Robust, cyber-secure, and collaborative, unintentional island detection for microgrids.

Abstract

Due to the unintentional islanding (UI) of a distributed energy resource (DER) circuit, the external area power system (EPS) of the DER circuit may remain energized. Therefore, UI detection methods have been developed to detect unintentional islanding and trigger a UI response. However, individual UI detection methods have various drawbacks. Accordingly, a consensus-based UI detection process is disclosed that optionally implements different UI detection methods to build a consensus from multiple UI detection sources. The redundancy in this consensus-based UI detection process provides robust, sensitive, selective, and cyber-secure UI detection for the entire DER circuit. For example, the consensus-based UI detection process can exclude or reduce non-detection areas, avoid false positives, and prevent cyberattacks.

Description

Technical Field

[0001] Government license right This invention was made with government support under Contract No. DE - OE0000896 awarded by the Department of Energy. The United States government has certain rights in this invention.

[0002] Background Field of the Invention Embodiments described herein generally relate to cooperative island detection, and more particularly to robust, sensitive, selective, and cyber - secure cooperative detection of unintentional islands (UI) for distributed energy resource (DER) circuits such as microgrids.

Background Art

[0003] Description of Related Art Grid codes generally require that interconnections with distributed energy resources accurately and quickly detect unintentional islands and cut off power. The new grid code extends this requirement to a single point of common coupling (PCC) between the microgrid and the main grid. For microgrids operating under the Institute of Electrical and Electronics Engineers (IEEE) standard (IEEE 1547-2018) or a similar grid code for interconnection and interoperability of distributed energy resources with relevant power grid interfaces, the UI response requirements are the same as for standalone distributed energy resources. IEEE 1547-2018 defines an unintentional island as an island scenario in which a DER circuit energizes a portion of the electrical power system (EPS) via a common coupling point. However, as used herein, the term “unintentional island” may be understood to refer to any scenario in which one or more distributed energy resources are unintentionally isolated from the rest of the power system and continue to supply power in a way that allows components of the power system to be energized.

[0004] Typical operation of a microgrid as an intentional island involves disconnection from an area EPS along a given electrical boundary (e.g., a common connection point). If an island forms outside these electrical boundaries so that both the microgrid and electrical system components are included within an area EPS that is not part of the microgrid, the microgrid must detect the unintentional island and cut off power to the non-microgrid components. For example, if a fault isolates a transformer located upstream of the microgrid and its common connection point from the main grid, the microgrid must quickly cut off power to the transformer.

[0005] Mango et al., "Overview of Anti-Islanding Algorithms for PV Systems. Part I: Passive Methods," 12th Int'l Power Electronics and Motion Control Conference, 2006, pp. 1878–1883, provides an overview of several existing anti-islanding algorithms. This disclosure relates to overcoming one or more problems found in state-of-the-art algorithms. [Overview of the project] [Means for solving the problem]

[0006] overview Accordingly, a system, method, and non-transient computer-readable medium for robust, highly sensitive, selective, cyber-secure, and collaborative UI detection for DER circuits including microgrids are disclosed. An object of the embodiments is to build consensus from multiple UI detection sources using one or more redundancy stages before triggering a UI response, such as a transition of an area EPS to an unpowered island. A further object of some embodiments is to eliminate or reduce non-detection areas within the UI detection method. A further object of some embodiments is to prevent false positives asserted by a UI detection source from triggering a UI response. A further object of some embodiments is to prevent a compromised UI detection source from supporting a cyberattack aimed at islandizing a DER circuit, such as a microgrid.

[0007] In one embodiment, a method is disclosed for detecting unintentional islanding (UI) in a distributed energy resource (DER) circuit, comprising: using at least one hardware processor to monitor transmissions from multiple UI detection sources to identify unintentional islanding indications from multiple UI detection sources; and determining that unintentional islanding in the DER circuit is not detected if unintentional islanding indications are identified from a number of multiple UI detection sources less than a consensus number during a time window, provided that the consensus number is greater than 1; and determining that unintentional islanding is detected if unintentional islanding indications are identified from a number of multiple UI detection sources equal to the consensus number during a time window.

[0008] Each transmission from one or more UI detection sources may include multiple measurements, and the method may identify unintentional islanding instructions in transmissions from one or more UI detection sources by determining, for each of the multiple measurements, whether the measurement satisfies its respective measurement threshold, determining that an unintentional islanding instruction has been identified in the transmission if a number of multiple measurements satisfies their respective measurement thresholds, provided that the number of thresholds is greater than 1, and determining that an unintentional islanding instruction has not been identified in the transmission if a number of multiple measurements does not satisfy their respective measurement thresholds. The multiple measurements may include positive and negative frequency change rates. The multiple measurements may include positive and negative frequency change rates. The multiple measurements may include positive and negative frequency change rates, positive and negative sequence change rates, positive and negative sequence change rates of the current, and negative sequence change rates of the current.

[0009] The method may include, using at least one hardware processor, determining whether a first UI detection source is local to or remote from a DER circuit when an unintentional islanding instruction is identified in a transmission from a first UI detection source among a plurality of UI detection sources; determining whether to perform detection of unintentional islanding of the DER circuit based on the location of the first UI detection source within the DER circuit when it is determined that the first UI detection source is local to the DER circuit; and performing detection of unintentional islanding of the DER circuit when it is determined that the first UI detection source is remote to the DER circuit. Determining whether to perform detection of unintentional islandization of a DER circuit based on the location of a first UI detection source in the DER circuit may include determining whether the first UI detection source is downstream of a segmenting device in the DER circuit, performing detection of unintentional islandization of the DER circuit if it is determined that the first UI detection source is not downstream of a segmenting device, determining whether the segmenting device is in an open state if it is determined that the segmenting device is not in an open state, performing detection of unintentional islandization of the DER circuit if it is determined that the segmenting device is in an open state, and not performing detection of unintentional islandization of the DER circuit if it is determined that the segmenting device is in an open state.

[0010] The method may further include using at least one hardware processor to start a timer representing a time window when an unintentional islanding instruction is identified in a transmission from a first UI detection source among multiple UI detection sources, performing detection of unintentional islanding of the DER circuit from the start of the timer, and blocking the transition of the DER circuit to an intentional island until, and until, an unintentional islanding of the DER circuit is detected before the timer expires.

[0011] The method may further include using at least one hardware processor to initiate a transition of a DER circuit to an intentional island in response to the detection of an unintentional islandization of the DER circuit. Initiating a transition of a DER circuit to an intentional island may include preparing a DER circuit for the intentional island. The method may further include using at least one hardware processor to open a common connection point with the DER circuit after preparing the DER circuit for the intentional island.

[0012] At least one of the multiple UI detection sources may generate instructions for unintentional islanding by utilizing a different UI detection method than another of the multiple UI detection sources.

[0013] Each of the transmissions from one or more of the multiple UI detection sources may include a binary value indicating whether or not unintentional islanding occurred.

[0014] Any of the above methods may be embodied individually or in any combination in executable software modules of processor-based systems such as servers, and / or in executable instructions stored on non-temporary computer-readable media.

[0015] Brief explanation of the drawing Details of the present invention, both in terms of its structure and operation, may be partially gathered by examining the accompanying drawings, in which similar reference numerals refer to similar parts. [Brief explanation of the drawing]

[0016] [Figure 1] An exemplary DER circuit in which one or more of the disclosed processes may be implemented according to one embodiment is illustrated. [Figure 2] An exemplary processing system in which one or more of the processes described herein may be performed, according to one embodiment, is illustrated. [Figure 3]An exemplary process for consensus-based UI detection according to one embodiment is illustrated. [Figure 4] An exemplary state diagram for consensus-based UI detection according to one embodiment is shown. [Figure 5] An exemplary timing of a consensus-based UI detection process according to one embodiment is illustrated. [Modes for carrying out the invention]

[0017] Detailed explanation In one embodiment, a system, method, and non-temporary computer-readable medium for robust, highly sensitive, selective, cyber-secure, and collaborative UI detection for DER circuits including a microgrid are disclosed. After reading this description, various alternative embodiments and methods for implementing the invention in alternative applications will become apparent to those skilled in the art. However, while various embodiments of the invention are described herein, it should be understood that these embodiments are presented for illustrative purposes only and are not limiting. Accordingly, this detailed description of various embodiments should not be construed as limiting the scope or breadth of the invention as set forth in the appended claims.

[0018] Conventional methods of UI detection can be grouped into three common categories: passive, active, and remote. Passive UI detection monitors specific anomalies that indicate island conditions in voltage and current waveform measurements. Examples of such measurements include undervoltage / overvoltage, rate of change of frequency (ROCOF), and voltage vector shift (VVS). Generally, these passive UI detection methods work because parameters such as voltage, frequency, and phase are disturbed immediately after the loss of connectivity to a rigid, high-inertia grid. While passive UI detection methods are easy to implement, they have two major drawbacks.

