Snowflake distribution network self-healing processing logic optimization method, system, device and medium

Abstract

The present disclosure relates to a method, system, device and medium for optimizing the self-healing processing logic of a snowflake-type distribution network, and belongs to the field of power system automation technology. The method comprises the following steps: constructing the protection coordination rules of the snowflake-type distribution network self-healing logic and the low-voltage photovoltaic grid-connected circuit breaker; optimizing the master station centralized logic; constructing a distributed fast self-healing logic based on the protection coordination rules and the optimized master station centralized logic to optimize the self-healing processing logic of the snowflake-type distribution network. The present disclosure effectively solves the problem of the relay protection system misjudging the fault current of multiple power supply terminals by introducing directional signals and directional relays, and reduces the erroneous circuit breaker tripping events. The optimized fault processing logic can isolate the fault area more quickly, restore power supply to the non-fault area, and improve the reliability and stability of the power grid.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system automation, and in particular, relates to a snowflake-type distribution network self-healing processing logic optimization method, system, device and medium. Background Art

[0002] With the access of a high proportion of distributed photovoltaics, the power flow direction, voltage distribution, reactive power balance, etc. of the distribution network have undergone significant changes. As an advanced distribution network structure, the snowflake distribution network has the advantages of high reliability, high flexibility, and high economy. However, in the context of the access of a high proportion of distributed photovoltaics, the self-healing processing logic of the snowflake distribution network also faces new challenges. The traditional centralized self-healing processing logic may not be able to respond to the complex changes brought about by distributed photovoltaics in a timely and accurate manner.

[0003] Therefore, it is necessary to provide a new snowflake-type distribution network self-healing processing logic optimization method, system, device and medium to solve the above technical problems. Summary of the invention

[0004] The purpose of the present disclosure is to provide a snowflake-type distribution network self-healing processing logic optimization method, system, device and medium in order to solve the above problems.

[0005] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0006] A snowflake-type distribution network self-healing processing logic optimization method comprises the following steps:

[0007] Construct the snowflake-type distribution network self-healing logic and the protection coordination rules of low-voltage photovoltaic grid-connected circuit breakers;

[0008] Optimize the centralized logic of the master station;

[0009] Based on the protection coordination rules and the optimized master station centralized logic, a distributed fast self-healing logic is constructed to optimize the snowflake-type distribution network self-healing processing logic.

[0010] As a further optimization scheme of the present disclosure, the snowflake-type distribution network self-healing logic and the protection coordination rules of the low-voltage photovoltaic grid-connected circuit breaker are constructed, including:

[0011] A low-voltage photovoltaic grid-connected circuit breaker is used as a key control point for distributed photovoltaic access to the power grid, and the low-voltage photovoltaic grid-connected circuit breaker is provided with over-voltage and under-voltage protection, reverse power protection and anti-islanding protection functions.

[0012] As a further optimization solution of the present disclosure, the over-voltage and under-voltage protection includes:

[0013] When the voltage at the transformer node in the distribution station area is too high and exceeds the set value of the low-voltage photovoltaic grid-connected circuit breaker, the overvoltage protection processing module of the new energy source is set through the master station system. Combined with the terminal overvoltage protection function, the low-voltage photovoltaic grid-connected circuit breaker is disconnected from the grid to solve the overvoltage fault problem.

[0014] As a further optimization solution of the present disclosure, the over-voltage and under-voltage protection specifically includes:

[0015] The terminal modifies the set value according to the command of the master station, and sends the modified set value to the master station, and sends the overvoltage event to the master station at the same time;

[0016] The master station optimizes and controls distributed energy according to overvoltage events;

[0017] The master station performs overvoltage processing based on the overvoltage protection action event sent by the terminal, the terminal overvoltage fault information and the system overvoltage condition;

[0018] If it is confirmed that the voltage is too high and exceeds the set value of the low-voltage photovoltaic grid-connected circuit breaker, a disconnection command is issued;

[0019] After receiving the disconnection instruction, the low-voltage photovoltaic grid-connected circuit breaker performs the disconnection operation according to the preset logic and steps.

