Multi-machine parallel black start method and device for energy storage system

Abstract

The application provides a multi-machine parallel black start method and device for an energy storage system, and relates to the technical field of smart power grids. The method comprises the following steps: after receiving a black start instruction, electrical data of a power supply grid is acquired, and it is determined whether the power supply grid is abnormal based on the electrical data of the power supply grid; if the power supply grid is abnormal, SOC data of the self device is used to construct a micro-grid system; after the micro-grid system is stable, device information is exchanged with other controllers, and master selection is performed according to the device information; the other controllers are other devices in the micro-grid system except the current controller; if the current controller is determined as a master, the master responsibility is performed to control the power supply of the micro-grid system; if the current controller is determined as a slave, the slave responsibility is performed and the instruction of the master is received. After the black start process is triggered, the application can prevent the whole black start process from stopping due to the failure of a single core control unit, and the reliability of the black start is improved.

Description

Technical Field

[0001] This invention relates to the technical field of smart grids, and in particular to a method and apparatus for black-starting multiple parallel units in an energy storage system. Background Technology

[0002] Multi-unit parallel black start refers to an emergency power supply technology where, after a nationwide power grid failure, multiple self-starting power units, without external grid support, rely on their own energy storage and auxiliary power supplies to start up. Through synchronized operation, these units are connected in parallel to gradually restore power to the regional load. Modern industrial parks, remote mining areas, island power supply systems, and new energy microgrids often utilize multiple distributed power sources working together. If a large-scale power outage cannot be quickly resolved through multi-unit parallel black start, it can lead to significant economic and safety losses, including production equipment shutdowns, critical load instability, and public service interruptions. Therefore, reliable and efficient multi-unit parallel black start capability is a core requirement for ensuring the stable operation of independent power supply systems and regional backup power sources.

[0003] Currently, most mainstream multi-unit parallel black start systems in the industry adopt a centralized collaborative black start scheme. The central controller uniformly issues start-up timing and voltage frequency adjustment commands to complete the self-start and no-load voltage building of a single unit in sequence, and then connects the units to the bus synchronously one by one. The central unit uniformly manages the power output of the entire network.

[0004] The multi-machine parallel black start control scheme in related technologies has obvious application defects: the black start operation depends on the central controller. When the central controller fails to work properly, the black start operation cannot be carried out normally, resulting in low reliability of the black start in related technologies. Summary of the Invention

[0005] This invention provides a method and apparatus for black start of multiple parallel units in an energy storage system, to solve the problem that black start cannot be performed normally when the central controller fails to work properly, resulting in low reliability of black start in related technologies.

[0006] In a first aspect, embodiments of the present invention provide a multi-machine parallel black-start method for an energy storage system, comprising: After receiving the black start command, the electrical data of the power grid is obtained, and the power grid is judged to be abnormal based on the electrical data of the power grid. If the power grid is abnormal, a microgrid system is constructed based on its own SOC data; After the microgrid system stabilizes, it exchanges device information with other controllers and performs a master election operation based on the device information; the other controllers are other devices in the microgrid system besides the current controller. If the current controller is determined to be the host, it performs the host responsibilities in order to control the power supply of the microgrid system; If the current controller is determined to be a slave, it performs slave functions and receives instructions from the master.

[0007] In one possible implementation, constructing a microgrid system based on its own SOC data includes: The system compares its own SOC data with a preset self-built network threshold. If its own SOC data exceeds the self-built network threshold, it generates first network construction data, builds a microgrid system based on the first network construction data, and sends the first network construction data to the other controllers. If the SOC data of the device exceeds the self-built network threshold, but receives the second network data sent by the other controller before generating the first network data, or if the SOC data of the device does not exceed the self-built network threshold, then the device receives the second network data sent by the other controller and integrates it into the microgrid system.

[0008] In one possible implementation, the execution host responsibilities include: The system baseline value adjustment amount of the microgrid system is determined, the load of the microgrid system in the next cycle is predicted and allocated, and when an abnormal operating condition report is received from the slave, the output weight is assigned to each slave.

