available from Advanced Micro Devices, Incorporated (AMD) of Santa Clara, California, any processor available from Apple Inc. of Cupertino (e.g., A-series, M-series, etc.), any processor available from Samsung Electronics Co., Ltd. of Seoul, Korea (e.g., Exynos™), etc.

[0023] The processor 210 is preferably connected to a communication bus 205. The communication bus 205 may include a data channel to facilitate information transfer between the storage and other peripheral components of the system 200. Additionally, the communication bus 205 may provide a set of signals used to communicate with the processor 210, including a data bus, an address bus, and / or a control bus (not shown). The communication bus 205 may include any standard or non-standard bus architecture, such as, for example, an industry standard architecture (ISA), an extended industry standard architecture (EISA), a Micro Channel Architecture (MCA), a peripheral component interconnect (PCI) local bus, a bus architecture conforming to standards promulgated by the Institute of Electrical and Electronics Engineers (IEEE), including the IEEE 488 general-purpose interface bus (GPIB), IEEE 696 / S-100, and the like.

[0024] The system 200 preferably includes a main memory 215 and may also include a secondary memory 220. The main memory 215 provides storage of instructions and data for programs executed on the processor 210, such as one or more of the functions and / or modules (e.g., software 112) described herein. It should be understood that the programs stored in the memory and executed by the processor 210 may be written and / or compiled according to any suitable language, including, but not limited to, C / C++, Java, JavaScript, Perl, Visual Basic, .NET, etc. The main memory 215 is typically a semiconductor-based memory, such as dynamic random access memory (DRAM) and / or static random access memory (SRAM). Other semiconductor-based memory types include, for example, synchronous dynamic random access memory (SDRAM), including read only memory (ROM), Rambus dynamic random access memory (RDRAM), ferroelectric random access memory (FRAM), and the like.

[0025] Secondary memory 220 may optionally include internal medium 225 and / or removable medium 230. Removable medium 230 is read from and written to in any known manner. Removable storage medium 230 may be, for example, a magnetic tape drive, a compact disc (CD) drive, a digital versatile disc (DVD) drive, other optical drive, a flash memory drive, or the like. Secondary memory 220 is a non-transitory computer-readable medium on which computer-executable code (e.g., software 112) and / or other data is stored. Computer software or data stored in secondary memory 220 is loaded into main memory 215 for execution by processor 210.

[0026] In alternative embodiments, secondary memory 220 may include other similar means for allowing computer programs or other data or instructions to be loaded into system 200. Such means may include, for example, a communications interface 240 that allows software and data to be transferred to system 200 from an external storage medium 245. Examples of external storage medium 245 may include an external hard disk drive, an external optical drive, an external magneto-optical drive, and the like. Other examples of secondary memory 220 may include semiconductor-based memory, such as programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable read-only memory (EEPROM), and flash memory (a block-oriented memory similar to EEPROM).

[0027] As mentioned above, the system 200 may include a communications interface 240. The communications interface 240 allows software and data to be transferred between the system 200 and an external device (e.g., a printer), a network, or other information source. For example, computer software or executable code may be transferred to the system 200 from a network server (e.g., the platform 110) via the communications interface 240. Examples of the communications interface 240 include an internal network adapter, a network interface card (NIC), a Personal Computer Memory Card International Association (PCMCIA) network card, a card bus network adapter, a wireless network adapter, a Universal Serial Bus (USB) network adapter, a modem, a wireless data card, a communications port, an infrared interface, an IEEE 1394 Firewire, and any other device capable of interfacing the system 200 with a network (e.g., the network 120) or another computing device.Communications interface 240 preferably implements industry published protocol standards such as Ethernet IEEE 802 standard, Fibre Channel, digital subscriber line (DSL), asynchronous digital subscriber line (ADSL), Frame Relay, asynchronous transfer mode (ATM), integrated digital services network (ISDN), personal communications service (PCS), transmission control protocol / Internet protocol (TCP / IP), serial line Internet protocol / point to point protocol (SLIP / PPP), etc., but may also implement customized or non-standard interface protocols.

[0028] The software and data transferred via communications interface 240 are typically in the form of electrical communications signals 255. These signals 255 may be provided to communications interface 240 via communications channel 250. In one embodiment, communications channel 250 may be a wired or wireless network (e.g., network 120), or any of a variety of other communications links. Communications channel 250 carries signals 255 and can be implemented using a variety of wired or wireless communications means, including wire or cable, optical fiber, conventional telephone line, a cellular phone link, a wireless data communications link, a radio frequency (RF) link, or an infrared link, just to name a few.

[0029] Computer-executable code (e.g., computer programs such as software 112) are stored in main memory 215 and / or secondary memory 220. Computer programs may also be received via communications interface 240 and stored in main memory 215 and / or secondary memory 220. Such computer programs, when executed, enable system 200 to perform various functions of the disclosed embodiments described elsewhere herein.

[0030] In this description, the term "computer-readable medium" is used to refer to any non-transitory computer-readable storage medium used to provide computer-executable code and / or other data to or within system 200. Examples of such media include main memory 215, secondary memory 220 (including internal memory 225, removable media 230, and external storage media 245), and any peripherals communicatively coupled to communication interface 240 (including a network information server or other network device). These non-transitory computer-readable media are means for providing executable code, programming instructions, software, and / or other data to system 200.

[0031] In embodiments implemented using software, the software may be stored on a computer-readable medium and loaded into system 200 via removable medium 230, I / O interface 235, or communication interface 240. In such embodiments, the software is loaded into system 200 in the form of electrical communication signals 255. The software, when executed by processor 210, preferably causes processor 210 to perform one or more of the processes and functions described elsewhere herein.