[0020] As a further optimization solution of the present disclosure, the reverse power protection includes:

[0021] When the reverse power exceeds the setting value of the low-voltage photovoltaic grid-connected circuit breaker, the low-voltage photovoltaic grid-connected circuit breaker disconnects from the grid.

[0022] As a further optimization scheme of the present disclosure, the reverse power protection specifically includes:

[0023] Real-time monitoring of the output power of the photovoltaic system and the power demand of the power grid;

[0024] Calculate the collected power data to determine whether the output power of the photovoltaic system exceeds the power demand of the power grid, that is, whether there is reverse power;

[0025] If the reverse power exceeds the preset value of the low-voltage photovoltaic grid-connected circuit breaker, a disconnection command is triggered;

[0026] After receiving the disconnection command, the low-voltage photovoltaic grid-connected circuit breaker quickly performs the disconnection operation to cut off the connection between the photovoltaic system and the grid.

[0027] As a further optimization solution of the present disclosure, the anti-islanding protection includes:

[0028] When a power outage is detected in the grid and an islanding phenomenon is about to occur, an anti-islanding protection processing module is set up through the master station system. Combined with the terminal anti-islanding protection function, the low-voltage photovoltaic grid-connected circuit breaker is disconnected from the grid to achieve anti-islanding and solve the islanding fault problem.

[0029] As a further optimization solution of the present disclosure, the anti-islanding protection specifically includes:

[0030] The terminal sends the switch action information to the main station, and the main station determines whether the system has a pressure loss state and the range of pressure loss based on the terminal action situation;

[0031] Determine the voltage and power flow conditions within the voltage loss range to determine whether there is an unplanned islanding state;

[0032] Remotely control the boundary switch of the unplanned island distributed power access point and send remote control commands to the terminal side;

[0033] The terminal modifies the set value according to the remote control command of the master station and sends the modified set value to the master station;

[0034] The master station confirms whether the unplanned island has disappeared;

[0035] If it is confirmed that the islanding phenomenon is about to occur or has occurred, the low-voltage photovoltaic grid-connected circuit breaker will quickly perform the disconnection operation in combination with the terminal anti-islanding protection function.

[0036] As a further optimization solution of the present disclosure, the optimization of the master station centralized logic includes:

[0037] By installing a control unit on each disconnect switch, important information before and after the fault, including current and voltage, can be collected in real time;

[0038] Upload the important information to the main site;

[0039] The master station conducts a comprehensive analysis of the important information received, determines the fault area and formulates a power supply restoration strategy.

[0040] As a further optimization solution of the present disclosure, optimizing the centralized logic of the master station also includes introducing a direction signal into the master station system.

[0041] As a further optimization solution of the present disclosure, the direction signal effectively determines the direction of the fault current by configuring a directional relay, thereby assisting in determining the true source of the instantaneous overcurrent.

[0042] As a further optimization scheme of the present invention, based on the auxiliary judgment of the direction signal, the master station combines the terminal direction and low-voltage information and makes a voltage judgment to accurately identify the fault area and eliminate the impact after the distributed photovoltaic access; isolate the fault area by remotely controlling each switch and restore power supply to the non-fault area.

[0043] As a further optimization scheme of the present disclosure, a distributed fast self-healing logic is constructed based on the protection coordination rules and the optimized master station centralized logic, including fault location and fault repair. The fault location includes a fault location algorithm based on power direction rules and a fault location algorithm based on current hot zone rules.

[0044] As a further optimization scheme of the present disclosure, the fault location algorithm based on power direction rule accurately identifies the fault location through the directionality of power flow in the power system, including node association matrix method, point-edge association matrix method and edge aggregation algorithm.

[0045] As a further optimization scheme of the present disclosure, the node association matrix method constructs an association matrix between power grid nodes. When a fault occurs, the matrix is ​​updated using power direction information. By comparing the difference between the matrix under normal conditions and the matrix under fault conditions, the node where the fault is located or the connection between the nodes is quickly locked.