[0009] In one possible implementation, the host's responsibilities also include sending a self-check health score to all the slaves, so that when the host's self-check health score is lower than a health threshold or the host fails to send a self-check health score to all the slaves, the slaves can re-elect a new host based on their self-check health score and their own election score.

[0010] In one possible implementation, the method further includes: When a communication anomaly occurs between the host and the slave, the host uses a frequency shift signaling layer cooperative mode to communicate with all the slaves. Meanwhile, the host sends UDP Probes to all the slave devices at a preset frequency. If it receives a reply at least twice in a row, the host switches back to consensus mode to communicate with all the slave devices.

[0011] In one possible implementation, determining the system reference value adjustment amount of the microgrid system includes: Receive frequency correction and voltage correction values ​​sent by each of the slave devices; The system reference value correction is calculated based on the frequency correction and the voltage correction, and then sent to the slave device.

[0012] In one possible implementation, predicting and allocating the next cycle load of the microgrid system includes: Obtain the historical active power of the load; The historical active power is input into a preset prediction model to obtain the load of the microgrid system in the next cycle. The next cycle load of the microgrid system is used to allocate the next cycle node load to each of the slave machines.

[0013] In one possible implementation, assigning output weights to each of the slave devices upon receiving an abnormal operating condition report from the slave device includes: Obtain the SOC status data and rated power of each slave device; Upon receiving an abnormal operating condition report from the slave device, the output weight of each slave device is calculated based on its SOC status data and rated power. Send the corresponding output weight to each of the slave devices.

[0014] In one possible implementation, the step of performing slave duties and receiving instructions from the master includes: Obtain its own electrical parameters and the electrical parameters of the microgrid system; Based on its own electrical parameters and the electrical parameters of the microgrid system, it calculates the frequency correction and voltage correction, and sends the frequency correction and voltage correction to the host. It obtains its own real-time output current, and calculates and updates its own virtual impedance in real time based on its own real-time output current. Receive and supply power according to the load assigned by the host for the next cycle; It determines whether it is experiencing abnormal operating conditions. If so, it sends an abnormal operating condition report to the host, receives the output weight assigned by the host, and adjusts its own load according to the output weight.

[0015] Secondly, embodiments of the present invention provide a multi-machine parallel black start device for an energy storage system, including at least one controller; The controller is used to acquire electrical data of the power grid after receiving a black start command, and determine whether the power grid is abnormal based on the electrical data of the power grid. If the power grid is abnormal, a microgrid system is constructed based on its own SOC data; After the microgrid system stabilizes, it exchanges device information with other controllers and performs a master election operation based on the device information; the other controllers are other devices in the microgrid system besides the current controller. If the current controller is determined to be the host, it performs the host responsibilities in order to control the power supply of the microgrid system; If the current controller is determined to be a slave, it performs slave functions and receives instructions from the master.

[0016] In this embodiment of the invention, after triggering the black start process, each device can independently collect grid electrical parameters and its own power status, autonomously determine the power supply fault condition, and prevent the entire black start process from stalling due to the failure of a single core control unit, thus improving the reliability of black start. Each device determines its network role based on its remaining power. Devices with sufficient power can autonomously output voltage signaling with micro-amplitude frequency shift characteristics to complete the microgrid system construction, while devices with insufficient power can actively identify external network signaling to smoothly integrate. The multi-device networking process does not require unified external command issuance, significantly shortening the time required for microgrid formation after power failure. After the microgrid system is running stably, all devices interactively self-check their health and election scores, autonomously selecting a leader to assume global control responsibilities, with the remaining devices acting as subordinate units executing corresponding commands. During leader election, the microgrid system will not be unable to operate stably due to the failure of a single device in the system, thus improving the stability of the microgrid system. Attached Figure Description

[0017] Figure 1 This is an application scenario diagram of the multi-machine parallel black start method for energy storage systems provided in the embodiments of the present invention; Figure 2 This is a flowchart illustrating the implementation of a multi-machine parallel black-start method for energy storage systems provided in this embodiment of the invention. Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0019] Figure 1 This diagram illustrates an application scenario of the multi-machine parallel black-start method for energy storage systems provided in this embodiment of the invention. Figure 1 As shown, the energy storage system includes multiple energy storage units, each of which includes a battery cluster, an energy storage converter, and a controller. The battery cluster is connected to the AC bus of the power grid through the energy storage converter. When the power grid is normally supplying power to the load, the energy storage system does not output power. Each battery cluster is equipped with a black start button. When the power grid malfunctions, the operator presses the black start button, and each controller executes the multi-unit parallel black start method for energy storage systems provided in this embodiment of the invention, controlling each battery cluster to supply power to the load.