[0032] In one embodiment, I / O interface 235 provides an interface between one or more components of system 200 and one or more input and / or output devices. Examples of input devices include, but are not limited to, sensors, keyboards, touch screens or other touch-sensing devices, cameras, biosensing devices, computer mice, trackballs, pen-based pointing devices, etc. Examples of output devices include, but are not limited to, other processing devices, cathode ray tubes (CRTs), plasma displays, light-emitting diode (LED) displays, liquid crystal displays (LCDs), printers, vacuum fluorescent displays (VFDs), surface-conduction electron-emitter displays (SEDs), field emission displays (FEDs), etc. In some cases, input and output devices may be combined, such as in the case of a touch-sensitive display (e.g., a smartphone, tablet, or other mobile device).

[0033] The system 200 may also include optional wireless communication components to facilitate wireless communication over voice and / or data networks (e.g., in the case of user system 130 being a smartphone or other mobile device). The wireless communication components include an antenna system 270, a radio system 265, and a baseband system 260. In the system 200, radio frequency (RF) signals are transmitted and received wirelessly by the antenna system 270 under the control of the radio system 265.

[0034] In one embodiment, antenna system 270 may include one or more antennas and one or more multiplexers (not shown) that perform switching functions to provide transmit and receive signal paths for antenna system 270. In the receive path, the received RF signal may be coupled from the multiplexer to a low noise amplifier (not shown), which amplifies the received RF signal and transmits the amplified signal to radio system 265.

[0035] In alternative embodiments, the radio system 265 may comprise one or more radios configured to communicate over various frequencies. In one embodiment, the radio system 265 may combine a demodulator (not shown) and a modulator (not shown) into one integrated circuit (IC). The demodulator and modulator may be separate components. In the inbound path, the demodulator removes the RF carrier signal leaving a baseband received audio signal that is transmitted from the radio system 265 to the baseband system 260.

[0036] If the received signal contains audio information, the baseband system 260 decodes the signal and converts it to an analog signal. The signal is then amplified and sent to a speaker. The baseband system 260 also receives analog audio signals from a microphone. These analog audio signals are converted to digital signals and encoded by the baseband system 260. The baseband system 260 also encodes the digital signals for transmission and generates a baseband transmit audio signal that is routed to a modulator portion of the radio system 265. The modulator mixes the baseband transmit audio signal with an RF carrier signal and generates an RF transmit signal that may be routed to the antenna system 270 and passed through a power amplifier (not shown). The power amplifier amplifies the RF transmit signal and routes it to the antenna system 270, where the signal is switched to an antenna port for transmission.

[0037] The baseband system 260 is also communicatively coupled to the processor 210. The processor 210 may access the data storage areas 215 and 220. The processor 210 is preferably configured to execute instructions (i.e., computer programs such as the disclosed software) that may be stored in the main memory 215 or the secondary memory 220. Computer programs may also be received from the baseband processor 260 and stored in the main memory 210 or the secondary memory 220 or executed upon receipt. Such computer programs, when executed, enable the system 200 to perform various functions of the disclosed embodiments.

[0038] 1.3. Example EV Depot 3 illustrates a single-line diagram of an example power distribution network for an example EV site 140, according to one embodiment. The EV site 140 is connected to a power grid 310 from which electricity may be purchased. The cost of purchasing electricity may vary according to time-of-use (ToU) rates, both daily (e.g., higher during the day than at night) and over the course of days (e.g., higher on summer days than on winter days). The ToU rates may assign peak, partial peak, and off-peak rates to various time periods (e.g., time intervals in a day) and represent the cost of electricity during those time periods.

[0039] Additionally, EV base 140 includes one or more distributed energy resources including, for example, one or more battery energy storage (BES) systems 320 and / or one or more generators 330, shown as generators 330A and 330B. Generators 330 may include renewable energy resources (e.g., solar generators, wind generators, geothermal generators, hydroelectric generators, fuel cells, etc.) and / or non-renewable energy resources (e.g., diesel generators, natural gas generators, etc.). For example, generator 330A may be a solar generator including multiple solar cells that convert sunlight into electricity, and generator 330B may be a diesel generator that burns diesel gasoline to generate electricity.

[0040] The EV depot also includes one or more EV charging stations 340, shown as EV charging stations 340A, 340B, 340C, 340D, 340E, 340F, and 340G. It should be understood that each EV charging station 340 represents a load and may be connected to an electric vehicle 350, shown as electric vehicles 350A, 350B, 350C, 350E, and 350F. Each EV charging station 340 is configured to be electrically connected to an electric vehicle 350 to supply electricity to one or more batteries of the electric vehicle 350. At any given time, some EV charging stations 340 may be connected to an electric vehicle 350 (e.g., 340A-350A, 340B-350B, 340E-350E, 340F-350F) and other EV charging stations 340 (e.g., 340D and 340G) may not be connected to an electric vehicle 350. One or more EV charging stations 340 may be configured to switch on or off the power supply to connected electric vehicles 350 under the control of the EMS 110 or other controller. For example, the EV charging station 340 may include a processing system 200 that receives commands from a controller (e.g., the EMS 110) via the communication interface 240, processes the commands using the processor 210 and main memory 215, and controls actuators (e.g., one or more switches) to switch the power source on or off according to the processed commands. It should be understood that the power distribution network of the EV site 140 may also include types of loads other than the electric vehicles 350, such as auxiliary loads for operating various functions of the EV site 140. It should also be understood that each BES system 320 can function as both a power source (i.e., when discharging) and a load (i.e., when charging).

[0041] 2. Process Overview An embodiment of a process for preventing violations in an EV site power distribution network and ensuring that critical energy requirements are met as needed will now be described in detail. It should be understood that the described process may be embodied in one or more software modules executed by one or more hardware processors (e.g., processor 210), for example, as software 112 executed by a processor of EMS 110. The described process may be implemented as instructions expressed in source code, object code, and / or machine code. These instructions may be executed directly by hardware processor 210, or may be executed by a virtual machine or container operating between the object code and hardware processor 210. Additionally, the disclosed software may be built on or interfaced with one or more existing systems.