[0019] The first drawback of the passive UI detection method is the existence of a non-detection zone (NDZ). The non-detection zone is the range of the net active power load and reactive power load that cannot detect the island state. For example, in an islanded DER circuit, the active power load and reactive power load are almost balanced by the DER power source, and little power is exchanged with the area EPS. As a result, when an island is formed, there is no significant change in the frequency or phase of the voltage waveform in the islanded DER circuit.

[0020] The second drawback of the passive UI detection method is nuisance tripping. Nuisance tripping refers to a scenario where an island is falsely indicated because the measured value exceeds the threshold used to detect unintentional islanding as a result of a non-islanding event. For example, a sudden large change in the load within a microgrid can cause a large change in voltage, thereby accidentally triggering UI detection. Nuisance tripping can lead to a cascade effect, which can have an adverse impact on the area EPS, as in the case of the 2016 Blue Cut fire event in Southern California. IEEE 1547-2018 addresses nuisance tripping by setting ride-through requirements for some common passive UI indicators (e.g., ROCOF and VVS). Under conditions where ride-through is required, nuisance tripping is not permitted.

[0021] In the active UI detection method, the distributed energy resource controls the voltage and / or current of its terminal that competes with the area EPS. Under normal conditions, since the distributed energy resource is very small relative to the bulk grid, this competition does not affect the area EPS. However, when the distributed energy resource is islanded, this competition causes the voltage waveform to deviate from its normal operation and quickly exceed a certain threshold. Examples of active UI detection include active frequency drift, Sandia frequency drift, impedance measurement, and reactive power control.

[0022] In active frequency drift, the distributed energy resource distorts its output current, and as a result, one cycle of the current waveform becomes shorter than the grid voltage period. When the distributed energy resource is islanded, the short current cycle rapidly increases the island frequency to exceed the measurement threshold. Therefore, when the island frequency exceeds the measurement threshold, there may be an indication of unintentional islanding.

[0023] The Sandia frequency drift improves the active frequency drift by adding a feedback loop where the chopping coefficient is a function of frequency. The Sandia frequency drift eliminates the non-detection region of the active frequency drift by rapidly driving the island frequency to the measurement threshold when the islanding causes a small frequency deviation. Therefore, again, when the island frequency exceeds the measurement threshold, there may be an indication of unintentional islanding. In impedance measurement, the distributed energy resource perturbs its output current signal. When the corresponding perturbation is measured within the voltage signal, the distributed energy resource is islanded. Therefore, when the corresponding perturbation is measured in the voltage signal, there may be an indication of unintentional islanding.

[0024] During operation, when the distributed energy resource generates reactive power exceeding the local reactive power demand, the excess is exported to the grid through the common coupling point. In the case of islanding, this excess reactive power can no longer be measured at the common coupling point. Therefore, in reactive power control, when the difference between the predicted reactive power and the actual reactive power at the common coupling point exceeds the measurement threshold, there may be an indication of unintentional islanding.

[0025] Active UI detection methods generally have small or no undetected areas, but still present potential problems with power quality. This is especially true in EPS with high DER penetration. In this case, many distributed energy resources, each independently injecting strain, can cause problems, and the effectiveness of the UI detection method is also reduced. Furthermore, active UI detection methods can only be implemented by the distributed energy resources themselves, as other components (e.g., relays, microgrid controllers, etc.) cannot directly control the voltage or frequency waveform.

[0026] Remote UI detection methods are based on communication between distributed energy resources or microgrids and upstream management systems such as area EPS Supervisory Control and Data Acquisition (SCADA) systems. Examples of remote UI detection methods include power line carrier signals and transport trips. While remote UI detection methods can be effective, they are potentially slower and require costly communication overhead compared to UI detection methods that are specific to DER equipment and therefore cost-free for area EPS operators.

[0027] Figure 1 illustrates an exemplary DER circuit 130 in which one or more of the disclosed processes may be implemented according to one embodiment. The grid 110 may be electrically connected to the DER circuit 130 via a common connection point 140. A transformer 120 may be present between the grid 110 and the common connection point 140 to convert the voltage levels between the grid 110 and the DER circuit 130. The common connection point 140 may include a circuit breaker 142 configured to switch between a closed state in which the DER circuit 130 is electrically connected to the grid 110 and an open state in which the DER circuit 130 is electrically disconnected from the grid 110 and the area EPS (e.g., comprising the transformer 120), or "islanded".

[0028] The DER circuit 130 may comprise one or more distributed energy resources 150 (e.g., 150A, 150B, and 150C) and one or more loads 160 (e.g., 160A, 160B, 160C, 160D, and 160E). Examples of distributed energy resources 150 include, but are not limited to, photovoltaics, synchronous generators, gas turbines, wind turbines, biomass generators, fuel cells, battery energy storage systems (BESS), electric vehicles, and other things that can generate and / or supply electricity. Examples of loads 160 may include electric vehicles, electrical appliances, machinery, and other things that consume electricity. The DER circuit 130 may comprise different types of distributed energy resources 150, or may consist of the same type of distributed energy resources 150. Similarly, the DER circuit 130 may comprise different types of loads 160, or may consist of the same type of loads 160.

[0029] Multiple UI detection sources 170 (e.g., 170A, 170B, 170C, 170D, and 170E) may be distributed locally within the DER circuit 130 (e.g., 170B-170E) and / or remotely outside the DER circuit 130 (e.g., 170A). Each UI detection source 170 may comprise a device designed to continuously or sequentially measure one or more parameters at a location within the electrical circuit. For example, UI detection source 170A measures a parameter at a point between the transformer 120 and the common junction 140, and UI detection source 170B measures a parameter at a point on the other side of the common junction 140, between the common junction 140 and the rest of the DER circuit 130. Other UI detection sources 170 (e.g., 170C, 170D, and 170E) may be distributed throughout the rest of the DER circuit 130. Each UI detection source 170 may measure one or more parameters at its respective location, the same as all other UI detection sources 170, or it may measure one or more sets of parameters different from one or more of the other UI detection sources 170. Similarly, each UI detection source 170 may use the same UI detection method, or it may use a different UI detection method from one or more of the other UI detection sources 170. The UI detection source 170 may be any device capable of measuring and outputting parameter values, including microgrid controllers, relays, distributed energy resources 150, and devices dedicated to detecting unintentional islands.

[0030] Each UI detection source 170 may communicate with the controller 190. For example, each UI detection source 170 may send messages or signals to the controller 190 directly or indirectly via wired or wireless communication. For example, each of the UI detection source 170 and the controller 190 may be connected to a network, and the UI detection source 170 may transmit to the controller 190 via the network. Communication between the UI detection source 170 and the controller 190 may be carried out using a digital communication protocol such as Distributed Network Protocol 3 (DNP3) or the International Electrotechnical Commission (IEC) 61850 standard, or may be based on simple digital or analog input / output. The UI detection source 170 may transmit the values ​​of each measured parameter continuously (e.g., periodically at predetermined intervals), sequentially, or in response to a trigger event. A trigger event may include a request from the controller 190, or the detection of local unintentional islanding in the UI detection source 170 based on the measured parameter. Alternatively, the UI detection source 170 may transmit only when unintentional islanding is detected locally at the UI detection source 170, or it may continuously or sequentially transmit a binary indication of whether unintentional islanding has been detected locally at the UI detection source 170. In other words, the UI detection source 170 may simply transmit a message or signal indicating that unintentional islanding has been detected without including any specific measured parameters. Another alternative is that the UI detection source 170 may report the difference between the measured parameter and its respective measurement threshold, instead of the value of the measured parameter itself. This difference value represents the severity of the measured parameter. Different UI detection sources 170 may utilize different types of these communications, and the controller 190 may be configured to receive and process each type of communication.

[0031] The DER circuit 130 may include one or more segmenting devices 180. Each segmenting device 180 may be configured to switch between a closed state in which two or more segments of the DER circuit 130 are electrically connected to each other, and an open state in which two or more segments of the DER circuit 130 are electrically disconnected or segmented to each other. When the segmenting device 180 is in the open state, local islands may be formed within the DER circuit 130. Examples of segmenting devices 180 include reclosers and circuit breakers.