[0020] See Figure 2The document illustrates a flowchart of the implementation of a multi-machine parallel black-start method for energy storage systems provided in an embodiment of the present invention, detailed below: A black-start method for multi-unit parallel operation in an energy storage system includes: S110. After receiving the black start command, obtain the electrical data of the power grid and determine whether the power grid is abnormal based on the electrical data.

[0021] In one embodiment, the black start instruction is for a worker to press a black start button. The electrical data of the power grid includes at least one of the supply voltage and supply frequency. When the supply voltage is below a voltage threshold and / or the supply frequency is below a frequency threshold, the power grid is determined to be abnormal.

[0022] S120. If the power grid is abnormal, construct a microgrid system based on the SOC data of its own equipment.

[0023] In one embodiment, S120 includes: The system compares its own SOC data with the preset self-built network threshold. If the SOC data of its own device exceeds the self-built network threshold, it generates the first network construction data, builds the microgrid system based on the first network construction data, and sends the first network construction data to other controllers.

[0024] If the SOC data of its own device exceeds the self-built network threshold and receives the second network data sent by other controllers before generating the first network data, or if the SOC data of its own device does not exceed the self-built network threshold, then it receives the second network data sent by other controllers and is integrated into the microgrid system.

[0025] For example, the first network data and the second network data are the same, both including voltage and micro-frequency shift signaling. When the black start button of the battery cluster is manually pressed, each controller starts and executes off-grid output logic, notifying all energy storage converters to enter "monitoring mode." Upon detecting an anomaly in the power grid, the controller determines whether its own equipment meets the standards. If the SOC data of its own battery cluster exceeds the self-built grid threshold, then its equipment meets the standards; otherwise, it does not. Controllers that detect that their own equipment meets the standards control the energy storage converter to perform self-built voltage (VF start) generation and send voltage and micro-frequency shift signaling to other controllers. After detecting the voltage and micro-frequency shift signaling, other controllers synchronously connect using a soft-start method, without requiring manual master configuration. If a controller that detects that its own equipment meets the standards receives voltage and micro-frequency shift signaling from other controllers before generating the voltage and micro-frequency shift signaling during the self-built voltage process, it stops the self-built voltage process and connects to the microgrid system according to the voltage and micro-frequency shift signaling sent by other controllers. If the controller detects that its own equipment is not up to standard, it will not perform self-voltage building and will wait for voltage and micro-amplitude frequency shift signaling from other controllers before connecting to the microgrid system.

[0026] S130. After the microgrid system stabilizes, exchange equipment information with other controllers and perform a master selection operation based on the equipment information; other controllers are other devices in the microgrid system besides the current controller.

[0027] For example, the leader election operation specifically involves conducting an election to determine the leader. The device information includes at least the effective value of the output voltage, output frequency, active power, reactive power, SOC status, load change rate, current virtual impedance, whether it is a leader candidate, the currently recognized leader ID (-1 indicates none), and self-test health status.

[0028] Each controller calculates its own election score based on the following formula: ; in, To score points in their own election campaign, the temperament range is: ; This is the normalized value of SOC, and its range is [value range missing]. ; Active power, measured in kW; Rated power, in kW; The normalized self-assessment health score has a value range of [value range missing]. ; For node communication quality, the value range is: .

[0029] When a candidate's campaign score exceeds 0.7, they become a lord candidate and submit their lord campaign application to other controllers. Each controller, within each election cycle, only casts its votes for the first lord candidate to submit a campaign application and whose term number has been updated. When a lord candidate receives more than half the votes, they are elected lord and send their ID to other controllers. A lord's term is 2 seconds; after this period, a new election is held according to the above rules, and lords can be re-elected.