[0042] Alternatively, the described processes may be implemented as hardware components (e.g., general purpose processors, integrated circuits (ICs), application-specific integrated circuits (ASICs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic, etc.), a combination of hardware components, or a combination of hardware and software components. To clearly illustrate the interchangeability of hardware and software, various example components, blocks, modules, circuits, and steps are described herein generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in various ways for each particular application, but such implementation decisions should not be interpreted as a departure from the scope of the present disclosure. Furthermore, the grouping of functions within a component, block, module, circuit, or step is for ease of description. Certain functions or steps can be moved from one component, block, module, circuit, or step to another without departing from the invention.

[0043] FIG. 4 illustrates a process 400 for preventing violations in an EV site power distribution network and, optionally, ensuring that critical energy requirements are met, according to one embodiment. Process 400 may be implemented as software 112 executed by one or more processors 210 of EMS 110. Although process 400 is illustrated with a particular arrangement and order of sub-processes, process 400 may be implemented with fewer, more, or different sub-processes, as well as a different arrangement and / or order of sub-processes. For example, in an alternative embodiment that does not ensure that critical energy requirements are met, process 400 may consist only of sub-processes 410-440 and 470 (e.g., where sub-process 470 proceeds directly from the "No" branch of sub-process 430). Additionally, even if the sub-processes are described or illustrated in a particular order, any sub-process that is not dependent on the completion of other sub-processes may be performed before, after, or in parallel with other independent sub-processes.

[0044] Process 400 may be executed for each of a number of time periods sequentially according to a rolling time window to generate a power schedule and a charging schedule for each time period. The size of the time window may be of any duration suitable for a particular design goal, such as 5 minutes, 15 minutes, 30 minutes, 1 hour, 12 hours, 24 hours, 1 week, etc. It should be understood that each period may be a future period. In this case, process 400 may be executed such that there is little or no time between process 400 outputting a final power schedule for that period and the start of that period, or sufficiently in advance of that period (e.g., hours, days, weeks, etc. before the start of the time period).

[0045] In sub-process 410, economic allocation is performed for the particular time period under consideration. Economic allocation may be implemented as a software application integrated into the software implementing the other sub-processes of process 400. Alternatively, economic allocation may be implemented as a software application separate from the software implementing one or more other sub-processes of process 400 and provide its output (e.g., to sub-process 420) via an application programming interface (API). For example, the output of sub-process 410 may be pushed via the API of the software implementing sub-process 420 or pulled by the software implementing sub-process 420 via the API of the economic allocation application.

[0046] Economic dispatch refers to the allocation of electricity demand from loads (e.g., 350) to distributed energy resources (e.g., BES systems 320 and / or generators 330) to achieve the most economical use of electricity. Typically, economic dispatch is formulated as an optimization problem that aims to minimize the purchase cost of electricity from the grid 310. The basic idea is to prioritize the use of distributed energy resources with lower marginal costs over the use of distributed energy resources and the grid 310 with higher marginal costs. Traditionally, economic dispatch does not consider network constraints.

[0047] In one embodiment, economic dispatch is performed for the particular period under consideration based on a charging schedule 415 that covers at least the particular period under consideration. The charging schedule 415 may include, for each of one or more electric vehicles 350 to be charged within at least the particular period under consideration, the time at which charging of the electric vehicle 350 is scheduled to begin, the duration at which the electric vehicle 350 is scheduled to be charged, the amount of charge to be provided to the electric vehicle 350 and / or the charge level at which the electric vehicle 350 should be charged (e.g., to have sufficient charge to complete the scheduled route), the time at which the electric vehicle 350 should be charged (e.g., to complete the route as scheduled), etc. The charging schedule 415 may be updated periodically (e.g., every 15 minutes) to reflect the current or expected state of each electric vehicle 350. It should be understood that the charging schedule 415 may include schedules for multiple periods to be considered (e.g., all future periods for which EV charging is scheduled), as long as it includes a schedule for the particular period under consideration.

[0048] The economic dispatch may generate a power schedule that specifies the power to be output from each of the distributed energy resources (e.g., BES system 310 and / or generator 330) at EV site 140 during the particular time period under consideration to meet the load required by electric vehicles 350 in the charging schedule 415 for the particular time period under consideration while minimizing the cost of electricity during the particular time period under consideration. The power schedule includes, for each distributed energy resource to be used during the particular time period under consideration, the identity of the distributed energy resource, the time period during which the distributed energy resource is scheduled to output power (e.g., discharged from BES system 320 or generated by generator 330), the amount of power to be output by the distributed energy resource, etc. During execution, the economic dispatch may consider equality constraints (e.g., power balance, electric vehicle state of charge balance, etc.) and inequality constraints (e.g., maintaining a load at a common node at a particular value, maintaining a threshold level of the state of charge of electric vehicles 350, preconditioning EV load, availability of electric vehicles 350, etc.). Traditionally, economic dispatch does not consider network constraints, such as voltage and / or current, at a node in the distribution network of the EV site 140. It should be appreciated that a node in the distribution network may be, for example, a point of common coupling with the grid 310, the BES system 320, the generator 330, the charging station 340, etc.

[0049] In sub-process 420, a load flow analysis is performed on the power schedule output by the economic dispatch performed in sub-process 410 to identify violations (e.g., voltage violations such as overvoltage or undervoltage, current violations, etc.). The distribution network of the EV site 140 may be modeled by a distribution network model representing each node in the distribution network. The load flow analysis may simulate the power schedule on the distribution network model to determine whether any node in the distribution network generates a violation during the simulation. In particular, the load flow analysis determines the operating steady state of each node in the distribution network for a given load in the power schedule. The steady state of each node may be represented as a set of parameters such as voltage, phase angle, active power, and reactive power. The load flow analysis may solve one or more of these parameters (e.g., voltage and phase angle) at each node in the distribution network as represented in the distribution network model using a set of simultaneous algebraic power equations for the nodes in the distribution network based on the active power and reactive power set points.