[0032] Each segmenting device 180 may communicate with the controller 190. For example, each segmenting device 180 may send messages or signals to the controller 190 directly or indirectly via wired or wireless communication. For example, each of the segmenting devices 180 and the controller 190 may be connected to a network, and the segmenting devices 180 may send messages to the controller 190 via the network. The segmenting device 180 may send status indications to the controller 190, such as whether the segmenting device is in a closed or open state, so that the controller 190 can form decisions based on the state of the segmenting device 180.

[0033] As described elsewhere in this specification, a controller 190, which may be included in the SCADA system of the DER circuit 130, monitors transmissions from the UI detection source 170 to identify unintentional islanding instructions from the UI detection source 170 and triggers a response based on a consensus scheme. In other words, the controller 190 may implement the UI detection and response processes described herein. The response may include controlling the PCC circuit breaker 142 to switch it to the open state, thereby disconnecting the DER circuit 130 from all external components, including the transformer 120. This control may be referred to as intentional islanding. Thus, the controller 190 may detect an unintentional island based on a consensus in the transmissions from the UI detection source 170 and transition the DER circuit to an intentional island accordingly. The controller 190 may communicate directly with the PCC circuit breaker 142, or it may communicate with the PCC circuit breaker 142 via a network to which both the controller 190 and the circuit breaker 142 are connected.

[0034] The DER circuit 130 is shown with a specific arrangement and number of components, including a PCC circuit breaker 142, distributed energy resources 150, loads 160, UI detection sources 170, segmentation devices 180, and a controller 190, but this is merely a non-limiting example for illustrative purposes. It should be understood that the DER circuit 130 may have any different arrangement and / or any different number of components. Furthermore, the DER circuit 130 may be connected to one or more other DER circuits, for example at point A. It should be understood that the DER circuit 130 may be a microgrid or may be included in a microgrid.

[0035] Figure 2 is a block diagram showing an exemplary wired or wireless system 200 that may be used in connection with various embodiments described herein. For example, system 200 may represent a controller 190, a UI detection source 170, and / or components of other processing devices described herein, either as one or more of the functions, processes, or methods described herein (e.g., for storing and / or executing software). System 200 can be a server or any conventional personal computer, or any other processor-enabled device capable of wired or wireless data communication. As will be apparent to those skilled in the art, other computer systems and / or architectures may also be used.

[0036] The system 200 preferably includes one or more processors 210. The processors 210 may include a central processing unit (CPU). Additional processors may be provided, such as a graphics processing unit (GPU), an auxiliary processor for managing inputs / outputs, an auxiliary processor for performing floating-point arithmetic, a dedicated microprocessor with an architecture suitable for high-speed execution of signal processing algorithms (e.g., a digital signal processor), a slave processor (e.g., a backend processor) subordinate to the main processing system, an additional microprocessor or controller for a dual or multiprocessor system, and / or a coprocessor. Such auxiliary processors may be separate processors or may be integrated with the processors 210. Examples of processors that may be used with System 200 include, but are not limited to, any processor available from Intel Corporation in Santa Clara, California (e.g., Pentium®, Core i7®, Xeon®, etc.), any processor available from Advanced Micro Devices, Incorporated (AMD) in Santa Clara, California, any processor available from Apple Inc. in Cupertino (e.g., A-series, M-series, etc.), any processor available from Samsung Electronics Co., Ltd. in Seoul, South Korea (e.g., Exynos®), and any processor available from NXP Semiconductors NV in Eindhoven, Netherlands.

[0037] The processor 210 is preferably connected to a communication bus 205. The communication bus 205 may include data channels to facilitate information transfer between storage and other peripheral components of the system 200. Furthermore, the communication bus 205 may provide a set of signals used for communication 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 bus architectures conforming to standards published by the Institute of Electrical and Electronics Engineers (IEEE), including, for example, industry standard architecture (ISA), extended industry standard architecture (EISA), micro channel architecture (MCA), peripheral component interconnect (PCI) local bus, and IEEE 696 / S-100, which includes the IEEE 488 general-purpose interface bus (GPIB).

[0038] The system 200 preferably includes main memory 215 and may also include secondary memory 220. The main memory 215 provides storage for instructions and data for programs executed on the processor 210, such as any of the software described herein. It should be understood that programs stored in memory and executed by the processor 210 may be written and / or compiled in any suitable language, including, but not limited to, C / C++, Java, JavaScript, Perl, Visual Basic, .NET, etc. The main memory 215 is typically 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, read-only memory (ROM), synchronous dynamic random access memory (SDRAM), Rambus dynamic random access memory (RDRAM), ferroelectric random access memory (FRAM®), etc.

[0039] The secondary memory 220 is a non-temporary computer-readable medium on which computer executable code (e.g., any of the software disclosed herein) and / or other data is stored. The computer software or data stored in the secondary memory 220 is read into the main memory 215 for execution by the processor 210. The secondary memory 220 may include, for example, 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 (block-oriented memory similar to EEPROM).

[0040] The secondary memory 220 may optionally include an internal medium 225 and / or removable media 230. The removable media 230 is read from and / or written to in any known way. The removable storage medium 230 may be, for example, a magnetic tape drive, a compact disc (CD) drive, a digital versatile disc (DVD) drive, another optical drive, a flash memory drive, and the like.

[0041] In alternative embodiments, the secondary memory 220 may include other similar means for enabling computer programs or other data or instructions to be loaded into the system 200. Such means may include, for example, a communication interface 240 that enables the transfer of software and data from an external storage medium 245 to the system 200. Examples of external storage media 245 include external hard disk drives, external optical drives, external magneto-optical drives, and the like.

[0042] As described above, system 200 may include a communication interface 240. The communication interface 240 enables the transfer of software and data between system 200 and external devices (e.g., printers), networks, or other information sources. For example, computer software or executable code may be transferred from a network server (e.g., platform 110) to system 200 via the communication interface 240. Examples of the communication interface 240 include a built-in network adapter, a network interface card (NIC), a Personal Computer Memory Card International Association (PCMCIA) network card, a CardBus network adapter, a wireless network adapter, a Universal Serial Bus (USB) network adapter, a modem, a wireless data card, a communication port, an infrared interface, an IEEE 1394 FireWire, and any other devices that can interface system 200 with a network or another computing device.The communication 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), and Serial Line Internet Protocol / Point-to-Point Protocol (SLIP / PPP), but may also implement customized or non-standard interface protocols.

[0043] The software and data transferred via the communication interface 240 are generally in the form of telecommunication signals 255. These signals 255 may be provided to the communication interface 240 via a communication channel 250. In one embodiment, the communication channel 250 may be a wired or wireless network or any various other communication link. The communication channel 250 carries the signals 255 and can be implemented using various wired or wireless means, including, to name just a few, wired or cable, optical fiber, conventional telephone lines, mobile phone links, wireless data communication links, radio frequency ("RF") links, or infrared links.

[0044] Computer executable code (e.g., computer programs such as the disclosed software) is stored in main memory 215 and / or secondary memory 220. Computer executable code can also be received via the communication interface 240 and stored in main memory 215 and / or secondary memory 220. When such computer programs are executed, they enable the system 200 to perform various functions of the embodiments disclosed elsewhere in this specification.

[0045] In this description, the term “computer-readable media” is used to refer to any non-temporary computer-readable storage media 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 and / or removable media 230), external storage media 245, and any peripheral devices (including network information servers or other network devices) that are communicatively coupled to the communication interface 240. These non-temporary computer-readable media are means for providing software and / or other data to System 200.

[0046] In embodiments implemented using software, the software may be stored on a computer-readable medium and loaded into the system 200 via a removable media 230, an I / O interface 235, or a communication interface 240. In such embodiments, the software is loaded into the system 200 in the form of telecommunications signals 255. When the software is executed by the processor 210, it preferably causes the processor 210 to perform one or more of the processes and functions described elsewhere in this specification.

[0047] In one embodiment, the I / O interface 235 provides an interface between one or more components of the system 200 and one or more input and / or output devices. Examples of input devices include, but are not limited to, sensors, keyboards, touchscreens 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, as in the case of a touch panel display (e.g., a smartphone, tablet, or other mobile device).

[0048] System 200 may also include optional radio communication components to facilitate radio communication over voice and / or data networks. The radio communication components include an antenna system 270, a radio system 265, and a baseband system 260. In System 200, radio frequency (RF) signals are transmitted and received wirelessly by the antenna system 270 under the control of the radio system 265.

[0049] In one embodiment, the antenna system 270 may include one or more antennas and one or more multiplexers (not shown) that perform a switching function to provide the antenna system 270 with a transmit signal path and a receive signal path. In the receive path, the received RF signal can be coupled from the multiplexer to a low-noise amplifier (not shown) that amplifies the received RF signal and transmits the amplified signal to the wireless system 265.