[0030] S140. If the current controller is determined to be the master, it performs the master's duties in order to control the power supply of the microgrid system.

[0031] In one embodiment, performing host responsibilities includes: Determine the system baseline adjustment amount for the microgrid system, predict and allocate the load for the next cycle of the microgrid system, and assign output weights to each slave when receiving abnormal operating condition reports from other controllers.

[0032] In one embodiment, determining the system reference value adjustment amount for the microgrid system includes: Receive frequency and voltage correction values ​​from other controllers; The system reference value correction is calculated based on the frequency correction and voltage correction, and then sent to the slave device.

[0033] For example, the system reference value correction includes a system frequency reference value correction and a system voltage reference value correction. The system frequency reference value correction and the system voltage reference value correction are calculated using the following formulas: ; ; in, This is the correction amount for the system frequency reference value, in Hz; The rated capacity of the battery cluster is expressed in kWh. For the number of devices; This is the correction amount for the system voltage reference value; This is the frequency correction amount; This is the voltage correction amount.

[0034] After determining the system frequency reference value correction and the system voltage reference value correction, the host computer feeds them back to all slave computers via broadcast.

[0035] In one embodiment, predicting and allocating the next cycle load of the microgrid system includes: Obtain the historical active power of the load.

[0036] By inputting historical active power into a preset prediction model, the load of the microgrid system in the next cycle can be obtained.

[0037] The next cycle load of the microgrid system is allocated to each slave node for the next cycle load.

[0038] For example, the host controller continuously collects the active power of the microgrid load at a sampling period of 20ms, and extracts 10 consecutive cycles of active power time series, totaling 200ms, as input data for a lightweight LSTM predictor. The predictor is configured with two hidden layers, each with only 8 computation units to reduce computational overhead. After forward inference, it outputs the load for the next cycle. TensorFlow Lite Micro or C arrays are used to distribute the load for the next cycle to each slave, serving as the node load for each slave in the next cycle.

[0039] In one embodiment, upon receiving an abnormal operating condition report from another controller, assigning output weights to each slave device includes: Obtain the SOC status data and rated power of each slave device.

[0040] Upon receiving an abnormal operating condition report from a slave device, the output weight of each slave device is calculated based on its SOC status data and rated power.

[0041] Send the corresponding output weight to each slave device.

[0042] For example, abnormal operating conditions of a slave device include any one of the following: load increment exceeding the increment threshold, load exceeding rated power, or its own SOC falling below the safety threshold. When the master device receives an abnormal operating condition report from a slave device, it calculates the output weight of each slave device using the following formula: ; in, For the first The output weight of each slave device; For the first The rated power of each slave unit; For the first The difference between the SOC of an individual slave device and the average SOC of the microgrid system.

[0043] In one embodiment, the host's responsibilities also include sending a self-check health score to all slaves so that when the host's self-check health score is lower than a health threshold or the host fails to send a self-check health score to all slaves, the slaves can re-elect a new host based on their self-check health score and their own election scores.

[0044] For example, the health threshold is 60. When a host's self-checked health falls below 60, a new host election begins. Each controller calculates its own election score; when its score exceeds 0.7, it becomes a host candidate and submits a host election application to other controllers. Within each election cycle, each controller only casts its votes for the first host candidate to submit an application and whose term number has been updated. When a host candidate receives more than half of the votes, it is elected as the host and sends its own ID to other controllers. The host term is 2 seconds; after its expiration, a new election is held according to the above rules, and a host can be re-elected.

[0045] S150. If the current controller is determined to be a slave, it performs slave duties and receives instructions from the master.

[0046] In one possible implementation, the slave device performs slave functions and receives instructions from the master device, including: Calculate the frequency correction and voltage correction based on the electrical parameters of its own equipment and the electrical parameters of the microgrid system, and send the frequency correction and voltage correction to the host.

[0047] For example, the frequency correction and voltage correction are calculated according to the following formulas: ; ; in, This is the frequency correction amount; Take 0.5; The rated frequency of the microgrid system; To measure the frequency of the microgrid system; This is the rated active power of the machine; This represents the real-time active power of the machine. Take 0.2; This is the voltage correction amount; Take 0.5; This is the rated voltage of the microgrid system; Measured voltage of microgrid system; Take 0.2; This is the rated reactive power of the machine; Real-time reactive power of this machine.