[0050] In sub-process 430, process 400 determines whether the load flow analysis applied in sub-process 420 detected a violation. For example, an overvoltage violation may occur if the node's steady-state voltage exceeds a predetermined threshold. Similarly, an undervoltage violation may occur if the node's steady-state voltage is below a predetermined threshold. Violations of other parameters, such as current, may be detected (e.g., using predefined thresholds). These predetermined thresholds may be defined by a grid code, such as the IEEE 1547 Standard for Interconnection and Interoperation of Distributed Energy Resources with Associated Electric Power Systems. IEEE 1547 defines an operating region for its Abnormal Operation Performance Category III continuous voltage operation as having a lower limit of 0.88 per unit and an upper limit of 1.1 per unit. Thus, if IEEE 1547 is used for the grid code, a voltage above 1.1 per unit of node is determined as an overvoltage violation and a voltage below 0.88 per unit of node is determined as an undervoltage violation. If a violation is detected (i.e., "Yes" in sub-process 430), process 400 proceeds to sub-process 440. On the other hand, if a violation is not detected (i.e., "No" in sub-process 430), process 400 proceeds to sub-process 450.

[0051] In subprocess 440, constraints are generated for each of the violations detected by the load flow analysis in subprocess 420 and added to the new run of economic dispatch in subprocess 410. In particular, each constraint may be formulated using a sensitivity analysis of the control variables (e.g., active and reactive power setpoints) of the node where the respective violation was detected. The sensitivity analysis determines the sensitivity factor S of a parameter such as voltage or current to a change Δu in the active and reactive power setpoints of the distributed energy resource at the violating node i. u Pi Consider S for the violation node i. u Pi can be calculated by load flow analysis. In the solution to economic dispatch, the voltage at the violation node i is P i iniThen, the constraint for the violating node i can be expressed as:

[0052]

number

[0053] Here, P i min is the minimum allowable value of parameter P (e.g., voltage or current defined by the grid code) at the violating node i, and P i max where n is the maximum allowed value of a parameter P (e.g., voltage or current defined by the grid code) at the violating node i, and n is the number of setpoint changes. Such constraints may be generated for one or more of the nodes where a violation is detected (e.g., a voltage violation such as an overvoltage or undervoltage, a current violation such as an overcurrent or undercurrent, etc.).

[0054] Once constraints are generated in sub-process 420 for all violations detected by the load flow analysis in sub-process 440, the generated constraints are added to the economic dispatch, and the economic dispatch is run again in another iteration of sub-process 410 while being constrained by the generated constraints. For example, to avoid a detected overvoltage violation, the voltage at a particular node i may be increased to P i max If a constraint is added preventing the voltage at node i from exceeding P i max Similarly, to avoid a detected undervoltage violation, we must generate a solution (i.e., a power schedule) that does not exceed P i min If a constraint is added preventing the voltage at node i from being less than P i min Similarly, to avoid a detected overcurrent violation, we must generate a solution (i.e., a power schedule) such that the current at a particular node i is greater than or equal to P i maxIf a constraint is added preventing the current at node i from exceeding P i max Similarly, to avoid a detected undercurrent violation, we must generate a solution (i.e., a power schedule) that does not exceed P i min If a constraint is added preventing the current at node i from being less than P i min or greater, a solution (i.e., a power schedule) must be generated.

[0055] The constraints generated in sub-process 440 may be accumulated over each iteration of sub-process 440, such that each iteration of economic allocation in sub-process 410 is constrained by all of the constraints generated by all previous and current iterations of sub-process 440 for the current period under consideration. It should be understood that an instance of process 400 may include one or any other non-zero number of iterations of sub-processes 410-430, and zero, one, or any other number of iterations of sub-process 440.

[0056] In sub-process 450, when a power schedule is output by the economic dispatch performed in sub-process 410 where no violation is detected in the load flow analysis of sub-process 420, process 400 determines whether the power schedule satisfies all load demands (e.g., electric vehicle 350 connected to charging station 340) in charging schedule 415. In other words, process 400 determines whether the load had to be reduced or curtailed to avoid the detected violation. If the generation in the power schedule is sufficient to supply all of the power required by the load during the current period under consideration, the load demand is met. Conversely, if the generation in the power schedule is not sufficient to supply all of the power required by the load during the current period under consideration, the load demand is not met. In the case of electric vehicle 350, the load demand of electric vehicle 350 is met if the generation is sufficient to charge electric vehicle 350 to a required charge level (e.g., a charge level required for electric vehicle 350 to complete a scheduled route). It should be understood that the required charge level for electric vehicle 350 may be, but need not be, the full capacity of the electric vehicle's battery. If the power schedule does not meet all of the load demands (i.e., "No" in sub-process 450), process 400 proceeds to sub-process 460. On the other hand, if the power schedule meets all of the load demands (i.e., "Yes" in sub-process 450), process 400 proceeds to sub-process 470.