[0050] In an alternative embodiment, 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 a single integrated circuit (IC). The demodulator and modulator may be separate components. In the incoming path, the demodulator removes the RF carrier signal, leaving the baseband received audio signal transmitted from the radio system 265 to the baseband system 260.

[0051] The baseband system 260 may be communicatively coupled to the processor 210. The processor 210 may have access to 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 can be stored in the main memory 215 or the secondary memory 220. The computer program can also be received from the baseband processor 260 and stored in the main memory 210 or the secondary memory 220, or executed upon receipt. When such a computer program is executed, it can enable the system 200 to perform various functions of the disclosed embodiments.

[0052] Figure 3 illustrates an exemplary process 300 for consensus-based UI detection according to one embodiment. Process 300 may be implemented by a controller 190 in the monitoring and control layer of the DER circuit 130. Process 300 may also be implemented as software executed by one or more processors (e.g., 210) of the controller 190. Alternatively, process 300 may be implemented as a hardware component (e.g., an integrated circuit (IC), an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field-programmable gate array (FPGA) or other programmable logic device, discrete gates or transistor logic, etc.). To clearly illustrate hardware-software compatibility, various subprocesses of process 300 are described herein with respect to their functions. Whether such functions are implemented as hardware or software depends on the specific application and design constraints imposed on the overall system. Those skilled in the art can implement the described functions in various ways for each specific application. Furthermore, the grouping of functions within process 300 is for the sake of clarity. In alternative embodiments, these functions may be grouped differently. Furthermore, while process 300 is illustrated with a specific arrangement and order of subprocesses, process 300 may be implemented with fewer, more, or different subprocesses, as well as subprocesses in different arrangements and / or orders. Moreover, even if subprocesses are described or illustrated in a specific order, it should be understood that any subprocess that does not depend on the completion of another subprocess may run before, after, or in parallel with other independent subprocesses.

[0053] In subprocess 305, the controller 190 monitors transmissions from the UI detection source 170 to identify instructions for unintentional islanding within a transmission. In embodiments where the UI detection source 170 transmits only when unintentional islanding is detected, instructions for unintentional islanding may be identified whenever a transmission is received from the UI detection source 170. In embodiments where the UI detection source 170 continuously or sequentially transmits a binary value indicating the presence or absence of unintentional islanding, instructions for unintentional islanding may be identified whenever the binary value indicates the presence of unintentional islanding. In embodiments where the UI detection source 170 continuously or sequentially transmits values ​​for one or more parameters, instructions for unintentional islanding may be identified whenever a transmission containing a parameter that satisfies one or more criteria is received from the UI detection source 170. For example, if the UI detection source 170 transmits a single parameter, unintentional islanding may be identified from the transmission if the parameter value satisfies a threshold (e.g., above or below the threshold, depending on the parameter). If the UI detection source 170 transmits multiple parameters, unintentional islanding may be identified from the transmission if each of the parameter values ​​of a threshold number or threshold percentage satisfies its respective threshold. It should be understood that there are many other means by which instructions for unintentional islanding can be expressed and identified in a transmission, and the disclosed embodiments do not depend on any particular means. If a first instruction is identified (i.e., "Yes" in subprocess 305), process 300 proceeds to subprocess 310. Otherwise, if a first instruction has not yet been identified (i.e., "No" in subprocess 305), process 300 continues to wait for a first instruction in subprocess 305.

[0054] In subprocess 310, the controller 190 determines whether a first instruction for unintentional islanding, identified in subprocess 305, has been received from a remote UI detection source 170. The remote UI detection source 170 may be any UI detection source 170 outside the DER circuit 130, such as UI detection source 170A between the grid 110 and the common connection point 140, or a UI detection source within or associated with the grid 110 (e.g., transmitted by the utility distribution control system). In contrast, the local UI detection source 170 may be any UI detection source 170 inside the DER circuit 130, such as UI detection sources 170B-170E. An instruction for unintentional islanding from a remote UI detection source 170 indicates an external island, while an instruction for unintentional islanding from a local UI detection source 170 may be the result of another event, such as a trip of a segmentation device 180 within the DER circuit 130, which does not require the entire DER circuit 130 to transition to an intentional island. If the segmentation device 180 switches to an open state to form an internal island, for example (as a protective action in response to a non-UI event), this may cause UI detection sources 170D and 170E downstream of the segmentation device 180 (i.e., on the other side of the segmentation device 180 as a common coupling point 140) to incorrectly indicate unintentional islanding of the DER circuit 130. If a first indication of unintentional islanding is received from the local UI detection source 170 (i.e., "No" in subprocess 310), process 300 proceeds to subprocess 315. If, instead, a first indication of unintentional islanding is received from the remote UI detection source 170 (i.e., "Yes" in subprocess 310), process 300 proceeds to subprocess 330.

[0055] In subprocess 315, the controller 190 determines whether the first instruction for unintentional islanding, identified in subprocess 305, was received from a local UI detection source 170 downstream of the segmentation device 180. The controller 190 may have, or have access to, a memory (e.g., 215 or 220) that stores a representation of the topology of the DER circuit 130. As an example, the topology representation may include identifiers for all UI detection sources 170 downstream of the segmentation device 180. In the illustrated example, UI detection sources 170D and 170E are downstream of the segmentation device 180, while UI detection sources 170A, 170B, and 170C are upstream of the segmentation device 180. Regardless of the particular representation, the controller 190 may access the topology representation to determine whether the UI detection source 170 from which the first instruction for unintentional islanding was received is downstream of the segmentation device 180. If the first instruction is received from a local UI detection source 170 located downstream of the segmentation device 180 (i.e., "Yes" in subprocess 315), process 300 proceeds to subprocess 320. Otherwise, if the first instruction is received from a local UI detection source 170 that is not located downstream of the segmentation device 180 (i.e., "No" in subprocess 315), process 300 proceeds to subprocess 330.

[0056] In subprocess 320, the controller 190 determines whether the segmenting device 180, which is upstream of the UI detection source 170 from which the first instruction for unintentional islanding was received, is in an open state. If the segmenting device 180 is in an open state (i.e., "Yes" in subprocess 320), process 300 proceeds to subprocess 325. In this case, the DER circuit 130 engages in normal protective operation without external islanding. In other words, the controller 190 stops the consensus algorithm when it becomes clear that the first instruction for unintentional islanding is an internal event. On the other hand, if the segmenting device 180 is in a closed state (i.e., "No" in subprocess 320), process 300 proceeds to subprocess 330.

[0057] In subprocess 325, the controller 190 resets the consensus-based UI detection function without initiating a UI response. In other words, the first instruction for unintentional islanding identified in a transmission from the UI detection source 170 downstream of the open segmentation device 180 is ignored or forgotten. The controller 190 returns to subprocess 305 and monitors transmissions from the UI detection source 170 for a new first instruction for unintentional islanding.

[0058] In subprocess 330, the controller 190 may, if necessary, block trips based on a first instruction for unintentional islanding. For example, if there is another mechanism within the DER circuit 130 (e.g., within the SCADA system of the DER circuit 130, within individual UI detection sources 170, etc.) configured to trigger a control, such as a trip of the PCC circuit breaker 142, based on a single instruction for unintentional islanding or on detection of unintentional islanding at a single UI detection source 170, the controller 190 may suppress or override this mechanism or control. For example, the controller 190 may issue a block command to all UI detection sources 170 that suppresses any control function so that none of the individual UI detection sources 170 trigger a control when a first instruction for unintentional islanding is received. Thus, no UI-based trips occur in the DER circuit 130 until the controller 190 detects unintentional islanding based on consensus. In other words, the DER circuit 130 continues to operate normally until process 300 detects unintentional islanding based on consensus. In particular, if the first indication of unintentional islanding is a false positive or a malicious cyberattack, the subprocess 330 prevents the false positive or cyberattack from triggering control within the DER circuit 130. In embodiments where the controller 190 is the sole mechanism for triggering such control, the subprocess 330 may be omitted.

[0059] Subprocess 330 may be particularly applicable when the distributed energy resource 150 includes an embedded UI detection function. For example, islanding prevention is a standard feature in modern distributed energy resources 150, but is typically located internally without an exposed communication interface to an external system. Therefore, it may be impossible for the controller 190 to access UI detection measurements and signals within the distributed energy resource 150. In other words, the controller 190 may not be able to utilize the UI detection function of the distributed energy resource 150 in its consensus algorithm. In this case, the UI detection function of the distributed energy resource 150 should be completely blocked to solve at least two problems. Firstly, while the islanding prevention function inside the distributed energy resource 150 is fast and autonomous, the consensus algorithm relies on some delay between the first instance of UI detection and the power cut-off to build consensus. Subprocess 330 may prevent the distributed energy resource 150 from cutting off power until a consensus is reached, and until a consensus is reached. Secondly, since the distributed energy resources 150 can control their voltage and current waveforms, they are more likely to use active UI detection methods. However, without a connection to a rigid, high-inertia grid 110 to absorb or attenuate the waveform distortion introduced by the active UI detection methods, the power quality in the islanded DER circuit 130 may degrade. By blocking these active UI detection methods, the subprocess 330 may prevent this degradation of power quality.