[0048] The virtual impedance of the device is calculated and updated in real time based on the real-time output current of the device itself.

[0049] For example, the reactive circulating current component of the machine is calculated using the instantaneous reactive current deviation according to the following formula: ; in, For the first The reactive circulating current component of the slave unit; For the first The instantaneous reactive current of the slave device; This represents the number of slave devices.

[0050] Calculate the virtual impedance of your device using the following formula: ; in, For the first The virtual impedance of a slave device; This is the initial virtual impedance; The proportionality constant is set to 0.2. for The reactive circulating current component at any given moment; The integral coefficient is 0.05.

[0051] Receive and supply power according to the load assigned by the host for the next cycle.

[0052] It determines whether its own equipment is in an abnormal operating condition. If so, it sends an abnormal operating condition report to the host, receives the output weight assigned by the host, and adjusts its own load according to the output weight.

[0053] For example, the slave device compares its own load with the rated load, calculates its own load increment, compares the load increment with the increment threshold, and compares its own SOC with the safety threshold. If any one or more of the following occur: its own load exceeds the rated load, the load increment exceeds the increment threshold, or its own SOC falls below the safety threshold, then the device is determined to be in an abnormal operating condition.

[0054] After receiving the output weight assigned by the host, adjust its own load according to the following calculation formula: ; in, For the first The updated load of each slave device; For the first The slave device's own load before the update; For the first The output weight of each slave device; This represents the sum of the load increments for all slave devices.

[0055] In one embodiment, it also includes: When a communication anomaly occurs between the master and slave devices, the master device adopts a frequency shift signaling layer cooperative mode to communicate with all slave devices.

[0056] Meanwhile, the host sends UDP Probes to all slaves at a preset frequency. If it receives a reply at least twice in a row, the host switches back to consensus mode to communicate with all slaves.

[0057] For example, if the host or slave device does not receive any UDP packets for 10 consecutive ms, or the CRC error rate exceeds 20%, it is determined that the communication between the host and slave devices is abnormal. In this case, the host adopts a frequency-shift signaling layer cooperative mode to communicate with all slave devices, with the host becoming the frequency-shift signaling transmitter and the slave devices becoming the receivers. Every 500 ms, the host attempts to send a UDP Probe to all slave devices. If it receives a reply three times consecutively, the host switches back to consensus mode to communicate with all slave devices.

[0058] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0059] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0060] The multi-machine parallel black start device for energy storage systems includes: at least one controller, which is used to acquire electrical data of the power grid after receiving a black start command, and determine whether the power grid is abnormal based on the electrical data of the power grid; If the power grid is abnormal, a microgrid system can be built based on its own SOC data; After the microgrid system stabilizes, it exchanges device information with other controllers and performs a master selection operation based on the device information; other controllers are the devices in the microgrid system other than the current controller. If the current controller is determined to be the master, it performs the master's duties in order to control the power supply of the microgrid system; If the current controller is determined to be a slave, it performs slave functions and receives instructions from the master.

[0061] For example, the controller includes: The power grid anomaly detection module is used to obtain electrical data of the power grid after receiving a black start command, and to determine whether the power grid is abnormal based on the electrical data of the power grid.

[0062] The microgrid system construction module is used to construct a microgrid system based on the SOC data of its own equipment if the power grid is abnormal.

[0063] The master selection module is used to exchange device information with other controllers after the microgrid system has stabilized, and to perform master selection operations based on the device information; other controllers are other devices in the microgrid system besides the current controller.

[0064] The host responsibility execution module is used to execute host responsibilities when the current controller is determined to be the host, so as to control the power supply of the microgrid system.

[0065] The slave responsibility execution module is used to perform slave responsibilities and receive instructions from the master when the current controller is determined to be a slave.

[0066] In one embodiment, the microgrid system construction module is further configured to compare its own device's SOC data with a preset self-built grid threshold. If its own device's SOC data exceeds the self-built grid threshold, it generates grid construction data, constructs the microgrid system based on the grid construction data, and sends the grid construction data to other controllers.