[0057] In sub-process 460, the charging schedule 415 may be adjusted based on the priorities assigned to the loads. For example, each electric vehicle 350 may be assigned a priority indicating the importance of the electric vehicle 350 and / or the flexibility of the schedule of the electric vehicle 350, with more important / flexible electric vehicles 350 being assigned a higher priority than less important / flexible electric vehicles 350. The priorities may be implemented in any manner (e.g., as weights used in modeling) and according to any scale that provides an appropriate solution for distinguishing between electric vehicles 350 (e.g., numerically on a scale such as binary, 1-5, or 1-10 for critical and non-critical classes). The priority of a given electric vehicle 350 may be determined manually or automatically based on a variety of factors including the purpose of the electric vehicle (e.g., an emergency vehicle may be prioritized over a non-emergency vehicle), route (e.g., an electric vehicle 350 having a more important or longer route may be prioritized over an electric vehicle 350 having a less important or shorter route), schedule (e.g., an electric vehicle 350 that must depart the EV site 140 earlier or has a less flexible schedule may be prioritized over an electric vehicle 350 that may depart the EV site 140 later or has a more flexible schedule), charge level (e.g., an electric vehicle 350 with a lower charge level may be prioritized over an electric vehicle 350 with a higher charge level), etc. In either case, the amount of available power generated according to the power schedule delivered to the more critical electric vehicles 350 may be increased at the expense of the amount of available power delivered to the less critical electric vehicles 350, such that the more critical electric vehicles 350 receive an amount of power that meets or a greater percentage of their load demands, while the less critical electric vehicles 350 receive no power or an amount of power that meets a smaller percentage of their load demands. Thus, it should be understood that adjusting the charging schedule 415 may include reducing the amount of charge to the less critical loads.Additionally or alternatively, an adjustment to the charging schedule 415 may include shifting a charging time for the load from a first time to a second time that is earlier or later than the first time. The second time to which the charging time of the load is shifted may be within the particular time period under consideration or may be outside the particular time period under consideration (e.g., within an earlier or later time period represented in the charging schedule 415, but outside the current range of a rolling time window).

[0058] Once charging schedule 415 is adjusted in sub-process 460, economic dispatch is performed again in another iteration of sub-process 410 with the adjusted charging schedule 415. It should be understood that this performance of economic dispatch may be constrained by any constraints previously generated in any iteration of sub-process 440 for the particular time period under consideration. It should also be understood that the adjusted charging schedule 415 may result in additional violations detected in sub-processes 420 and 430 that may be addressed in additional iterations of sub-process 440.

[0059] In sub-process 470, once a power schedule is generated by economic dispatch in sub-process 410, does not produce any violations detected by the load flow analysis in sub-process 420, and satisfies all loads in sub-process 450, the power schedule is output as a final power schedule used to schedule power output by distributed energy resources (e.g., BEM system 320, generator 330, etc.) in EV site 140 during the particular time period under consideration. Additionally, charging schedule 415 may be used to schedule various loads (e.g., electric vehicles 350) during the particular time period under consideration.

[0060] The final power schedule that is output in sub-process 470 may be used to inform control decisions during the particular period considered during the iteration of process 400. It should be appreciated that another iteration of process 400 may be performed for the next time period encompassed by the rolling time window to generate a final power schedule for that time period, and so on.

[0061] In one embodiment, this final power schedule is used by EMS 110 or other systems to generate control commands for one or more BES systems 320, generators 330, charging stations 340, and / or other electrical components of EV site 140. Specifically, EMS 110 may generate and transmit the control commands to associated electrical components in EV site 140 via network 120, and EV site 140 may then execute the received control commands. For example, EMS 110 may control distributed energy resources (e.g., BES systems 320, generators 330, etc.) by transmitting control commands to them to generate and / or output power during one or more scheduled time periods and not output power outside of the one or more scheduled time periods. As another example, EMS 110 may control charging station 340 by transmitting control commands to it to output power to connected electric vehicles 350 during one or more scheduled time periods and not output power outside of the one or more scheduled time periods.

[0062] 3. Example Use Cases An exemplary use case of the process 400 will now be described for purposes of illustration and not limitation. In the example, the EV depot 140 includes a bus depot for charging electric buses as electric vehicles 350 in a fleet of an urban mass transit system. The active and reactive power set points of the distributed energy resources (e.g., the BES system 320, the generators 330, etc.) and the charging stations 340 may be scheduled at one-hour intervals (e.g., the process 400 may be executed iteratively over a period within a one-hour rolling time window). The generators 330 are assumed to comprise solar generators. Each electric bus has a route that must be operated according to a route schedule. Thus, each electric bus must be charged to at least a sufficient level of charge to complete its scheduled route and must leave the EV depot 140 by a specific time to comply with the route schedule.

[0063] In the first use case, it is assumed that there is no restriction associated with the amount of power that may be purchased from the grid 310. The economic dispatch in the first iteration of sub-process 410 maximizes the power generation by the solar generators to minimize the amount of electricity that must be purchased from the grid 310. As a result, during the day (e.g., afternoon) when the cost of purchasing solar and electricity is highest, the cost of purchasing electricity is generally lower (e.g., potentially negative if the grid 310 operator purchases excess power from the EV site 140). However, if the power schedule output by the economic dispatch after the first iteration of sub-process 410 was to be used, the EV site 140 may violate the associated grid code (e.g., due to an overvoltage or undervoltage condition). Thus, the power schedule may be modified by one or more iterations of the loop formed by sub-process 420-430-440-410 to limit the economic dispatch until no violations are detected by the load flow analysis in sub-process 420. As a result, the overall power purchase cost of the modified power schedule may increase, especially during time intervals when solar and power purchase costs are highest, because solar generator utilization is reduced to avoid violations. However, while more costly in the short term, the modified power schedule is an improvement over the original power schedule because it avoids violations that may be more costly in the long term. It should be appreciated that similar situations that arise with other types of distributed energy resources or as a result of increased EV loads may similarly be addressed by process 400.