[0046] The point-edge association matrix method constructs a point-edge association matrix by combining the relationship between power grid nodes and edges, and effectively identifies the edges affected by the fault and their adjacent nodes by analyzing the changes in the power direction in the point-edge association matrix.

[0047] The edge set operation algorithm calculates the power direction of each edge in the edge set by operating on the power grid edge set, and determines the edge where the fault is located in combination with the system topology.

[0048] As a further optimization solution of the present disclosure, the fault location algorithm based on the current hot zone rule includes:

[0049] Through the preset current hot zone identification algorithm, the current data of each monitoring point is analyzed to identify the area with abnormal current changes; based on the identified current hot zone location and combined with the topological structure of the power system, the specific location of the fault point is inferred.

[0050] A snowflake type distribution network self-healing processing logic optimization system, comprising:

[0051] The protection coordination rule construction module is used to construct the snowflake-type distribution network self-healing logic and the protection coordination rules of the low-voltage photovoltaic grid-connected circuit breaker;

[0052] The master station logic optimization module is used to optimize the centralized logic of the master station;

[0053] The self-healing logic construction module is used to construct distributed fast self-healing logic based on the protection coordination rules and the optimized master station centralized logic to optimize the snowflake-type distribution network self-healing processing logic.

[0054] An electronic device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0055] Memory, for storing computer programs;

[0056] The processor is used to execute the program stored in the memory to implement any one of the snowflake-type distribution network self-healing processing logic optimization methods.

[0057] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the snowflake-type distribution network self-healing processing logic optimization method.

[0058] The beneficial effects of the present disclosure are:

[0059] The present disclosure effectively solves the problem of relay protection system misjudging fault current at multiple power supply ends by introducing directional signals and directional relays, and reduces the number of erroneous circuit breaker tripping events. The optimized fault handling logic can isolate the fault area more quickly and restore power supply to the non-fault area, thereby improving the reliability and stability of the power grid.

[0060] The present disclosure also provides a variety of fault location algorithms, which help to quickly and accurately locate faults in distributed photovoltaic systems, shorten fault processing time, and achieve self-recovery of power grid faults through the application of intelligent distributed terminals, thereby improving the stability and reliability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 is a flow chart of a method in an embodiment of the present disclosure;

[0062] Figure 2 is an overvoltage fault handling strategy diagram in an embodiment of the present disclosure;

[0063] Figure 3 is a diagram of an island fault handling strategy in an embodiment of the present disclosure;

[0064] Figure 4 is a flow chart of a fault location algorithm based on power direction rule in an embodiment of the present disclosure;

[0065] Figure 5 is a flow chart of a fault location algorithm based on current hot zone rules in an embodiment of the present disclosure;

[0066] Figure 6 is a medium voltage overcurrent fault handling strategy diagram in an embodiment of the present disclosure;

[0067] Figure 7 is a system structure block diagram in an embodiment of the present disclosure;

[0068] Figure 8 It is a block diagram of the device structure in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0069] The present application is further described in detail below in conjunction with the accompanying drawings. It is necessary to point out here that the following specific implementation methods are only used to further illustrate the present application and cannot be understood as limiting the scope of protection of the present application. Technical personnel in this field can make some non-essential improvements and adjustments to the present application based on the above application content.

[0070] like Figure 1 As shown, a snowflake-type distribution network self-healing processing logic optimization method includes the following steps:

[0071] S1: Construct the snowflake-type distribution network self-healing logic and the protection coordination rules of low-voltage photovoltaic grid-connected circuit breakers, including:

[0072] Low-voltage photovoltaic grid-connected circuit breakers are the key control points for distributed photovoltaic access to the power grid.

[0073] Based on the traditional functions, the low-voltage photovoltaic grid-connected circuit breaker has added over-voltage and under-voltage protection, reverse power protection, anti-islanding protection and other functions.