[0060] In subprocess 335, controller 190 starts a timer to determine when a predetermined time window has expired, starting from the time the first instruction for unintentional islanding was received. Furthermore, in subprocess 340, a counter is initialized (for example, to a value of 1, representing the receipt of the first instruction for unintentional islanding). Any additional instructions for unintentional islanding are counted to build consensus until the timer expires. If the timer expires without a consensus being reached (i.e., "Yes" in subprocess 345), process 300 proceeds to subprocess 325 to reset the consensus-based UI detection function. Otherwise, if the timer has not yet expired (i.e., "No" in subprocess 345), process 300 continues to wait for consensus in subprocess 350.

[0061] In subprocess 350, controller 190 monitors transmissions from UI detection source 170 to identify new instructions for unintentional islanding within a transmission. It should be understood that transmission monitoring in subprocess 350 may be identical or similar to transmission monitoring in subprocess 305, except that receiving a new instruction in subprocess 350 adds to the consensus building, whereas receiving a new instruction in subprocess 305 initiates consensus building. If a new instruction is identified (i.e., "Yes" in subprocess 350), controller 190 increments a counter in subprocess 355 and proceeds to subprocess 360. Otherwise, if no new instruction has yet been identified (i.e., "No" in subprocess 350), process 300 continues to wait either for the timer to expire or for consensus to be reached. In one embodiment, the incrementing of the counter may be replaced by a more complex calculation that combines, for example, expressions of severity within an instruction (e.g., the difference between the measured value and each measured threshold) to form an aggregate or composite representation of the overall severity state.

[0062] In subprocess 360, the controller 190 determines whether a consensus has been reached. This determination in subprocess 360 may utilize one of several potential schemes for building consensus (i.e., more than one indication of unintentional islanding) before detecting an unintentional island. Some such consensus-based schemes are described below. However, it should be understood that the schemes described are not limiting, and any different consensus-based schemes may be utilized in subprocess 360. The advantages of the disclosed embodiments are that they require identifying multiple indications of unintentional islanding before implementing any control that would interfere with the normal operation of the DER circuit 130 (e.g., tripping the PCC circuit breaker 142), thereby mitigating or reducing the impact of false positives or cyberattacks on the DER circuit 130. Thus, in each scheme, an unintentional islanding is not detected while fewer than a consensus number of indications are received from the UI detection source 170 and / or while fewer than a consensus number of indications are received from the UI detection source 170. Conversely, unintentional islanding is detected when instructions are received from the consensus number UI detection source 170 and / or when instructions for the consensus number are received from the UI detection source 170. This consensus number may be determined from a predetermined count, percentage, etc., and can be set according to specific design goals of the implementation (e.g., desired confidence level). However, it should be understood that the consensus number should be set to require more than one UI detection source 170 and / or more than one instructions.

[0063] In the first method, a consensus may be reached (i.e., "Yes" in subprocess 360) when unintentional islanding instructions are received from UI detection sources 170 with different threshold numbers or threshold percentages. In the illustrated example, there are five UI detection sources 170A, 170B, 170C, 170D, and 170E. In this case, the counter may be incremented each time a new instruction is identified from a UI detection source 170 that was not previously visible. If the threshold number is 3 (or the threshold percentage is 60%), a consensus is reached when the counter reaches 3. This is an example of a one-stage consensus-based method.

[0064] In the second method, a consensus may be reached (i.e., "Yes" in subprocess 360) when instructions for unintentional islanding of a threshold number or threshold percentage are received. This method may be applicable when a single UI detection source 170 transmits measurements of one or more parameters, each of which may individually indicate unintentional islanding. For example, measurements of parameters that satisfy their respective predetermined measurement thresholds may be identified as instructions for unintentional islanding. In the illustrated example, there are five UI detection sources 170A, 170B, 170C, 170D, and 170E. Assume that each UI detection source 170 transmits measurements of four parameters, each of which may individually indicate unintentional islanding (e.g., if their respective thresholds are met), for a total of 20 instructions for potential unintentional islanding. In this case, the counter may be incremented each time a measurement from any UI detection source 170 satisfies its respective measurement threshold. If the threshold number is 15 (or the threshold percentage is 75%), consensus is reached when the counter reaches 15. This is another example of a one-stage consensus-based scheme.

[0065] In the third method, a consensus may be reached (i.e., "Yes" in subprocess 360) if an indication of unintentional islanding is identified from transmissions of UI detection source 170 with different threshold numbers or threshold percentages, and an indication of unintentional islanding is not identified in transmissions from UI detection source 170 unless the measurement of the threshold number or threshold percentage indicates an unintentional island. This method may be applicable when a single UI detection source 170 transmits measurements of multiple parameters, each of which may individually indicate unintentional islanding. For example, measurements of parameters that satisfy their respective predetermined measurement thresholds may be identified as indications of unintentional islanding. In the illustrated example, there are five UI detection sources 170A, 170B, 170C, 170D, and 170E. Assume that each UI detection source 170 transmits measurements of four parameters, each of which may individually indicate unintentional islanding (e.g., if their respective thresholds are met). In this case, the counter may be incremented each time that a previously unseen measurement of the number of thresholds from the UI detection source 170 meets its respective measurement threshold. If the threshold numbers for the different UI detection sources 170 are 3 (or the threshold percentage is 60%) and the measurement threshold number is 3 (or the threshold percentage is 75%), then when the counter reaches 3, consensus is reached, indicating that each of the three UI detection sources has reported at least 3 measurements that meet their respective measurement thresholds. This is an example of a two-stage consensus-based approach.

[0066] In particular, a UI detection source 170 that monitors measurements of multiple parameters may be configured to locally determine whether the measurements of threshold numbers or threshold percentages meet their respective thresholds. In this case, each UI detection source 170 may send an unintentional islanding instruction only if the UI detection source 170 locally determines that the measurements of threshold numbers or threshold percentages meet their respective thresholds. In this case, the controller 190 may determine that a consensus has been reached when the UI detection sources 170 for threshold numbers or threshold percentages send an unintentional islanding instruction. Technically, this is an example of a two-stage consensus-based scheme, but from the controller 190's perspective, this is a one-stage consensus-based scheme that can be implemented by the controller 190 in the same way as the scheme described earlier.

[0067] In the fourth method, a consensus may be reached (i.e., "Yes" in subprocess 360) if UI detection sources 170 with different threshold numbers or threshold percentages indicate unintentional islands, and the measured values ​​of the threshold numbers or threshold percentages across all UI detection sources 170 indicate unintentional islands. This method may be applicable when a single UI detection source 170 transmits measurements of multiple parameters, each of which may individually indicate unintentional islandization. For example, measurements of parameters that satisfy their respective predetermined measurement thresholds may be identified as indications of unintentional islandization. In the illustrated example, there are five UI detection sources 170A, 170B, 170C, 170D, and 170E. Assume that each UI detection source 170 transmits measurements of four parameters, each of which may individually indicate unintentional islandization (e.g., if their respective thresholds are met). In this case, there may be a first counter tracking the number of different UI detection sources 170 that have sent measurements indicating unintentional islanding, and a second counter tracking the total number of measurements indicating unintentional islanding sent by any UI detection source 170. If the threshold number of different UI detection sources 170 is 3 (or the threshold percentage is 60%), and the threshold number of measurements is 15 (or the threshold percentage is 75%), then consensus is reached when the first counter reaches 3 and the second counter reaches 15. This is another example of a two-stage consensus-based scheme.