[0064] In a second use case, the amount of power available for purchase from the grid 310 may be reduced. This may be due to demand response by the grid 310 operator, grid 310 failure, islanding, violation of grid code, cyber attack, natural disaster, peak load shaving, etc. In such situations, the operator prioritizes minimizing the overall load on the grid 310. In these cases, the EV site 140 must cooperate with the grid 310 by reducing its power consumption at the point of common coupling with the grid 310. This reduction in power consumption may mean that not all loads can be satisfied by the power schedule (i.e., “No” in sub-process 450). Thus, the charging schedule 415, and therefore the power schedule, may be modified by one or more iterations of sub-processes 460-410-420-430-450 (potentially by one or more iterations of the inner loop formed by sub-processes 410-420-430-440). The modified charging and power schedules may result in higher power purchase costs and / or some electric buses (e.g., non-critical buses) being only partially or not charged at all before leaving EV depot 140. As described elsewhere herein, each electric bus may be ranked according to a priority that represents the importance of the electric bus and / or the flexibility of the electric bus schedule. This ranking may be performed manually (e.g., by the operator of EV depot 140) or automatically.

[0065] Regardless of the particular scenario, the disclosed embodiments utilize load flow analysis (e.g., subprocess 420) to detect violations of grid codes in the generation schedule output by economic dispatch (e.g., subprocess 410) and integrate constraints for those violations into the economic dispatch to generate a generation schedule that does not violate the grid codes. Additionally, the disclosed embodiments may utilize priorities assigned to electric vehicles 350 to shift loads to ensure that critical loads are met without violating grid codes and that all electric vehicles 350 leave EV site 140 with at least a target state of charge (e.g., required to meet scheduled routes). Thus, the disclosed embodiments improve the overall performance of the distribution network within EV site 140 while maximizing economic benefits for operators of EV site 140.

[0066] Although the disclosed embodiments are described primarily with respect to controlling power generation and charging within EV depot 140, the disclosed embodiments may be applied to other applications. For example, the same methods may be used to design research and customer demonstrations. Additionally, the same methods may be used by electric power companies to manage circuit segments of a medium voltage distribution system.

[0067] Further, it should be understood that the disclosed embodiments may be applied to a system of two or more EV sites 140. In particular, a single EMS 110 may manage power and charging schedules for the multiple EV sites 140. In this case, the power schedule may encompass generation at distributed energy resources across the multiple EV sites 140, and the charging schedule 415 may encompass EV charging at charging stations 340 across the multiple EV sites 140. Furthermore, if an electric vehicle 350 can be easily charged at two or more different EV sites 140, load may be moved (e.g., in subprocess 460) between EV sites 140 (e.g., from a first EV site 140 to a second EV site 140) to avoid load shedding. Similarly, generation may be shifted by economic dispatch (e.g., in subprocess 410) between EV sites 140 (e.g., from a first EV site 140 to a second EV site 140) to avoid violations and accommodate adjustments to the charging schedule 415 (e.g., in subprocess 460).

[0068] The following aspects refer to particular embodiments of the present disclosure. 1. For each of the one or more iterations, receiving a power schedule from an economic dispatch application for a charging station comprising one or more distributed energy resources, the power schedule specifying power to be output from the one or more distributed energy resources to service a charging schedule for a load at the charging station; simulating a power schedule on a distribution network model of the charging station, to determine whether at least one node in the distribution network model generates a violation during the simulation; in response to determining that at least one node in the electric power distribution network model generates a violation during the simulation; generating a constraint for at least one node in the power distribution network model that is determined to cause a violation during simulation; initiating a re-execution of the economic dispatch application, updated with the generated constraints, to generate a new power schedule for the next iteration; and outputting a power schedule if no node in the power distribution network model is determined to cause a violation during the simulation; Scheduling power generation by distributed energy resources and charging of loads at charging stations based on the output power schedule; Use at least one hardware processor to perform the The method includes:

[0069] 2. Determining whether the output power schedule satisfies all the loads in the charging schedule; In response to determining that the output power schedule does not satisfy all of the loads in the charging schedule, adjusting a charging schedule for the one or more loads based on a priority assigned to the one or more loads; initiating a re-execution of the economic dispatch application using the adjusted charging schedule, followed by at least one additional iteration; If it is determined that the output power schedule satisfies all the loads in the charging schedule, output the output power schedule as a final power schedule, and a schedule of power generation by distributed energy resources and charging of the loads at the charging station is based on the final power schedule. Use at least one hardware processor to perform the 2. The method of embodiment 1, further comprising:

[0070] 3. The method of aspect 2, wherein modifying the charging schedule includes reducing an amount that at least one load having a lower priority than at least one other load is charged.

[0071] 4. The method of aspect 2, wherein modifying the charging schedule includes shifting a time at which the at least one load is charged.

[0072] 5. The method of embodiment 2, wherein modifying the charging schedule for one or more loads based on the priority assigned to the one or more loads includes adjusting the charge amount or charge time of each of the one or more loads to prioritize critical loads over non-critical loads.

[0073] 6. The method of aspect 1, wherein the load at the charging station includes an electric vehicle. 7. The method of aspect 1, wherein the one or more distributed energy resources include one or more of a solar generator, a wind generator, a fuel cell, a thermal power plant, a hydroelectric power plant, a gasoline generator, or a battery.

[0074] 8. The method of aspect 1, wherein scheduling power generation by distributed energy resources includes controlling at least one of the one or more distributed energy resources to output power during one or more scheduled time periods and not output power outside the one or more scheduled time periods.

[0075] 9. The method of aspect 1, wherein scheduling charging of a load at a charging location includes controlling at least one charging station to output power to a connected load during one or more scheduled time periods and not output power outside of the one or more scheduled time periods.

[0076] 10. The method of aspect 1, wherein the at least one constraint for at least one node in the power distribution network defines a voltage range within which the voltage of the at least one node must be maintained across all changes in power set point during the power schedule.

[0077] 11. The method of aspect 1, wherein the violation is a violation of a grid code that defines requirements that the charging location must meet.

[0078] 12. The method of aspect 1, wherein the simulation includes a load flow analysis on a power distribution network model.