[0067] If the SOC data of its own device exceeds the self-built network threshold and it receives network construction data sent by other controllers before producing network construction data, or if the SOC data of its own device does not exceed the self-built network threshold, it receives network construction data sent by other controllers and integrates into the microgrid system.

[0068] In one embodiment, the host responsibility execution module is also used to determine the system baseline adjustment amount of the microgrid system, predict and allocate the load of the microgrid system in the next cycle, and assign output weights to each slave when receiving abnormal operating condition reports from other controllers.

[0069] In one embodiment, the master responsibility execution module is further configured to send a self-check health status to all slaves, so that when the master's self-check health status is lower than the health threshold or the master fails to send a self-check health status to all slaves, the slaves can re-elect a new master based on their self-check health status and their own election scores.

[0070] In one embodiment, the host responsibility execution module is also configured to receive frequency correction and voltage correction amounts sent by other controllers.

[0071] The system reference value correction is calculated based on the frequency correction and voltage correction, and then sent to the slave device.

[0072] In one embodiment, the host responsibility execution module is also used to obtain the historical active power of the load.

[0073] By inputting historical active power into a preset prediction model, the load of the microgrid system in the next cycle can be obtained.

[0074] The next cycle load of the microgrid system is allocated to each slave node for the next cycle load.

[0075] In one embodiment, the host responsibility execution module is further configured to acquire the SOC status data and rated power of each slave device.

[0076] Upon receiving an abnormal operating condition report from a slave device, the output weight of each slave device is calculated based on its SOC status data and rated power.

[0077] Send the corresponding output weight to each slave device.

[0078] In one embodiment, the slave duty execution module is further configured to calculate the frequency correction and voltage correction based on the electrical parameters of its own device and the electrical parameters of the microgrid system, and send the frequency correction and voltage correction to the master.

[0079] The virtual impedance of the device is calculated and updated in real time based on the real-time output current of the device itself. Receive and supply power according to the next cycle load assigned by the lord.

[0080] Determine if your equipment is experiencing any abnormal operating conditions. If so, send an abnormal operating condition report to the lord, receive the output weight assigned by the lord, and adjust your own load according to the output weight.

[0081] Figure 3This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Figure 3 As shown, the electronic device 4 in this embodiment includes a processor 40 and a memory 41. The memory 41 stores a computer program 42. When the processor 40 executes the computer program 42, it implements the steps in the various method embodiments described above. Alternatively, when the processor 40 executes the computer program 42, it implements the functions of each module / unit in the various device embodiments described above.

[0082] For example, computer program 42 may be divided into one or more modules / units, which are stored in memory 41 and executed by processor 40 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 42 in electronic device 4.

[0083] Electronic device 4 may include, but is not limited to, processor 40 and memory 41. Those skilled in the art will understand that... Figure 3 This is merely an example of electronic device 4 and does not constitute a limitation on electronic device 4. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 4 may also include input / output devices, network access devices, buses, etc.

[0084] The processor 40 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0085] The memory 41 can be an internal storage unit of the electronic device 4, such as a hard disk or RAM. The memory 41 can also be an external storage device of the electronic device 4, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 41 can include both internal and external storage units of the electronic device 4. The memory 41 is used to store the computer program 42 and other programs and data required by the electronic device 4. The memory 41 can also be used to temporarily store data that has been output or will be output.

[0086] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.

[0087] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0088] This invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0089] Computer programs include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0090] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0091] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for black-starting multiple parallel units in an energy storage system, characterized in that, include: After receiving the black start command, the electrical data of the power grid is obtained, and the power grid is judged to be abnormal based on the electrical data of the power grid. If the power grid is abnormal, a microgrid system is constructed based on its own SOC data; After the microgrid system stabilizes, it exchanges device information with other controllers and performs a master election operation based on the device information; the other controllers are other devices in the microgrid system besides the current controller. If the current controller is determined to be the host, it performs the host responsibilities in order to control the power supply of the microgrid system; If the current controller is determined to be a slave, it performs slave functions and receives instructions from the master.

