Power grid fault disposal auxiliary decision-making method and related device

Abstract

The invention belongs to a decision-making method, and provides a power grid fault disposal auxiliary decision-making method and a related device for solving the technical problems that the pressure of real-time fault disposal in a current power system is gradually increased and the fault disposal quality and efficiency need to be improved. And according to the fault information, retrieving a power grid dispatching procedure and a power grid control requirement to obtain a decision basis. And performing auxiliary analysis on the fault information to obtain an auxiliary analysis result, and finally, pushing a corresponding operation instruction or suggestion according to the auxiliary analysis result. According to the invention, a method of combining artificial intelligence and power system analysis can be adopted to construct a special fault handling aid decision-making agent, when the power grid breaks down or is abnormal, the actual operation condition of the power grid is automatically matched, the operation rule requirement is pushed, and the scheduling operation aid decision is intelligently generated. And the working efficiency of real-time fault handling of the dispatcher can be improved.

Description

Technical Field

[0001] The present application relates to a decision-making method, and specifically to a power grid fault handling auxiliary decision-making method and related devices. Background Art

[0002] Grid control and decision-making support is an important means of ensuring the safe and stable operation of power systems. Reasonable dispatching decisions can improve power system reliability, grid economy, and power balance capabilities. With the development of new power systems, the objects of control have undergone profound changes, the scale of control has increased exponentially, and the control objectives have become complex and diverse. This has led to a growing contradiction between the increasing complexity of the system, the impact intensity of extreme events, and the high requirements for defense resilience. This has resulted in the normalization of extreme events in the power grid, increased system coupling, and the frequent occurrence of complex cascading failures. The large number of alarms and information that flood dispatchers in a short period of time has increased the pressure on dispatchers to handle faults in real time, and the quality and efficiency of fault handling needs to be improved. Summary of the Invention

[0003] In response to the technical problems that the pressure of real-time fault handling in the current power system is gradually increasing and the quality and efficiency of fault handling need to be improved, this application provides a power grid fault handling auxiliary decision-making method and related devices.

[0004] In order to achieve the above objectives, this application adopts the following technical solutions: In a first aspect, the present application proposes a power grid fault handling decision-making auxiliary method, comprising: Obtain fault information from fault abnormality signal alarm information; Formulate an over-limit adjustment strategy based on fault information and implement the over-limit adjustment strategy to make adjustments; According to the fault information, search the grid dispatch regulations and grid control requirements to obtain the basis for decision-making; Perform auxiliary analysis on fault information to obtain auxiliary analysis results; According to the auxiliary analysis results, corresponding operation instructions or suggestions are pushed.

[0005] Furthermore, the fault abnormality signal alarm information includes the name of the faulty device, the alarm time and the data source.

[0006] Furthermore, after obtaining the fault information in the fault abnormality signal alarm information, the method further includes verifying the fault information.

[0007] Furthermore, the method for verifying fault information includes: Respectively measuring the active power and reactive power at a preset time point before the fault occurs and at a preset time point after the fault occurs, and recording them as first measurement parameters; Obtaining the highest value of the grid frequency within a preset time range before the fault occurs, and recording it as the second measurement parameter; Obtaining the transmission section power value and bus voltage measurement value at a preset time point after the fault occurs, and recording them as the third measurement parameter; The fault information is verified according to the first measurement parameter, the second measurement parameter, and the third measurement parameter.

[0008] Furthermore, the method for formulating an over-limit adjustment strategy includes: Determine whether one of the over-limit section and over-limit bus voltage is over-limit. If so, call the power system optimization decision and generate an over-limit adjustment strategy.

[0009] Furthermore, the decision-making basis includes section limit adjustment rules, safety and control action strategies, and safety and control device mode adjustment requirements.

[0010] Furthermore, the method for assisting in analyzing fault information includes: Query the phasor measurement unit data, push the voltage dynamic curve, current dynamic curve and power dynamic curve of the faulty equipment before and after the fault occurs, and assist in determining the cause of the fault based on the change rules of the dynamic curves.

[0011] Furthermore, after pushing the corresponding operation instructions or suggestions, the method further includes: generating reporting information including the fault situation, fault impact and fault handling situation.