[0074] Over-voltage and under-voltage protection: When the voltage at the transformer node in the distribution station area is too high and exceeds the set value of the low-voltage photovoltaic grid-connected circuit breaker, the overvoltage protection processing module of the new energy source is set through the master station system. Combined with the terminal overvoltage protection function, the low-voltage photovoltaic grid-connected circuit breaker is disconnected from the grid to solve the overvoltage fault problem.

[0075] Now combined Figure 2 The overvoltage fault handling strategy diagram is used to illustrate this.

[0076] Step 1: The terminal side modifies the set value according to the master station command and sends an overvoltage alarm event to the master station.

[0077] Step 2: The terminal side modifies the set value according to the command to modify the set value, and sends the modified set value to the master station.

[0078] Step 3: The master station optimizes and regulates distributed energy based on overvoltage events.

[0079] Step 4: After regulation, the overvoltage cannot disappear.

[0080] Step 5: The master station performs overvoltage processing based on the overvoltage protection action event sent by the terminal, the terminal overvoltage fault information and the system overvoltage condition.

[0081] Step 6: If it is confirmed that the voltage is too high and exceeds the set value of the low-voltage photovoltaic grid-connected circuit breaker, a disconnection command is issued.

[0082] Step 7: Execute the disconnection operation: After receiving the disconnection instruction, the low-voltage photovoltaic grid-connected circuit breaker executes the disconnection operation according to the preset logic and steps.

[0083] Reverse power protection: When the reverse power exceeds the set value of the low-voltage photovoltaic grid-connected circuit breaker, the low-voltage photovoltaic grid-connected circuit breaker disconnects from the grid, including:

[0084] Step 1: Real-time monitoring and data collection: The output power of the photovoltaic system and the power demand of the power grid are monitored in real time through the power monitoring device; the data acquisition system collects and processes these real-time monitoring data to provide a basis for subsequent judgment and decision-making.

[0085] Step 2: Reverse power judgment: The data processing system calculates the collected power data to determine whether the output power of the photovoltaic system exceeds the power demand of the power grid, that is, whether there is reverse power.

[0086] Step 3: If the reverse power exceeds the preset value of the low-voltage photovoltaic grid-connected circuit breaker, a disconnection command is triggered.

[0087] Step 4: Execute the disconnection operation: After receiving the disconnection command, the low-voltage photovoltaic grid-connected circuit breaker quickly executes the disconnection operation to cut off the connection between the photovoltaic system and the grid.

[0088] Anti-islanding protection: When a power outage is detected and an islanding phenomenon is about to occur, the anti-islanding protection processing module is set up through the master station system. Combined with the terminal anti-islanding protection function, the low-voltage photovoltaic grid-connected circuit breaker is disconnected from the grid to achieve anti-islanding and solve the islanding fault problem.

[0089] Now combined Figure 3 The island fault handling strategy diagram is used to illustrate this.

[0090] Step 1: The terminal sends the switch action information to the master station, which determines whether the system is under pressure based on the information and determines the specific range of the pressure loss.

[0091] Step 2: The master station will conduct a detailed analysis of the voltage and power flow conditions within the voltage loss range to determine whether there is an unplanned islanding state.

[0092] Step 3: Once the unplanned islanding state is confirmed, the master station will remotely control the access point boundary switch of the unplanned islanding distributed power source and send the corresponding remote control command to the terminal side.

[0093] Step 4: After receiving the remote control command from the master station, the terminal side will modify the set value according to the command and upload the modified set value information back to the master station.

[0094] Step 5: The master station will confirm that the unplanned islanding state has disappeared.

[0095] Step 6: Execute the disconnection operation: Once it is confirmed that the islanding phenomenon is about to occur or has occurred, combined with the terminal anti-islanding protection function, the low-voltage photovoltaic grid-connected circuit breaker quickly performs the disconnection operation.