2. The multi-machine parallel black-start method for energy storage systems according to claim 1, characterized in that, The construction of a microgrid system based on its own SOC data includes: The system compares its own SOC data with a preset self-built network threshold. If its own SOC data exceeds the self-built network threshold, it generates first network construction data, builds a microgrid system based on the first network construction data, and sends the first network construction data to the other controllers. If the SOC data of the device exceeds the self-built network threshold, but receives the second network data sent by the other controller before generating the first network data, or if the SOC data of the device does not exceed the self-built network threshold, then the device receives the second network data sent by the other controller and integrates it into the microgrid system.

3. The multi-machine parallel black-start method for energy storage systems according to claim 1, characterized in that, The responsibilities of the execution host include: The system baseline value adjustment amount of the microgrid system is determined, the load of the microgrid system in the next cycle is predicted and allocated, and when an abnormal operating condition report is received from the slave, the output weight is assigned to each slave.

4. The multi-machine parallel black-start method for energy storage systems according to claim 3, characterized in that, The host's responsibilities also include sending a self-check health status to all the slaves, so that when the host's self-check health status is lower than a health threshold or the host fails to send a self-check health status to all the slaves, the slaves can re-elect a new host based on their self-check health status and their own election scores.

5. The multi-machine parallel black-start method for energy storage systems according to claim 4, characterized in that, The method further includes: When a communication anomaly occurs between the host and the slave, the host uses a frequency shift signaling layer cooperative mode to communicate with all the slaves. Meanwhile, the host sends UDP Probes to all the slave devices at a preset frequency. If it receives a reply at least twice in a row, the host switches back to consensus mode to communicate with all the slave devices.

6. The multi-machine parallel black-start method for energy storage systems according to claim 3, characterized in that, The determination of the system reference value fine-tuning amount for the microgrid system includes: Receive frequency correction and voltage correction values ​​sent by each of the slave devices; The system reference value correction is calculated based on the frequency correction and the voltage correction, and then sent to the slave device.

7. The multi-machine parallel black-start method for energy storage systems according to claim 3, characterized in that, The prediction and allocation of the next cycle load of the microgrid system includes: Obtain the historical active power of the load; The historical active power is input into a preset prediction model to obtain the load of the microgrid system in the next cycle. The next cycle load of the microgrid system is used to allocate the next cycle node load to each of the slave machines.

8. The multi-machine parallel black-start method for energy storage systems according to claim 3, characterized in that, The step of assigning output weights to each slave device upon receiving an abnormal operating condition report from the slave device includes: Obtain the SOC status data and rated power of each slave device; Upon receiving an abnormal operating condition report from the slave device, the output weight of each slave device is calculated based on its SOC status data and rated power. Send the corresponding output weight to each of the slave devices.

9. The multi-machine parallel black-start method for an energy storage system according to any one of claims 1 to 5, characterized in that, The process of performing slave functions and receiving instructions from the master includes: Obtain its own electrical parameters and the electrical parameters of the microgrid system; Based on its own electrical parameters and the electrical parameters of the microgrid system, it calculates the frequency correction and voltage correction, and sends the frequency correction and voltage correction to the host. It obtains its own real-time output current, and calculates and updates its own virtual impedance in real time based on its own real-time output current. Receive and supply power according to the load assigned by the host for the next cycle; It determines whether it is experiencing abnormal operating conditions. If so, it sends an abnormal operating condition report to the host, receives the output weight assigned by the host, and adjusts its own load according to the output weight.

10. A multi-machine parallel black-start device for an energy storage system, characterized in that, include: At least one controller; The controller is used to acquire electrical data of the power grid after receiving a black start command, and determine whether the power grid is abnormal based on the electrical data of the power grid. If the power grid is abnormal, a microgrid system is constructed based on its own SOC data; After the microgrid system stabilizes, it exchanges device information with other controllers and performs a master election operation based on the device information; the other controllers are other devices in the microgrid system besides the current controller. If the current controller is determined to be the host, it performs the host responsibilities in order to control the power supply of the microgrid system; If the current controller is determined to be a slave, it performs slave functions and receives instructions from the master.

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