[0012] In a second aspect, the present application proposes a power grid fault handling auxiliary decision-making system, comprising: An information module is used to obtain fault information in the fault abnormality signal alarm information; The adjustment module is used to formulate an over-limit adjustment strategy based on fault information and implement the over-limit adjustment strategy for adjustment; The retrieval module is used to retrieve the grid dispatching regulations and grid control requirements based on the fault information to obtain the basis for decision-making; An analysis module is used to perform auxiliary analysis on fault information and obtain auxiliary analysis results; The push module is used to push corresponding operation instructions or suggestions based on the auxiliary analysis results.

[0013] Furthermore, a verification module is included; The verification module is used to verify the fault information after obtaining the fault information in the fault abnormality signal alarm information.

[0014] Furthermore, it also includes a reporting module; The reporting module is used to generate reporting information including the fault situation, fault impact and fault handling situation after pushing the corresponding operation instruction or suggestion.

[0015] In a third aspect, the present application proposes an electronic device comprising: a memory, and one or more processors; the memory is coupled to the processor; wherein computer program code is stored in the memory, and the computer program code includes computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the steps of the above-mentioned power grid fault handling auxiliary decision-making method.

[0016] In a fourth aspect, the present application proposes a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned power grid fault handling auxiliary decision-making method are implemented.

[0017] Compared with the prior art, this application has the following beneficial effects: This application proposes a method for auxiliary decision-making for power grid fault handling. Based on the fault information, an over-limit adjustment strategy is formulated and the over-limit adjustment strategy is implemented for adjustment. Then, based on the fault information, the power grid dispatching regulations and power grid control requirements are retrieved to obtain a basis for decision-making. The fault information is assisted in analysis to obtain auxiliary analysis results. Finally, according to the auxiliary analysis results, corresponding operation instructions or suggestions are pushed. This application can use a method that combines artificial intelligence and power system analysis to build a dedicated fault handling auxiliary decision-making intelligent body. When a fault or abnormality occurs in the power grid, it automatically matches the actual operating conditions of the power grid, pushes operating rules and requirements, and intelligently generates auxiliary scheduling and operation decisions, which helps to improve the efficiency of the dispatcher's real-time fault handling work.

[0018] This application proposes a power grid fault handling auxiliary decision-making system, an electronic device and a computer storage medium, which have all the advantages of the above-mentioned power grid fault handling auxiliary decision-making method. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flowchart of a power grid fault handling auxiliary decision-making method for this application; Figure 2 Two flowcharts of the power grid fault handling auxiliary decision-making method for this application; Figure 3 This is a schematic diagram of the power grid fault handling auxiliary decision-making system of this application. DETAILED DESCRIPTION

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0023] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0024] In the description of the embodiments of the present application, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the accompanying drawings, or the orientation or position relationship in which the product of the invention is usually placed when in use. This is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, it should not be understood as a limitation on the present application. In addition, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0025] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0026] In the description of the embodiments of this application, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art can understand the specific meanings of the above terms in this application based on specific circumstances.

[0027] As a core support for ensuring the safe and stable operation of power systems, grid control and decision-making support is of paramount importance. Scientific and rational dispatching decisions can not only significantly improve the reliability of power systems and ensure the continuity and stability of power supply, but also effectively optimize the economic efficiency of the power grid, improve the utilization efficiency of power resources, and enhance the ability to balance power to meet ever-changing power demands.

[0028] However, with the rapid development of new power systems, the control objectives of power grids have undergone profound changes. Traditional control objectives have gradually evolved into more complex and diverse elements, and the scale of control has also shown an exponential growth trend. This not only increases the difficulty of power grid regulation, but also places higher demands on the intelligence and refinement of control strategies. At the same time, the complexity and diversity of control objectives have become increasingly prominent. How to balance multiple objectives such as economy, environmental protection, and efficiency while ensuring a secure and stable power supply has become a major challenge for power grid regulation.

[0029] Even more serious is the increasing intensity of extreme events as system complexity grows. As the foundational infrastructure of the national economy, the power system faces unprecedented demands for resilience. However, the regular occurrence of extreme events in the power grid and the increasing coupling of the system have led to the frequent occurrence of complex cascading failures, posing a serious threat to the safe and stable operation of the power grid.

[0030] In this situation, the influx of alarms and information within a short period of time places enormous pressure on dispatchers. Dispatchers must filter, analyze, and process this massive amount of information in a very short time to make accurate fault handling decisions. This not only places extremely high demands on dispatchers' professionalism and adaptability, but also requires further improvement in the quality and efficiency of fault handling.