[0079] 13. The method of aspect 12, wherein the power schedule includes set points for one or more nodes in the power distribution network model, and the load flow analysis is performed for each of the set points in the power schedule.

[0080] 14. The method of aspect 1, wherein the power generation and charging of the load are further based on a charging schedule.

[0081] 15. The method of aspect 1, wherein the violation comprises a voltage violation or a current violation. 16. At least one hardware processor; Software and wherein the software, when executed by at least one hardware processor, For each of the one or more iterations, receiving a power schedule from an economic dispatch application for a charging station comprising one or more distributed energy resources, the power schedule specifying power to be output from the one or more distributed energy resources to service a charging schedule for a load at the charging station; simulating a power schedule on a distribution network model of the charging station, to determine whether at least one node in the distribution network model generates a violation during the simulation; in response to determining that at least one node in the electric power distribution network model generates a violation during the simulation; generating a constraint for at least one node in the power distribution network model that is determined to cause a violation during simulation; initiating a re-execution of the economic dispatch application, updated with the generated constraints, to generate a new power schedule for the next iteration; and outputting a power schedule if no node in the power distribution network model is determined to cause a violation during the simulation; Scheduling power generation by distributed energy resources and charging of loads at charging stations based on the output power schedule; 2. An energy management system configured to:

[0082] 17. The software, when executed by at least one hardware processor, Determining whether the output power schedule satisfies all the loads in the charging schedule; In response to determining that the output power schedule does not satisfy all of the loads in the charging schedule, adjusting a charging schedule for the one or more loads based on a priority assigned to the one or more loads; initiating a re-execution of the economic dispatch application using the adjusted charging schedule, followed by at least one additional iteration; If it is determined that the output power schedule satisfies all the loads in the charging schedule, output the output power schedule as a final power schedule, and a schedule of power generation by distributed energy resources and charging of the loads at the charging station is based on the final power schedule. 17. The energy management system of embodiment 16, further configured to:

[0083] 18. The energy management system of aspect 16, wherein the load at the charging station includes an electric vehicle and the one or more distributed energy resources include one or more of a solar generator, a wind turbine, a fuel cell, a thermal power plant, a hydroelectric power plant, a gasoline generator, or a battery.

[0084] 19. Scheduling generation of electricity by distributed energy resources includes controlling at least one of the one or more distributed energy resources to output power during one or more scheduled time periods and not output power outside the one or more scheduled time periods; The energy management system of embodiment 16, wherein scheduling the charging of the load at the charging station includes controlling at least one charging station to output power to the connected load during one or more scheduled time periods and not output power outside the one or more scheduled time periods.

[0085] 20. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by a processor, causing the processor to: For each of the one or more iterations, receiving a power schedule from an economic dispatch application for a charging station comprising one or more distributed energy resources, the power schedule specifying power to be output from the one or more distributed energy resources to service a charging schedule for a load at the charging station; simulating a power schedule on a distribution network model of the charging station, to determine whether at least one node in the distribution network model generates a violation during the simulation; in response to determining that at least one node in the electric power distribution network model generates a violation during the simulation; generating a constraint for at least one node in the power distribution network model that is determined to cause a violation during simulation; initiating a re-execution of the economic dispatch application, updated with the generated constraints, to generate a new power schedule for the next iteration; and outputting a power schedule if no node in the power distribution network model is determined to cause a violation during the simulation; Scheduling power generation by distributed energy resources and charging of loads at charging stations based on the output power schedule; A non-transitory computer-readable medium for causing

[0086] The above description of the disclosed embodiments is provided to enable those skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles described herein can be applied to other embodiments without departing from the spirit or scope of the present invention. It should therefore be understood that the description and drawings presented herein represent the presently preferred embodiments of the present invention, and thus represent the subject matter broadly contemplated by the present invention. It is further understood that the scope of the present invention fully encompasses other embodiments that may become apparent to those skilled in the art, and thus the scope of the present invention is not limited.

[0087] Combinations described herein such as "at least one of A, B, or C," "one or more of A, B, or C," "at least one of A, B, and C," "one or more of A, B, and C," and "A, B, C, or any combination thereof" include any combination of A, B, and / or C, and may include multiple As, multiple Bs, or multiple Cs. Specifically, combinations such as "at least one of A, B, or C," "one or more of A, B, or C," "at least one of A, B, and C," "one or more of A, B, and C," and "A, B, C, or any combination thereof" may be A only, B only, C only, A and B, A and C, B and C, or A and B and C, and any such combination may include one or more members of its components A, B, and / or C. For example, a combination of A and B may include one A and multiple Bs, multiple A and one B, or multiple A and multiple Bs.

Claims

1. For each of the one or more iterations, receiving a power schedule from an economic dispatch application for a charging station comprising one or more distributed energy resources, the power schedule specifying power to be output from the one or more distributed energy resources to service a charging schedule for loads at the charging station; simulating the power schedule on a power distribution network model of the charging station, to determine whether at least one node in the power distribution network model generates a violation during the simulation; in response to determining that at least one node in the power distribution network model generates a violation during the simulation; generating a constraint for the at least one node in the power distribution network model that is determined to cause a violation during the simulation; and initiating a re-execution of the economic dispatch application, updated with the generated constraints, to generate a new power schedule for a next iteration; and outputting the power schedule if it is determined that no node in the power distribution network model generates a violation during the simulation; scheduling power generation by the distributed energy resources and charging of the loads at the charging stations based on the output power schedule; using at least one hardware processor to perform The method comprises: determining whether the output power schedule satisfies all loads in the charging schedule; in response to determining that the output power schedule does not satisfy all loads in the charging schedule; adjusting the charging schedule for one or more loads based on priorities assigned to the one or more loads; initiating a re-execution of the economic dispatch application using the adjusted charging schedule, followed by at least one additional iteration; If it is determined that the output power schedule satisfies all the loads in the charging schedule, outputting the output power schedule as a final power schedule, wherein the scheduling of power generation by the distributed energy resources and charging of the loads at the charging station is based on the final power schedule. using said at least one hardware processor to perform The method further comprising:

2. The method of claim 1 , wherein modifying the charging schedule comprises decreasing an amount at least one load having a lower priority than at least one other load is charged.