[0068] In the fifth method, a consensus may be reached when an indication of unintentional islanding is identified from transmissions of UI detection sources 170 with different threshold numbers or threshold percentages (i.e., "Yes" in subprocess 360), where an indication of unintentional islanding is not identified in transmissions from UI detection sources 170 unless the measurement of the threshold number or threshold percentage indicates an unintentional island, and the measurement of the threshold number or threshold percentage across all UI detection sources 170 does not indicate an unintentional island. This method may be applicable when a single UI detection source 170 transmits measurements of multiple parameters, each of which may individually indicate unintentional islanding. For example, measurements of parameters that satisfy each predetermined measurement threshold may be identified as indications of unintentional islanding. In the illustrated example, there are five UI detection sources 170A, 170B, 170C, 170D, and 170E. Assume that each UI detection source 170 sends measurements of four parameters, each potentially indicating unintentional islanding individually (e.g., if each threshold is met). In this case, a first counter may be incremented each time a measurement of the threshold number from a UI detection source 170 that was not previously seen meets its respective measurement threshold, and a second counter may be incremented each time a measurement from any UI detection source 170 meets its respective threshold. If the threshold numbers for different UI detection sources 170 are 3 (or the threshold percentage is 60%), the threshold number of measurements from UI detection sources 170 is 3 (or the threshold percentage is 75%), and the threshold number of measurements across all UI detection sources 170 is 16 (or the threshold percentage is 80%), then consensus is reached when the first counter reaches 3 (indicating that each of the three UI detection sources has reported at least three measurements that meet their respective measurement thresholds) and the second counter reaches 16. This is an example of a three-stage consensus-based scheme.

[0069] In any embodiment where the UI detection sources 170 can utilize different UI detection methods, a hybrid approach may be used. For example, some UI detection sources 170 may transmit locally determined unintentional islanding instructions or measurements of a single parameter, while other UI detection sources 170 may transmit measurements of multiple parameters. In this case, the controller 190 may increment a counter each time it identifies an unintentional islanding instruction in a transmission, but the controller 190 may then identify each instruction differently depending on the UI detection source 170 from which the transmission was received. For example, if a locally determined unintentional islanding instruction is received, the controller 190 may increment the counter. If a transmission consisting of measurements of a single parameter is received, the controller 190 may increment the counter only if the measurements satisfy their respective measurement thresholds. If a transmission containing measurements of multiple parameters is received, the controller 190 may increment the counter only if the measurements satisfy their respective measurement thresholds, such as a certain number of thresholds or a threshold percentage. Regardless of how instructions from different UI detection sources 170 are identified, the controller 190 may determine that consensus has been reached when the counter reaches a consensus threshold (i.e., "Yes" in subprocess 360).

[0070] In the sixth method, consensus may be reached if the overall severity of the indications reaches a consensus threshold (i.e., "Yes" in subprocess 360). This method may be applicable if the UI detection source 170 transmits the difference between each measured value and its respective measurement threshold, representing the severity of the measured parameters. Alternatively, the UI detection source 170 may transmit measured values, and the controller 190 may calculate the difference between the measured values ​​and their respective measurement thresholds. In either case, the differences may be combined in some way, and the result may be compared to a consensus threshold. In particular, in this method, the counter is not a simple incremental counter. Rather, subprocess 355 may involve a more complex calculation that combines the aggregated difference or other representation of aggregated severity with the difference of the new indications of unintentional islanding identified in subprocess 350. As a result, consensus is not based on whether the UI detection source 170 agreed that unintentional islands have occurred. Rather, the consensus is based on whether the DER circuit 130 as a whole has reached a state of aggregated severity indicating unintentional islandization.

[0071] The sixth method can be further improved if the UI detection sources 170 utilize different UI detection methods. For example, consider two UI detection sources 170 that utilize two different UI detection methods, each having two different non-detection regions. At the point when an unintentional island occurs, the net power change may be within the non-detection region of the first UI detection source 170, but outside the non-detection region of the second UI detection source 170. In this case, the first UI detection source 170 does not provide instructions for unintentional islanding, while the second UI detection source 170 does. If the consensus algorithm only knows that the second UI detection source 170 indicates an unintentional island, while the first UI detection source 170 does not, then no UI response is triggered. However, if the consensus algorithm knows that the second UI detection source 170 shows measured parameters far above its respective measurement threshold, and the first UI detection source 170 shows measured parameters that are not exactly at its respective measurement threshold but are very close, then the aggregated severity state may be sufficient to trigger a UI response.

[0072] In any method utilizing measurements of one or more parameters, the parameters may include any parameters that may exhibit unintentional islands. Examples of such parameters include, but are not limited to, undervoltage / overvoltage, underfrequency / overfrequency, frequency change rate, voltage vector shift, frequency change rate with respect to power (df / dP), total harmonic distortion (THD), and rate of change of symmetric components. It should be understood that a single UI detection source 170 may measure multiple parameters, potentially all of these, as well as one or any combination of other parameters not specifically described herein.

[0073] In the absence of a rigid, high-inertia grid 110, the voltage and / or frequency of an unintentional island may rise or fall in relation to voltage undervoltage / voltage overvoltage or frequency undervoltage / frequency overvoltage. This is particularly likely when there is an imbalance between power generation by distributed energy resources 150 and the loads 160 inside the island. Therefore, an unintentional island may be indicated if the voltage or frequency exceeds a first measurement threshold or falls below a second measurement threshold.

[0074] With respect to the rate of frequency change, in the absence of a high-inertia grid 110, the frequency in an unintentional island may change rapidly due to an imbalance between the power generated by the distributed energy resources 150 and the loads 160 within the island. Therefore, if the rate of frequency change (i.e., the frequency derivative) exceeds a measurement threshold, an unintentional island may be indicated. Positive and negative rates of frequency change may be calculated as two separate parameters or as a single parameter.

[0075] With respect to voltage vector shifts, a sudden loss of the voltage reference from grid 110 can cause a step change in the phase of the voltage within the DER circuit 130. Therefore, if the voltage signal period is tracked, an unintentional island may be shown if the difference between the measured signal period and the reference exceeds a measurement threshold.

[0076] Regarding the rate of frequency change with respect to power, under normal grid connection conditions, changes in power output by the distributed energy resource 150 do not result in significant frequency changes within the DER circuit 130. However, without connection to the high-inertia grid 110, step changes in output power can result in large frequency changes. Therefore, the value of the rate of frequency change with respect to the rate of power change (i.e., df / dP) may be tracked, and if this value exceeds a measurement threshold, an unintentional island may be indicated.

[0077] With respect to total harmonic distortion, if the DER circuit 130 loses its connection to the grid 110, the high-frequency components of the current output by the distributed energy resource 150 may experience an increase in impedance, resulting in an increase in the total harmonic distortion of the voltage. Therefore, if the total harmonic distortion exceeds the measurement threshold, unintentional islands may be observed.

[0078] Regarding the rate of change of symmetric components (e.g., positive and negative sequences), unintentional islands may disrupt the symmetry of the three-phase current waveform. Therefore, if the rate of change of the magnitude of a positive or negative sequence component exceeds a measurement threshold, unintentional islands may be present.

[0079] Regardless of the specific method and / or measurement used, if a consensus is reached (i.e., "Yes" in subprocess 360), process 300 proceeds to subprocess 365. Otherwise, if a consensus is not reached (i.e., "No" in subprocess 360), process 300 continues to wait either for the timer to expire or for a consensus to be reached.

[0080] In subprocess 365, the controller 190 may initiate islanding preparations. Islanding preparations may include any steps necessary to transition the DER circuit 130 into an intentional island (i.e., before opening the PCC circuit breaker 142). Such steps may include, but are not limited to, configuring various components of the DER circuit 130, including managing the load 160 for islanding preparations, changing the control mode of the DER circuit 130 or one or more distributed energy resources 150 within the DER circuit 130 from grid following to grid formation, providing voltage and frequency references, and performing load shedding as necessary.

[0081] In subprocess 370, the controller 190 may initiate the transition of the PCC circuit breaker 142 from the closed state to the open state. For example, the controller 190 may communicate directly or indirectly (e.g., via a network) with the PCC circuit breaker 142 to send a control command or signal to open the PCC circuit breaker 142. After the PCC circuit breaker 142 transitions to the open state, which represents an intentional island, the DER circuit 130 may operate in islanding mode. Process 300 may terminate when the PCC circuit breaker 142 transitions back to the closed state, at which point process 300 may be restarted. In other words, process 300 may operate whenever the PCC circuit breaker 142 is in the closed state and may stop operating whenever the PCC circuit breaker 142 is in the open state.

[0082] In particular, when the PCC circuit breaker 142 is opened, the area EPS including the transformer 120 is no longer energized by the DER circuit 130 according to the applicable grid code. The DER circuit 130 may continue to operate in islanding mode.

[0083] Figure 4 illustrates an exemplary state diagram 400 for consensus-based UI detection according to one embodiment. The state diagram 400 may be implemented by a controller 190 in the monitoring and control layer of the DER circuit 130. Although the state diagram 400 is illustrated with a specific arrangement of states, the state diagram 400 may be implemented with fewer, more, or different states and different arrangements of states.