[0096] S2: Optimize the centralized logic of the master station, including:

[0097] The centralized fault handling logic of the master station collects important information such as current and voltage before and after the fault in real time by installing a control unit on each disconnect switch;

[0098] Uploading the important information to the main station via the communication channel;

[0099] The master station conducts a comprehensive analysis of the received data, identifies the fault area, and formulates a strategy for restoring power supply;

[0100] It is also proposed to introduce a direction signal in the master station system. The direction signal effectively determines the direction of the fault current by configuring a directional relay, thereby assisting in determining the true source of the instantaneous overcurrent.

[0101] Based on the auxiliary judgment of the direction signal, the master station combines the terminal direction and low-voltage information, and makes a voltage judgment to accurately identify the fault area and eliminate the impact after the distributed photovoltaic access.

[0102] The faulty area is isolated by remotely controlling the switches, and power supply to the non-faulty areas is restored.

[0103] S3: Based on the protection coordination rules and the optimized master station centralized logic, a distributed fast self-healing logic is constructed to optimize the self-healing processing logic of the snowflake distribution network. Figure 4 The fault location algorithm process based on the power direction rule is described, including:

[0104] Step 1: Build the model:

[0105] Node association matrix method: Construct a node association matrix based on network topology information; mark the adjacent nodes and power flow direction of each node.

[0106] Point-edge association matrix method: construct a point-edge association matrix to associate nodes with edges (lines); mark the starting node and ending node of each edge, as well as the power direction.

[0107] Edge set operation algorithm: List the set of all edges; number each edge and record its power transfer status.

[0108] Step 2: Power direction analysis:

[0109] Get real-time power data: Get real-time power data from sensors or measurement devices.

[0110] Compare power directions: Compare real-time power data with the power directions in the model; flag abnormal power directions.

[0111] Step 3: Fault Detection:

[0112] Based on the node association matrix, the impact of abnormal power on the node association matrix is ​​analyzed to determine possible faulty nodes or areas.

[0113] Based on the point-edge correlation matrix, the impact of abnormal power on point-edge correlation is analyzed to locate the specific fault edge.

[0114] Based on edge set operations, abnormal edges are analyzed to further confirm the faulty edges and their impact range.

[0115] Step 4: Troubleshooting:

[0116] Comprehensive analysis: Combine the results of the node association matrix method, the point-edge association matrix method, and the edge set operation algorithm, and comprehensively consider multiple methods for fault diagnosis to improve accuracy.

[0117] Fault location: Finally determine the fault location and output a fault report, including the fault node / edge, fault type, impact range, etc.

[0118] Step 5: Fix the problem according to the problem report

[0119] Now combined Figure 5 The fault location algorithm process based on current hot zone rules is explained.

[0120] Step 1: Data preprocessing:

[0121] Remove high-frequency noise from current data, further clean up data, ensure data accuracy, and convert current data into a standard format for subsequent processing. Based on the structure and numerical characteristics of different power data, and based on convolutional neural network technology, we construct training sets and thresholds to extract high-level features of power big data. By continuously adjusting and optimizing neural network parameters, we train multi-channel data detection and verification model sets to achieve integrity, correctness, and logic verification of power big data, thereby improving data quality.

[0122] Step 2: Construct the current hot zone:

[0123] Calculate current changes: Analyze the current data of each monitoring point and calculate the change amount and change rate of the current.

[0124] Identify hot spots: Based on the current changes, identify the area with abnormal current, that is, the current hot spot.

[0125] Step 3: Fault location:

[0126] Analyze the location of hot spots: Perform location analysis on the identified current hot spots.

[0127] Combined with system topology: Combine the hot zone location with the power system model to infer the fault point; At the same time, combine the main distribution network accident tripping events, tripping signals and protection signals, combined with measurement verification and downstream distribution transformer outage and restoration signals to generate outage and restoration information;

[0128] Determine the fault point: Based on the above information, determine the specific location of the fault point.