[0031] Based on the above situation, the present application proposes a power grid fault handling auxiliary decision-making method and related devices, and the present application is described in detail below with reference to the embodiments and drawings.

[0032] like Figure 1 As shown in FIG. 1 , a first flow chart of the auxiliary decision-making method for handling power grid faults of the present application may include: S101, obtaining fault information in fault abnormality signal alarm information.

[0033] In practical applications, the system can receive real-time fault anomaly signal alerts from monitoring equipment, sensors, or the power grid management system. These alerts can include the time and location of the fault, the fault type (e.g., short circuit, open circuit, overload), the impact range, and the possible initial cause. Fault information typically includes the fault type (e.g., short circuit, open circuit, ground fault), time of occurrence, location (specific substation, line, etc.), and impact range (e.g., outage area, number of affected users).

[0034] In addition, to ensure the accuracy and timeliness of fault information, advanced Internet of Things technologies, big data analysis technologies, or artificial intelligence algorithms can be used to screen and verify fault information, eliminate false alarms and interference, and ensure that subsequent decisions are based on accurate data.

[0035] S102: Formulate an over-limit adjustment strategy based on the fault information, and execute the over-limit adjustment strategy to perform adjustments.

[0036] In practical applications, targeted over-limit adjustment strategies can be developed based on the specific content of the fault information, taking into account factors such as the fault type, severity, impact scope, and the current operating status of the power grid. It should be noted that over-limit adjustment strategies may include adjusting generator output, switching lines, and switching backup equipment on or off to restore normal grid operation or mitigate the impact of the fault. Once developed, over-limit adjustment strategies can be executed immediately.

[0037] S103, based on the fault information, search the grid dispatching regulations and grid control requirements to obtain a decision basis.

[0038] It's important to note that grid dispatching regulations and grid control requirements are crucial foundations for grid operation and fault handling. They define the organizational, command, guidance, and coordination principles for grid dispatching, as well as the operating specifications and safety requirements for grid equipment. Therefore, search results related to grid dispatching regulations and grid control requirements can serve as a basis for decision-making. This decision-making basis ensures the legality and compliance of fault handling, avoiding violations of relevant laws and regulations. Furthermore, it provides scientific guidance and recommendations for fault handling, improving efficiency and accuracy.

[0039] S104: Perform auxiliary analysis on the fault information to obtain auxiliary analysis results.

[0040] In practical applications, various methods and tools can be used to assist in analyzing fault information, such as data analysis and simulation. Data analysis can reveal the inherent patterns and characteristics of faults, providing a basis for developing response strategies. Simulation can simulate the fault's development and response effectiveness, allowing evaluation of the pros and cons of different strategies. The results of this auxiliary analysis can help decision-makers gain a more comprehensive understanding of the fault's circumstances and potential impacts, enabling them to make more accurate response decisions. They can also provide valuable insights for subsequent fault prevention and power grid optimization.

[0041] S105: Push corresponding operation instructions or suggestions based on the auxiliary analysis results.

[0042] The power grid fault handling decision-making support method is a systematic and complex process that requires close coordination and efficient operation of all links. The method proposed in this application can effectively improve the efficiency and accuracy of power grid fault handling and ensure the safe and stable operation of the power grid.

[0043] like Figure 2 As shown, this is a second flow chart of the power grid fault handling auxiliary decision-making method of the present application, which may include: S201, fault abnormal signal alarm.

[0044] In this embodiment, fault and abnormality signal alarms are obtained by reading comprehensive intelligent alarm information from the control cloud. Comprehensive intelligent alarm information typically includes the name of the faulty device, the alarm time, and the data source. Alarm monitoring equipment types can include DC, generators, AC lines, busbars, transformers, etc. Fault (or abnormality) types can include DC block, fault trip, and equipment return.

[0045] S202, fault information verification.

[0046] When verifying fault information, you can query SCADA (Supervisory Control And Data Acquisition) and PMU (Phasor Measurement Unit) data based on the faulty device name and alarm time to determine the following information: (1) Equipment operating status: equipment active and reactive power measurement 1 minute before and after the fault occurs; (2) Grid frequency: the highest value within 1 minute before and after the fault occurs; (3) Transmission section power and bus voltage: The transmission section power value and bus voltage measurement value 1 minute after the fault occurs.