[0084] In state 410, the DER circuit 130 operates normally while connected to the area EPS (e.g., corresponding to subprocess 305). If an unintentional islanding instruction is received from the local UI detection source 170 during normal operation 410 (e.g., corresponding to "No" in subprocess 310), the controller 190 transitions to topology analysis 420 to find the source of the instruction (e.g., corresponding to subprocesses 315 and 320). If an unintentional islanding instruction is received from the remote UI detection source 170 during normal operation 410 (e.g., corresponding to "Yes" in subprocess 310), the controller 190 transitions to consensus algorithm 430 (e.g., corresponding to subprocesses 330-360). At this point, the controller 190 does not yet know whether an actual island has been formed, or whether the UI detection logic has been tripped for another reason, such as a false positive or a troublesome trip based on a cyberattack.

[0085] If the UI detection from the topology analysis 420 indicates an internal island, the controller 190 transitions to a protective operation 440, which may involve reconfiguring the DER circuit 130. Once the protective operation 440 is complete, the controller 190 transitions from protective operation 440 to normal operation 410. On the other hand, if the UI detection indicates an external island, the controller 190 transitions from topology analysis 420 to consensus algorithm 430.

[0086] If consensus is not reached within a predetermined time window from consensus algorithm 430 (for example, corresponding to "Yes" in subprocess 345), controller 190 transitions to return to normal operation 410. Otherwise, if consensus is reached within a predetermined time window (for example, corresponding to "Yes" in subprocess 360), controller 190 transitions from consensus algorithm 430 to islanding preparation 450 (for example, corresponding to subprocess 365). Once islanding preparation 450 is complete, controller 190 transitions from islanding preparation 450 to islanding operation 460 (for example, corresponding to subprocess 370), where DER circuit 130 is disconnected from area EPS. Once islanding operation 460 is complete (for example, electrical connection to grid 110 is restored), controller 190 transitions from islanding operation 460 to normal operation 410.

[0087] The grid code applicable to the DER circuit 130 may limit the time frame during which the DER circuit 130 must detect and respond to unintentional islands. For example, the IEEE 1547 standard requires the DER circuit 130 to detect and cut off power to an unintentional island within two seconds of its formation. Therefore, the controller 190 should be able to execute process 300 within this time constraint defined by the grid code.

[0088] Figure 5 illustrates exemplary timing of process 300 for consensus-based UI detection in one embodiment where the time constraint specified by the applicable grid code is 2 seconds. As shown, after the first instruction for intentional islanding is identified (e.g., subprocess 305), the controller 190 begins executing the consensus algorithm (e.g., including subprocesses 330-360). Upon reaching consensus (e.g., "Yes" in subprocess 360), the controller 190 begins the transition of the DER circuit to intentional islanding (e.g., subprocesses 365 and 370).

[0089] The consensus algorithm and transitions should be able to be performed within a specified period (e.g., 2 seconds). Therefore, the length of the timer used in the consensus algorithm (e.g., started in subprocess 335) should be set to be sufficient to capture enough instructions for unintentional islanding that satisfy the consensus threshold, but short enough to allow transitions to intentional islands within the applicable time constraints, taking into account latency in communication, processing, etc. For example, the timer length may be calculated by subtracting the maximum duration required for the UI detection source 170 to communicate instructions for unintentional islanding to the controller 190, subtracting the maximum duration required for transitions to intentional islands, and potentially subtracting buffer durations from the time constraint. For example, if the time constraint is 2 seconds, and communication between the UI detection source 170 and the controller 190 requires a maximum of 50 milliseconds, and the transition to an intentional island requires a maximum of 1 second, the timer length may be set to 950 milliseconds.

[0090] The disclosed consensus-based or collaborative UI detection offers several advantages over conventional UI detection based on individual UI detection sources (e.g., monitored only at common connection points). For example, a redundant, consensus-based approach using multiple UI detection sources 170 distributed across multiple locations inside and / or outside the DER circuit 130 to trigger a UI response when the number of positive indications reaches a threshold improves the sensitivity (i.e., the ability to correctly detect unintentional islanding regardless of the magnitude of the disturbance), selectivity (i.e., the ability to ignore disturbances not caused by unintentional islanding), and resilience to cyberattacks (i.e., the ability to ignore malicious false positives) of the DER circuit 130. Furthermore, in one embodiment, different types of UI detection sources 170 may be utilized to introduce diversity or robustness into the consensus-based UI detection process.

[0091] The sensitivity of any single UI detection method is limited by the UI detection method and the location of the UI detection source 170 within the DER circuit 130. Process 300 can improve the overall sensitivity of UI detection to the DER circuit 130 by utilizing multiple UI detection sources 170 and / or multiple parameters, thereby ensuring that the most sensitive UI detection method operates during UI detection for each given situation. For example, the use of multiple UI detection sources 170 and / or multiple parameters, which may have overlapping detection zones, effectively reduces or eliminates non-detection areas present in conventional passive UI detection methods. Thus, process 300 enables conventional passive UI detection methods to detect unintentional islands.

[0092] Events other than unintentional islanding can cause disturbances that may generate instructions for unintentional islanding under certain UI detection methods. For example, a voltage-based method may trip due to large changes in load, while a frequency-based method ignores the same disturbance. Process 300 can improve the selectivity of UI detection by utilizing multiple UI detection sources 170 and / or multiple parameters, thereby preventing such troublesome trips. In particular, a single false positive cannot trigger a UI response because consensus is required. The type and arrangement of the UI detection sources 170 may be chosen to prevent all such false positives from triggering a UI response. Thus, process 300 can prevent troublesome trips as required by the applicable grid code.

[0093] Process 300 can also improve the resilience of UI detection to cyberattacks. For example, the use of multiple UI detection sources 170 increases redundancy, preventing a compromised UI detection source 170 from triggering a UI response. In particular, the consensus requirement prevents a single or small set of compromised UI detection sources 170 from using false-positive instructions to trigger a UI response to the entire DER circuit 130. In other words, if a compromised UI detection source 170 generates a false positive attempt to trigger a UI response (e.g., to take the DER circuit 130 offline), Process 300 prevents the cyberattack by requiring that the unintentional islanding be confirmed by one or more different UI detection sources 170 before the UI response is triggered. For a cyberattack to succeed, a malicious actor would need to compromise a threshold number of UI detection sources 170. In particular, the cyber resilience of the DER circuit 130 is such that DER circuit 1 3 It may be scaled up by increasing the number of UI detection sources 170 within 0 and / or the threshold number of UI detection sources 170 required for consensus.

[0094] In particular, process 300 is also computationally inexpensive (i.e., does not require significant computational resources). Therefore, process 300 can be integrated into the existing controller 190 of the DER circuit 130. In addition, process 300 can be executed within the time constraints imposed by the applicable grid code. In experiments with several different scenarios, process 300 was able to detect true unintentional islands within 0.3 to 0.4 seconds, well within the 2-second time constraint imposed by IEEE 1547-2018, while successfully ignoring false positives.

[0095] As described elsewhere in this specification, the UI detection source 170 may measure one or more parameters. In one embodiment, one or more UI detection sources 170, potentially all of the above, measure several parameters such as a positive frequency rate change, a negative frequency rate change, a rate of change of a positive sequence component, and / or a rate of change of a negative sequence component. Each measured parameter represents a distinct UI detection function in which unintentional islands can be detected. In particular, each measured parameter may be compared to its respective measurement threshold, and if the measured parameter meets its respective measurement threshold (e.g., exceeds the threshold in the case of the four exemplary parameters above), it may be used to indicate the possibility of an unintentional island.

[0096] Each measurement threshold for each UI detection function (i.e., the measured parameter) may be adjusted to strike an appropriate balance between sensitivity and selectivity. In particular, different measurement thresholds may be used for different UI detection sources 170, for example, based on their location within the DER circuit 130. Furthermore, in schemes that require a measured number of thresholds or a threshold percentage to satisfy each measurement threshold, those thresholds may also be set to strike an appropriate balance between sensitivity and selectivity. Moreover, the consensus threshold number or threshold percentage of UI detection sources 170 from which instructions for unintentional islanding must be received before unintentional island detection may also be set to strike an appropriate balance between sensitivity, selectivity, and cyber resilience. In other words, there are multiple stages that can be adjusted based on experiments (e.g., simulations) and design goals (e.g., applicable time constraints) to strike an appropriate balance between sensitivity, selectivity, and / or cyber resilience.

[0097] The following table illustrates one specific example of measurement thresholds for different exemplary parameters (i.e., positive and negative frequency change rates, positive sequence current change rate, and negative sequence current change rate) measured by each of the UI detection sources 170A to 170E within the DER circuit 130.