[0129] Step 4: Output detailed information of the fault point, such as location, type, etc. Establish a fault information model, including power outage event ID, power outage event description, responsible unit, power outage time, power outage line, affiliated substation, trip switch, affiliated substation, power outage nature (fault / plan / other), fault type (short circuit / grounding), power outage type (10kV whole line, 10kV branch line, single distribution transformer, 0.4kV outgoing line, low voltage multi-family, low voltage single family), judgment method, reclosing situation, fault area, power outage affected distribution transformer number, power outage affected equipment (list form), power outage area description (community, village, etc.), power outage affected users number, power outage affected users (list form), power restoration time, whether the power is fully restored (partial / complete), etc. Support emergency repair dispatch, power outage management, 95598 business, reliability management and other businesses.

[0130] Figure 6 This is a diagram of the medium-voltage overcurrent fault handling strategy. When a high proportion of new energy equipment is connected, the fault characteristics of distribution system short circuit and other faults change. The traditional distribution automation system fault handling strategies, such as protection, centralized feeder automation, and local feeder automation may not operate correctly, resulting in islanding, increased leakage current, overvoltage, frequency failure and other problems. The process of handling strategies for different types of scenarios is shown in the figure.

[0131] The load balancing control of the snowflake network line equipment fault in the present disclosure includes: the feeder automation fault self-healing function, in the case of a whole group of hexagonal grids under multi-station interconnection, when the transfer line is overloaded and the upper main transformer is overloaded, the load needs to be analyzed, calculated and split, and transferred separately. The fault self-healing function is upgraded, and the judgment and calculation of the load rate of the transfer line and the load rate of the upper main transformer are added, and the load splitting of the non-fault area is carried out to ensure the load balancing during the transfer.

[0132] like Figure 7 As shown, an embodiment of the present disclosure provides a snowflake-type distribution network self-healing processing logic optimization system, including:

[0133] A protection coordination rule construction module 11 is used to construct a snowflake-type distribution network self-healing logic and a protection coordination rule for a low-voltage photovoltaic grid-connected circuit breaker;

[0134] The master station logic optimization module 12 is used to optimize the centralized logic of the master station;

[0135] The self-healing logic construction module 13 is used to construct a distributed fast self-healing logic based on the protection coordination rules and the optimized master station centralized logic to optimize the snowflake-type distribution network self-healing processing logic.

[0136] The implementation process of the functions and effects of each module in the above system is specifically described in the implementation process of the corresponding steps in the above method, which will not be repeated here.

[0137] For the system embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The system embodiment described above is only schematic, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the disclosed solution. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0138] In the above embodiments, any number of all modules can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. At least one of all modules can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in a suitable combination of any of them. Alternatively, at least one of all modules can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0139] See also Figure 8 , an electronic device provided by an embodiment of the present disclosure includes a processor 1110, a communication interface 1120, a memory 1130 and a communication bus 1140, wherein the processor 1110, the communication interface 1120, and the memory 1130 communicate with each other through the communication bus 1140;

[0140] Memory 1130, for storing computer programs;

[0141] The processor 1110 is used to implement the snowflake-type distribution network self-healing processing logic optimization method as shown below when executing the program stored in the memory 1130.

[0142] The communication bus 1140 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0143] The communication interface 1120 is used for communication between the above electronic device and other devices.

[0144] The memory 1130 may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory 1130 may also be at least one storage device located away from the processor 1110.

[0145] The above-mentioned processor 1110 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0146] The embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the snowflake-type distribution network self-healing processing logic optimization method as described above is implemented.

[0147] The computer-readable storage medium may be included in the device / apparatus described in the above embodiment; or it may exist independently without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the snowflake-type distribution network self-healing processing logic optimization method according to the embodiment of the present disclosure is implemented.

[0148] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus, or device.

[0149] The above-mentioned embodiments only express several implementation methods of the present disclosure, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present disclosure. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present disclosure, and these all belong to the protection scope of the present disclosure.