[0047] S203: Generate an over-limit adjustment strategy.

[0048] Read the dynamic section limits and bus voltage upper and lower limits on the control cloud, and combine the transmission section power and bus voltage in step S202 to calculate the over-limit equipment, over-limit section, and over-limit bus voltage, as follows:

[0049]

[0050] in, For the i The active power of the cross-limit section, For the i The upper limit value of the cross-limit section, For the i The lower limit value of the cross-limit section, For the i The voltage value of the busbar that exceeds the limit, For the i The voltage upper limit of the over-limit bus, For the i The lower voltage limit of the busbar that exceeds the limit.

[0051] It should be noted that dynamic section limits on the control cloud refer to the maximum or minimum transmission power allowed at a transmission section under specific operating conditions. These limits are typically adjusted dynamically based on factors such as the real-time operating status of the power grid, equipment capabilities, and safety constraints. To read dynamic section limits, you can access the control cloud's interface and parse the returned data format to obtain the upper and lower limits for each section. Bus voltage upper and lower limits refer to the maximum and minimum values allowed for each bus voltage in the power grid. These limits are critical to ensuring the stable operation of the power grid. Similarly, when reading bus voltage upper and lower limits, you can also obtain the relevant data through the control cloud's interface and parse it into a usable format.

[0052] If there is a cross-section or voltage over-limit situation, the power system optimization decision can be called to generate an over-limit adjustment strategy. If there is no over-limit situation, step S204 is directly performed.

[0053] It should be noted that power system optimization decisions typically involve adjusting grid operation, reallocating equipment output, and optimizing reactive power compensation. These decisions can employ algorithms such as linear programming, nonlinear programming, and genetic algorithms to determine the optimal adjustment solution.

[0054] S204, grid regulation and control requirements are retrieved.

[0055] In practical applications, RAG (Retrieval-Augmented Generation) technology can be used to retrieve documents such as grid stability regulations and safety and control regulations, and push original content such as fault-related section limit adjustment rules, safety and control action strategies, and safety and control device adjustment requirements.

[0056] It's important to note that RAG technology is an innovative approach that combines the strengths of information retrieval and generative models. The retrieval module quickly locates the text most relevant to a user's question from a large-scale knowledge base. This information is then passed to the generative module to produce more accurate and useful responses or text. This technical approach aims to improve the accuracy and reliability of AI systems in answering natural language questions, particularly when handling knowledge-intensive tasks.

[0057] The following methods can be used: (1) Encode documents such as grid stability regulations and safety control regulations. Vector embedding models are usually used to convert document content into vector representations. These vectors are then stored in a vector database and indexed for subsequent rapid retrieval.

[0058] (2) When a user enters a query related to power grid failure, the RAG system first encodes the query into a vector using a pre-trained language model. Then, by calculating the similarity between the query vector and the document vector (e.g., cosine similarity), the most relevant documents to the query are retrieved from the index library.

[0059] (3) The retrieved documents contain original texts such as fault-related section limit adjustment rules, safety and control action strategies, and safety and control device adjustment requirements.

[0060] In practical applications, this information can be used in combination with the context of the user's query to generate answers or text that meet the user's needs. The RAG system can push the generated answers or text to the user, usually displaying the content most relevant to the fault in the form of highlights or summaries.

[0061] S205, auxiliary analysis of the fault cause.

[0062] You can query PMU (Phasor Measurement Unit, PMU) data and push dynamic curves such as voltage, current, and power of the faulty device before and after the fault occurs. Based on the changing patterns of the curves, you can help determine the cause of the fault.

[0063] It's important to note that the PMU provides real-time information on voltage amplitude, phase angle, and current at each grid node. This information is crucial for power system state estimation, fault location, and stability analysis. PMU data queries can typically be performed through backend software. Users select the time period and data type (such as voltage, current, or power) to view. After querying the data, the data can be displayed in a graph, and the graph display parameters can be adjusted as needed to more clearly visualize data changes. Dynamic curve push allows dynamic curves of voltage, current, and power, such as those before and after a fault, to be sent to relevant personnel for fault analysis.