[0098] [Table 1]

[0099] In one embodiment, different consensus algorithms may be used depending on one or more characteristics of the DER circuit 130 (e.g., load condition, net steady-state power, etc.). For example, if the net steady-state power of the intersection common connection point 140 is outside the entire undetectable region, a first consensus algorithm may be used in process 300, and if the net steady-state power of the intersection common connection point 140 is inside the entire undetectable region, a second consensus algorithm may be used in process 300. The entire undetectable region may be identified in advance through system studies of various undetectable regions in the passive UI detection method used by the UI detection source 170. The first and second consensus algorithms may differ in various respects, including, but are not limited to, whether trips are blocked in the subprocess 330, various measurement thresholds (e.g., different measurement thresholds based on load conditions), consensus thresholds, consensus-based methods, etc. For example, in the first consensus algorithm (i.e., used when power is outside the entire undetectable region), the internal active UI detection method of the distributed energy resource 150 may be blocked in subprocess 330, but in the second consensus algorithm (i.e., used when power is inside the entire undetectable region), subprocess 330 may be omitted so as not to cause blocking. Therefore, the distributed energy resource 150 may continue to exercise its internal active UI detection methods in situations where the passive UI detection method may not be able to detect unintentional islanding.

[0100] The above description of the disclosed embodiments is provided to enable those skilled in the art to construct or use the 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 invention. It should be understood that the descriptions and drawings presented herein represent currently preferred embodiments of the invention and, therefore, represent the subject matter broadly intended by the invention. It should be further understood that the scope of the invention fully encompasses other embodiments that may be readily apparent to those skilled in the art, and that the scope of the invention is not limited accordingly.

[0101] The 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 A's, multiple B's, or multiple C's. 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 constituent A, B, and / or C. For example, the combination of A and B may include one A and multiple B's, multiple A's and one B's, or multiple A's and multiple B's.

Claims

1. A method for detecting unintentional islanding (UI) of at least one distributed energy resource (DER) circuit, using at least one hardware processor, Monitoring transmissions from multiple UI detection sources to identify unintentional islandization instructions from the multiple UI detection sources, Detection of unintentional island formation in the aforementioned DER circuit, Determining that no unintentional islanding has been detected while unintentional islanding instructions have been identified from fewer than the consensus number of UI detection sources during the time window, provided that the consensus number is greater than 1, and If instructions for unintentional islanding are identified from the multiple UI detection sources of the consensus number during the time window, it is determined that unintentional islanding has been detected. to be carried out by Includes, Each of the transmissions from one or more of the plurality of UI detection sources includes a plurality of different types of measurements, and the method indicates unintentional islanding in the transmission from each of the one or more UI detection sources. For each of the aforementioned multiple measurement values, determine whether the measurement value satisfies the respective measurement threshold. The determination that an unintentional islanding instruction was identified in the transmission when the number of threshold values ​​of the plurality of measurements satisfies the respective measurement threshold, wherein the number of threshold values ​​is greater than 1, and If the multiple measurements of the threshold number do not satisfy the respective measurement threshold, it is determined that an unintentional islanding instruction is not identified in the transmission. A method that includes identifying by

2. The plurality of measured values Positive frequency change rate and negative frequency change rate, and / or The rate of change of the positive sequence component of the current and the rate of change of the negative sequence component of the current. The method according to claim 1, including the method described in claim 1.

3. The method according to claim 2, wherein the plurality of measured values ​​include positive and negative frequency change rates.

4. The method according to claim 2, wherein the plurality of measured values ​​include the rate of change of the positive sequence component of the current and the rate of change of the negative sequence component of the current.

5. The method according to claim 2, wherein the plurality of measured values ​​include a positive frequency change rate, a negative frequency change rate, a rate of change of the positive sequence component of the current, and a rate of change of the negative sequence component of the current.

6. If, using the at least one hardware processor, the instruction for unintentional islanding is identified in the transmission from the first UI detection source among the plurality of UI detection sources, Determining whether the first UI detection source is local to the DER circuit or remote from the DER circuit, If it is determined that the first UI detection source is local to the DER circuit, Based on the location of the first UI detection source within the DER circuit, it is determined whether to perform the detection of unintentional islandization of the DER circuit. If the first UI detection source is determined to be remote to the DER circuit, To perform the detection of unintentional islandization of the DER circuit and The method according to claim 1, including the method described in claim 1.

7. Based on the location of the first UI detection source within the DER circuit, it is determined whether to perform the detection of unintentional islandization of the DER circuit. To determine whether the first UI detection source is downstream of the segmentation device in the DER circuit, If it is determined that the first UI detection source is not downstream of the segmentation device, the detection of unintentional islandization of the DER circuit is performed, If it is determined that the first UI detection source is downstream of the segmentation device, Determine whether the segmenting device is in an open state. If it is determined that the segmentation device is not in the open state, the detection of unintentional islandization of the DER circuit is performed, and If the segmentation device is determined to be in the open state, the detection of unintentional islandization of the DER circuit will not be performed. The method according to claim 6, including the method described in claim 6.

8. If, using the at least one hardware processor, the instruction for unintentional islanding is identified in the transmission from the first UI detection source among the plurality of UI detection sources, The timer representing the time window is started, and the detection of unintentional islandization of the DER circuit is performed from the start of the timer, Unless an unintentional islandization of the DER circuit is detected before the timer expires, and until such detection occurs, the transition of the DER circuit to an intentional island is blocked. The method according to claim 1, further comprising:

9. The method according to claim 1, further comprising using the at least one hardware processor to initiate a transition of the DER circuit to an intentional island in response to detection of an unintentional islandization of the DER circuit.

10. The method according to claim 9, wherein initiating a transition of the DER circuit to an intentional island includes preparing the DER circuit for the intentional island.

11. The method according to claim 10, further comprising using the at least one hardware processor to prepare the DER circuit for the intentional island, and then opening a common connection point with the DER circuit.

12. The method according to claim 1, wherein at least one of the plurality of UI detection sources generates the instruction for unintentional islanding using a different UI detection method than another of the plurality of UI detection sources.

13. The method according to claim 1, wherein each of the transmissions from one or more of the plurality of UI detection sources includes a binary value indicating whether or not unintentional islanding occurred.

14. At least one hardware processor, When executed by the aforementioned at least one hardware processor, To monitor transmissions from multiple UI detection sources and identify unintentional islanding instructions from the multiple UI detection sources, Detection of unintentional islandization in distributed energy resource (DER) circuits, Determining that no unintentional islanding has been detected while unintentional islanding instructions have been identified from fewer than the consensus number of UI detection sources during the time window, provided that the consensus number is greater than 1, and If instructions for unintentional islanding are identified from the multiple UI detection sources of the consensus number during the time window, it is determined that unintentional islanding has been detected. Software configured to be implemented by Control system equipped with Equipped with, Each of the transmissions from one or more of the plurality of UI detection sources includes a plurality of different types of measurements, and the software provides instructions for unintentional islanding in the transmissions from each of the one or more UI detection sources. For each of the aforementioned multiple measurement values, determine whether the measurement value satisfies the respective measurement threshold. The determination that an unintentional islanding instruction was identified in the transmission when the number of threshold values ​​of the plurality of measurements satisfies the respective measurement threshold, wherein the number of threshold values ​​is greater than 1, and If the multiple measurements of the threshold number do not satisfy the respective measurement threshold, it is determined that an unintentional islanding instruction is not identified in the transmission. A system further configured to be identified by

15. The system according to claim 14, further comprising the plurality of UI detection sources.

16. The system according to claim 15, further comprising the DER circuit, wherein the plurality of UI detection sources are distributed to different locations relative to the DER circuit.

17. The system according to claim 16, wherein the DER circuit is a microgrid comprising one or more distributed energy resources.

18. The system according to claim 15, wherein at least one of the plurality of UI detection sources generates the instruction for unintentional islanding using a different UI detection method than another of the plurality of UI detection sources.

19. The plurality of measured values Positive frequency change rate and negative frequency change rate, and / or The rate of change of the positive sequence component of the current and the rate of change of the negative sequence component of the current. The system according to claim 14, including the system described in claim 14.

20. A non-temporary computer-readable medium on which instructions are stored, wherein when the instructions are executed by the processor, the processor receives Monitoring transmissions from multiple UI detection sources to identify unintentional islandization instructions from the multiple UI detection sources, Detection of unintentional islandization in distributed energy resource (DER) circuits, Determining that no unintentional islanding has been detected while unintentional islanding instructions have been identified from fewer than the consensus number of UI detection sources during the time window, provided that the consensus number is greater than 1, and If instructions for unintentional islanding are identified from the multiple UI detection sources of the consensus number during the time window, it is determined that unintentional islanding has been detected. To be implemented by A non-temporary computer-readable medium that enables the operation of [the process].

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