Claims

1. A snowflake distribution network self-healing processing logic optimization method, characterized in that: The following steps are involved: Construct the snowflake-type distribution network self-healing logic and the protection coordination rules of low-voltage photovoltaic grid-connected circuit breakers; Optimize the centralized logic of the master station, including: By installing a control unit on each disconnect switch, important information before and after the fault, including current and voltage, can be collected in real time; Upload the important information to the main site; The master station comprehensively analyzes the important information received, determines the fault area and formulates a strategy for restoring power supply; It also includes the introduction of directional signals in the master station system; The direction signal is used to effectively determine the direction of the fault current by configuring a directional relay, thereby assisting in determining the true source of the instantaneous overcurrent; Based on the auxiliary judgment of the direction signal, the master station combines the terminal direction and low-voltage information, and makes a voltage judgment to accurately identify the fault area and eliminate the impact after the distributed photovoltaic access; isolate the fault area by remotely controlling each switch and restore power supply to the non-fault area; Based on the protection coordination rules and the optimized master station centralized logic, a distributed fast self-healing logic is constructed to optimize the snowflake-type distribution network self-healing processing logic.

2. A snowflake-type distribution network self-healing processing logic optimization method according to claim 1, characterized in that: The snowflake-type distribution network self-healing logic and the protection coordination rules of low-voltage photovoltaic grid-connected circuit breakers include: A low-voltage photovoltaic grid-connected circuit breaker is used as a key control point for distributed photovoltaic access to the power grid, and the low-voltage photovoltaic grid-connected circuit breaker is provided with over-voltage and under-voltage protection, reverse power protection and anti-islanding protection functions.

3. A snowflake-type distribution network self-healing processing logic optimization method according to claim 2, characterized in that: The over-voltage and under-voltage protection includes: When the voltage at the transformer node in the distribution station area is too high and exceeds the set value of the low-voltage photovoltaic grid-connected circuit breaker, the overvoltage protection processing module of the new energy source is set through the master station system. Combined with the terminal overvoltage protection function, the low-voltage photovoltaic grid-connected circuit breaker is disconnected from the grid to solve the overvoltage fault problem.

4. A snowflake-type distribution network self-healing processing logic optimization method according to claim 3, characterized in that: The over-voltage and under-voltage protection specifically includes: The terminal modifies the set value according to the command of the master station, and sends the modified set value to the master station, and sends the overvoltage event to the master station at the same time; The master station optimizes and controls distributed energy according to overvoltage events; The master station performs overvoltage processing based on the overvoltage protection action event sent by the terminal, the terminal overvoltage fault information and the system overvoltage condition; If it is confirmed that the voltage is too high and exceeds the set value of the low-voltage photovoltaic grid-connected circuit breaker, a disconnection command is issued; After receiving the disconnection instruction, the low-voltage photovoltaic grid-connected circuit breaker performs the disconnection operation according to the preset logic and steps.

5. A snowflake-type distribution network self-healing processing logic optimization method according to claim 2, characterized in that: The reverse power protection comprises: When the reverse power exceeds the setting value of the low-voltage photovoltaic grid-connected circuit breaker, the low-voltage photovoltaic grid-connected circuit breaker disconnects from the grid.

6. A snowflake-type distribution network self-healing processing logic optimization method according to claim 5, characterized in that: The reverse power protection specifically includes: Real-time monitoring of the output power of the photovoltaic system and the power demand of the power grid; Calculate the collected power data to determine whether the output power of the photovoltaic system exceeds the power demand of the power grid, that is, whether there is reverse power; If the reverse power exceeds the preset value of the low-voltage photovoltaic grid-connected circuit breaker, a disconnection command is triggered; After receiving the disconnection command, the low-voltage photovoltaic grid-connected circuit breaker quickly performs the disconnection operation to cut off the connection between the photovoltaic system and the grid.

7. A snowflake-type distribution network self-healing processing logic optimization method according to claim 2, characterized in that: The anti-islanding protection includes: When a power outage is detected in the grid and an islanding phenomenon is about to occur, an anti-islanding protection processing module is set up through the master station system. Combined with the terminal anti-islanding protection function, the low-voltage photovoltaic grid-connected circuit breaker is disconnected from the grid to achieve anti-islanding and solve the islanding fault problem.