[0064] Analyzing the changing patterns of dynamic curves such as voltage, current, and power provided by the PMU can assist in determining the cause of a fault. For example, a sudden drop in the voltage curve may indicate a line fault or equipment damage; abnormal fluctuations in the current curve may indicate equipment overload or a short circuit. In practical applications, the voltage and current changes at various nodes in the power grid before and after the fault can be compared to determine the location and type of the fault. PMU data can also be used for fault location. By constructing a busbar impedance matrix and reading the voltage offset measured by smart meters, the fault current can be estimated, thereby pinpointing the fault location. Determining the fault cause based on the changing patterns of dynamic curves can provide support for fault handling decisions. For example, if a line fault is identified, a repair team can be quickly dispatched for repair; if an equipment overload is identified, operating parameters can be adjusted promptly or backup equipment can be added.

[0065] S206: Pushing operations related to the faulty device.

[0066] By using RAG technology to retrieve grid dispatching and operation regulation documents, you can query the relevant equipment operations after a fault occurs, including whether to arrange a trial transmission of the faulty equipment, whether to perform faulty equipment isolation operations, etc., and push operations.

[0067] S207, information reporting.

[0068] In practical applications, the grid accident level rules can be determined according to the accident investigation and handling regulations, and a briefing report can be generated according to the fault information reporting template. The briefing report content can include three parts: basic situation, fault impact, and handling situation. As an example, the information contained in each part may include: (1) Basic information: time of fault occurrence, faulty equipment and fault type, execution of protection action, fault loss power or current value, and fault grid accident level.

[0069] (2) Fault impact: Which sections have changed their limit values after the fault? What are the limits before and after the fault? What are the newly added over-limit sections and over-limit voltages after the fault? What are the adjustment strategies for over-limit situations?

[0070] (3) Disposal status: the execution status of safety and control actions after the failure, and related operations for the faulty equipment.

[0071] The above briefing content is an example format, and specific information can be filled in according to actual conditions.

[0072] The power grid fault handling auxiliary decision-making method proposed in this application is aimed at the real-time power grid fault handling business needs. It arranges key links such as fault information verification, dispatching procedure query, over-limit adjustment strategy generation, and information reporting into a task flow. It combines technical methods such as knowledge retrieval enhancement, large model tool call, power system dynamic section limit and optimization decision model to realize real-time power grid fault auxiliary decision-making, improve the work efficiency of dispatchers in fault handling work, and contribute to the safe operation of the power grid.

[0073] like Figure 3 FIG. 1 is a schematic diagram of a power grid fault handling auxiliary decision-making system of the present application, which may include: An information module is used to obtain fault information in the fault abnormality signal alarm information; The adjustment module is used to formulate an over-limit adjustment strategy based on fault information and implement the over-limit adjustment strategy for adjustment; The retrieval module is used to retrieve the grid dispatching regulations and grid control requirements based on the fault information to obtain the basis for decision-making; An analysis module is used to perform auxiliary analysis on fault information and obtain auxiliary analysis results; The push module is used to push corresponding operation instructions or suggestions based on the auxiliary analysis results.

[0074] In some embodiments of the power grid fault handling auxiliary decision-making system of the present application, a verification module is further included; The verification module is used to verify the fault information after obtaining the fault information in the fault abnormality signal alarm information.

[0075] In some embodiments of the power grid fault handling auxiliary decision-making system of the present application, a reporting module is further included; The reporting module is used to generate reporting information including the fault situation, fault impact and fault handling situation after pushing the corresponding operation instruction or suggestion.

[0076] It should be noted that in the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of each module is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules can be combined or integrated into another device, or some features can be ignored or not executed. The modules described as separate components may or may not be physically separated. The components displayed as modules may be one physical unit or multiple physical units, that is, they may be located in one place, or they may be distributed in multiple different places. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0077] In addition, the modules in the various embodiments of the present invention may be integrated into a single processing unit, each module may exist physically separately, or two or more modules may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0078] An embodiment of the present application also provides an electronic device, which may include one or more processors, memories, and communication interfaces.

[0079] The memory, the communication interface, and the processor are coupled together. For example, the memory, the communication interface, and the processor may be coupled together via a bus.

[0080] The communication interface is used to transmit data with other devices. The memory stores computer program code. The computer program code includes computer instructions that, when executed by the processor, cause the electronic device to perform the steps of the above-mentioned power grid fault handling decision-making support method.

[0081] Among them, the processor can be a processor or a controller, for example, a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute the various exemplary logic blocks, modules and circuits described in conjunction with the contents of this disclosure. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The processor can be used to support electronic devices in executing the method steps provided in the above embodiments.