3. The method of claim 1 , wherein modifying the charging schedule includes shifting a time at which at least one load is charged.

4. 2. The method of claim 1, wherein modifying the charging schedule for one or more loads based on priorities assigned to the one or more loads includes adjusting a charge amount or charge time of each of the one or more loads to prioritize critical loads over non-critical loads.

5. The method of claim 1 , wherein the load at the charging station includes an electric vehicle.

6. The method of claim 1 , wherein the one or more distributed energy resources include one or more of a solar generator, a wind generator, a fuel cell, a thermal power plant, a hydroelectric power plant, a gasoline generator, or a battery.

7. 2. The method of claim 1 , wherein scheduling generation of electricity by the distributed energy resources includes controlling at least one of the one or more distributed energy resources to output power during one or more scheduled time periods and not output power outside of the one or more scheduled time periods.

8. 2. The method of claim 1, wherein scheduling charging of a load at the charging location includes controlling at least one charging station to output power to a connected load during one or more scheduled time periods and not output power outside the one or more scheduled time periods.

9. 2. The method of claim 1, wherein at least one constraint for at least one node in the power distribution network defines a voltage range within which a voltage of the at least one node must be maintained across all changes in power setpoint during the power schedule.

10. The method of claim 1 , wherein the violation is a violation of a grid code that defines requirements that the charging site must meet.

11. The method of claim 1 , wherein the simulation includes a load flow analysis for the power distribution network model.

12. The method of claim 11 , wherein the power schedule includes set points for one or more nodes in the power distribution network model, and the load flow analysis is performed for each of the set points in the power schedule.

13. The method of claim 1 , wherein the generating electricity and charging of a load is further based on the charging schedule.

14. The method of claim 1 , wherein the violation comprises a voltage violation or a current violation.

15. at least one hardware processor; Software and wherein the software, when executed by the at least one hardware processor, For each of the one or more iterations, receiving a power schedule from an economic dispatch application for a charging station comprising one or more distributed energy resources, the power schedule specifying power to be output from the one or more distributed energy resources to service a charging schedule for loads at the charging station; simulating the power schedule on a power distribution network model of the charging station, to determine whether at least one node in the power distribution network model generates a violation during the simulation; in response to determining that at least one node in the power distribution network model generates a violation during the simulation; generating a constraint for the at least one node in the power distribution network model that is determined to cause a violation during the simulation; and initiating a re-execution of the economic dispatch application, updated with the generated constraints, to generate a new power schedule for a next iteration; and outputting the power schedule if it is determined that no node in the power distribution network model generates a violation during the simulation; scheduling power generation by the distributed energy resources and charging of the loads at the charging stations based on the output power schedule; configured to: The software, when executed by the at least one hardware processor, determining whether the output power schedule satisfies all loads in the charging schedule; in response to determining that the output power schedule does not satisfy all loads in the charging schedule; adjusting the charging schedule for one or more loads based on priorities assigned to the one or more loads; initiating a re-execution of the economic dispatch application using the adjusted charging schedule, followed by at least one additional iteration; If it is determined that the output power schedule satisfies all the loads in the charging schedule, outputting the output power schedule as a final power schedule, wherein the scheduling of power generation by the distributed energy resources and charging of the loads at the charging station is based on the final power schedule. The energy management system is further configured to:

16. 16. The energy management system of claim 15, wherein the loads at the charging station include electric vehicles and the one or more distributed energy resources include one or more of a solar generator, a wind generator, a fuel cell, a thermal power plant, a hydroelectric power plant, a gasoline generator, or a battery.

17. Scheduling generation of electricity by the distributed energy resources includes controlling at least one of the one or more distributed energy resources to output power during one or more scheduled time periods and not to output power outside the one or more scheduled time periods; 16. The energy management system of claim 15, wherein scheduling charging of a load at the charging location includes controlling at least one charging station to output power to a connected load during one or more scheduled time periods and not output power outside of the one or more scheduled time periods.

18. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to: For each of the one or more iterations, receiving a power schedule from an economic dispatch application for a charging station comprising one or more distributed energy resources, the power schedule specifying power to be output from the one or more distributed energy resources to service a charging schedule for loads at the charging station; simulating the power schedule on a power distribution network model of the charging station, to determine whether at least one node in the power distribution network model generates a violation during the simulation; in response to determining that at least one node in the power distribution network model generates a violation during the simulation; generating a constraint for the at least one node in the power distribution network model that is determined to cause a violation during the simulation; and initiating a re-execution of the economic dispatch application, updated with the generated constraints, to generate a new power schedule for a next iteration; and outputting the power schedule if it is determined that no node in the power distribution network model generates a violation during the simulation; scheduling power generation by the distributed energy resources and charging of the loads at the charging stations based on the output power schedule; Let them do so, The instructions, when executed by the processor, cause the processor to: determining whether the output power schedule satisfies all loads in the charging schedule; in response to determining that the output power schedule does not satisfy all loads in the charging schedule; adjusting the charging schedule for one or more loads based on priorities assigned to the one or more loads; initiating a re-execution of the economic dispatch application using the adjusted charging schedule, followed by at least one additional iteration; If it is determined that the output power schedule satisfies all the loads in the charging schedule, outputting the output power schedule as a final power schedule, wherein the scheduling of power generation by the distributed energy resources and charging of the loads at the charging station is based on the final power schedule. A non-transitory computer-readable medium further comprising:

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