8. A snowflake-type distribution network self-healing processing logic optimization method according to claim 7, characterized in that: The anti-islanding protection specifically includes: The terminal sends the switch action information to the main station, and the main station determines whether the system has a pressure loss state and the range of pressure loss based on the terminal action situation; Determine the voltage and power flow conditions within the voltage loss range to determine whether there is an unplanned islanding state; Remotely control the boundary switch of the unplanned island distributed power access point and send remote control commands to the terminal side; The terminal modifies the set value according to the remote control command of the master station and sends the modified set value to the master station; The master station confirms whether the unplanned island has disappeared; If it is confirmed that the islanding phenomenon is about to occur or has occurred, the low-voltage photovoltaic grid-connected circuit breaker will quickly perform the disconnection operation in combination with the terminal anti-islanding protection function.

9. A snowflake-type distribution network self-healing processing logic optimization method according to claim 1, characterized in that: Building distributed fast self-healing logic based on the protection coordination rules and the optimized master station centralized logic includes fault location and fault repair. The fault location includes a fault location algorithm based on power direction rules and a fault location algorithm based on current hot zone rules.

10. A snowflake-type distribution network self-healing processing logic optimization method according to claim 9, characterized in that: The fault location algorithm based on power direction rule accurately identifies the fault location through the directionality of power flow in the power system, including a node association matrix method, a point-edge association matrix method and an edge aggregation algorithm.

11. A snowflake-type distribution network self-healing processing logic optimization method according to claim 10, characterized in that: The node association matrix method constructs an association matrix between power grid nodes. When a fault occurs, the matrix is ​​updated using power direction information. By comparing the difference between the matrix under normal conditions and the matrix under fault conditions, the node where the fault is located or the connection between nodes is quickly locked. The point-edge association matrix method constructs a point-edge association matrix by combining the relationship between power grid nodes and edges, and effectively identifies the edges affected by the fault and their adjacent nodes by analyzing the changes in the power direction in the point-edge association matrix. The edge set operation algorithm calculates the power direction of each edge in the edge set by operating on the power grid edge set, and determines the edge where the fault is located in combination with the system topology.

12. A snowflake-type distribution network self-healing processing logic optimization method according to claim 9, characterized in that: The fault location algorithm based on the current hot zone rule includes: Through the preset current hot zone identification algorithm, the current data of each monitoring point is analyzed to identify the area with abnormal current changes; based on the identified current hot zone location and combined with the topological structure of the power system, the specific location of the fault point is inferred.

13. A snowflake-type distribution network self-healing processing logic optimization system, characterized in that: include: The protection coordination rule construction module is used to construct the snowflake-type distribution network self-healing logic and the protection coordination rules of the low-voltage photovoltaic grid-connected circuit breaker; The master station logic optimization module is used to optimize the centralized logic of the master station, including: By installing a control unit on each disconnect switch, important information before and after the fault, including current and voltage, can be collected in real time; Upload the important information to the main site; The master station comprehensively analyzes the important information received, determines the fault area and formulates a strategy for restoring power supply; It also includes the introduction of directional signals in the master station system; The direction signal is used to effectively determine the direction of the fault current by configuring a directional relay, thereby assisting in determining the true source of the instantaneous overcurrent; Based on the auxiliary judgment of the direction signal, the master station combines the terminal direction and low-voltage information, and makes a voltage judgment to accurately identify the fault area and eliminate the impact after the distributed photovoltaic access; isolate the fault area by remotely controlling each switch and restore power supply to the non-fault area; The self-healing logic construction module is used to construct distributed fast self-healing logic based on the protection coordination rules and the optimized master station centralized logic to optimize the snowflake-type distribution network self-healing processing logic.

14. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, for storing computer programs; A processor is used to execute the program stored in the memory to implement the snowflake-type distribution network self-healing processing logic optimization method described in any one of claims 1-12.

15. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the snowflake-type distribution network self-healing processing logic optimization method according to any one of claims 1 to 12 is implemented.

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