[0082] The bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The above buses may be divided into an address bus, a data bus, a control bus, etc.

[0083] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned power grid fault handling auxiliary decision-making method are implemented.

[0084] The computer-readable storage medium involved in this application includes random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD ROMs, or any other form of storage medium known in the technical field.

[0085] The above are merely preferred embodiments of the present application and are not intended to limit the present application. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A power grid fault handling auxiliary decision-making method, characterized in that: include: Obtain fault information from fault abnormality signal alarm information; Formulate an over-limit adjustment strategy based on fault information and implement the over-limit adjustment strategy to make adjustments; According to the fault information, search the grid dispatch regulations and grid control requirements to obtain the basis for decision-making; Perform auxiliary analysis on fault information to obtain auxiliary analysis results; According to the auxiliary analysis results, corresponding operation instructions or suggestions are pushed.

2. The power grid fault handling auxiliary decision-making method according to claim 1, characterized in that: The fault abnormality signal alarm information includes the name of the faulty device, the alarm time and the data source.

3. The power grid fault handling auxiliary decision-making method according to claim 1, characterized in that: After obtaining the fault information in the fault abnormality signal alarm information, the method further includes verifying the fault information.

4. The power grid fault handling auxiliary decision-making method according to claim 3, characterized in that: The method for verifying fault information includes: Respectively measuring the active power and reactive power at a preset time point before the fault occurs and at a preset time point after the fault occurs, and recording them as first measurement parameters; Obtaining the highest value of the grid frequency within a preset time range before the fault occurs, and recording it as the second measurement parameter; Obtaining the transmission section power value and bus voltage measurement value at a preset time point after the fault occurs, and recording them as the third measurement parameter; The fault information is verified according to the first measurement parameter, the second measurement parameter, and the third measurement parameter.

5. The power grid fault handling auxiliary decision-making method according to claim 1, characterized in that: The method for formulating an over-limit adjustment strategy includes: Determine whether one of the over-limit section and over-limit bus voltage is over-limit. If so, call the power system optimization decision and generate an over-limit adjustment strategy.

6. The power grid fault handling auxiliary decision-making method according to claim 1, characterized in that: The decision-making basis includes section limit adjustment rules, safety and control action strategies, and safety and control device adjustment requirements.

7. The power grid fault handling auxiliary decision-making method according to claim 1, characterized in that: The method for assisting in analyzing fault information includes: Query the phasor measurement unit data, push the voltage dynamic curve, current dynamic curve and power dynamic curve of the faulty equipment before and after the fault occurs, and assist in determining the cause of the fault based on the change rules of the dynamic curves.

8. The power grid fault handling auxiliary decision-making method according to claim 1, characterized in that: After pushing the corresponding operation instructions or suggestions, the method further includes: generating reporting information including the fault situation, fault impact and fault handling situation.

9. A power grid fault handling auxiliary decision-making system, characterized in that: include: An information module is used to obtain fault information in the fault abnormality signal alarm information; The adjustment module is used to formulate an over-limit adjustment strategy based on fault information and implement the over-limit adjustment strategy for adjustment; The retrieval module is used to retrieve the grid dispatching regulations and grid control requirements based on the fault information to obtain the basis for decision-making; An analysis module is used to perform auxiliary analysis on fault information and obtain auxiliary analysis results; The push module is used to push corresponding operation instructions or suggestions based on the auxiliary analysis results.

10. The power grid fault handling auxiliary decision-making system according to claim 1, characterized in that: Also includes verification module; The verification module is used to verify the fault information after obtaining the fault information in the fault abnormality signal alarm information.

11. The power grid fault handling auxiliary decision-making system according to claim 1, characterized in that: It also includes a reporting module; The reporting module is used to generate reporting information including the fault situation, fault impact and fault handling situation after pushing the corresponding operation instruction or suggestion.

12. An electronic device, characterized in that: include: A memory, one or more processors; the memory is coupled to the processor; wherein the memory stores computer program code, the computer program code includes computer instructions, and when the computer instructions are executed by the processor, the electronic device performs the steps of the power grid fault handling auxiliary decision-making method according to any one of claims 1 to 8.

13. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the power grid fault handling auxiliary decision-making method according to any one of claims 1 to 8 are implemented.

Images