Distribution network multi-dimensional measurement configuration method and system for improving risk perception capabilities

Abstract

The present invention relates to a distribution network multidimensional measurement configuration method and system for improving risk perception capabilities, which includes: analyzing data requirements for the types of disasters faced by the distribution network in the region; selecting distribution network multidimensional measurement equipment based on the analysis results of the data requirements and taking into account the micro-meteorological factors in the region; considering the real-time data transmitted by the multidimensional measurement equipment configured in the distribution network, comparing the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopting a distribution network risk perception accuracy improvement method; improving the distribution network risk perception capability, ensuring that the measurement equipment configuration has good economic efficiency as the goal, and taking into account the observability of important load nodes, using a genetic algorithm to solve the number and location of the multidimensional measurement configuration in the distribution network. The present invention achieves the improvement of the distribution network disaster loss identification capability in the event of failure of the electrical measurement device, and can be widely used in the field of electrical automation.

Description

Technical Field

[0001] The present invention relates to the field of electrical automation, and in particular to a multi-dimensional measurement configuration method and system for a distribution network aimed at improving risk perception capabilities. Background Art

[0002] The safe and stable operation of distribution networks is crucial to the harmonious and stable production and life of society and the general public. Therefore, detecting damage to distribution network components in disaster scenarios is crucial for restoration and repair efforts. However, existing electrical measurement devices in distribution networks cannot obtain timely information about component failures if a measurement failure occurs. This can hinder the command center's ability to determine de-icing scheduling and allocation of repair resources.

[0003] Existing multi-dimensional measurement configuration methods for distribution networks aimed at improving risk perception capabilities have lacked mature application strategies. While there is extensive research on micrometeorology, the significant differences in micrometeorological conditions across different regions and climates, as well as varying user needs, have made widespread application difficult. Summary of the Invention

[0004] In response to the above problems, the purpose of the present invention is to provide a distribution network multi-dimensional measurement configuration method and system for improving risk perception capabilities, which achieves the improvement of distribution network disaster loss identification capabilities in the event of failure of electrical measurement devices, and is stable and reliable.

[0005] To achieve the above objectives, the present invention adopts the following technical solutions: a distribution network multidimensional measurement configuration method for improving risk perception capabilities, which includes: analyzing the data requirements for accurately perceiving the distribution network operation risks based on the disaster types faced by the distribution network in the region; selecting the distribution network multidimensional measurement equipment based on the analysis results of the data requirements and taking into account the micro-meteorological factors in the region; considering the real-time data transmitted by the multidimensional measurement equipment configured in the distribution network, comparing the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopting a distribution network risk perception accuracy improvement method; with the goal of maximizing the distribution network risk perception capability while ensuring the good economic efficiency of the measurement equipment configuration, and taking into account the observability of important load nodes, a genetic algorithm is used to solve the number and location of the multidimensional measurement configuration in the distribution network.

[0006] Furthermore, the data requirements include: electrical quantity data, meteorological quantity data and other types of data.

[0007] Furthermore, the electrical quantity data demand analysis includes: sensing the conditions of operating elements such as grid switch information, network topology, unit output and power flow;

[0008] The meteorological data demand analysis includes: dynamically evaluating component failure rates in the distribution network, using actual meteorological measurement values ​​to replace key factors that change slowly, and using weather forecast values ​​for other factors that change quickly, to achieve accurate prediction of ice thickness;

[0009] The analysis of other types of data needs includes: collecting topographic information along the line, and understanding the model, safety factor, design standard, tower height, span, and longitude and latitude design background information of the line and tower; at the same time, in order to compare with the actual values, it is also necessary to obtain dynamic data of the distribution network lines under historical icing scenarios.

[0010] Furthermore, the selection of the multi-dimensional measurement equipment for the power distribution network includes: using a line micro-meteorological monitoring unit for line condition monitoring; monitoring meteorological parameters around the line through the line micro-meteorological monitoring unit;

[0011] The line micro-meteorological monitoring unit includes a rainfall sensor, a humidity sensor, a temperature sensor, a wind speed sensor and a wind direction sensor.

[0012] Furthermore, the method for improving the accuracy of distribution network risk perception includes:

[0013] Considering the real-time meteorological data transmitted by the line micrometeorological monitoring unit configured in the distribution network, and comparing the line failure probability result obtained based on the distribution network disaster mechanism model with the actual line failure probability, the accuracy of distribution network component fault judgment is obtained.

[0014] Furthermore, the method of using a genetic algorithm to solve the number and location of multi-dimensional measurement configurations in the distribution network includes:

[0015] Establish an indicator system to measure the effectiveness of multi-dimensional measurement configuration, accurately perceive the damage situation of the lines where important load nodes are located, and set the distance between the micro-meteorological monitoring unit and the important load nodes;

[0016] Perform multi-dimensional measurement optimization configuration of the distribution network, set the objective function and constraints, including measurement number constraints and observability constraints of important load nodes.

[0017] Furthermore, the indicator system includes: the cost of configuring multi-dimensional meteorological measurements, including the one-time investment cost of new equipment and the annual operation and maintenance cost of the new equipment.

[0018] A distribution network multidimensional measurement configuration system for improving risk perception capabilities comprises: a demand analysis module, which analyzes data requirements for accurately perceiving distribution network operation risks based on the types of disasters faced by the distribution network in a region; a selection module, which selects distribution network multidimensional measurement equipment based on the analysis results of the data requirements and takes into account micro-meteorological factors in the region; a comparison module, which considers the real-time data transmitted by the multidimensional measurement equipment configured in the distribution network, compares the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopts a method for improving distribution network risk perception accuracy; and a solution module, which adopts a genetic algorithm to solve the number and location of multidimensional measurement configurations in the distribution network with the goal of maximizing the risk perception capability of the distribution network while ensuring the good economic efficiency of the measurement equipment configuration and taking into account the observability of important load nodes.

[0019] A computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the above methods.

[0020] A computing device comprises: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the above methods.

[0021] The present invention has the following advantages due to the adoption of the above technical solution:

[0022] The present invention adopts an objective technical design of a multi-dimensional measurement configuration decision process, which not only improves the ability to identify distribution network disasters and losses in the event of failure of electrical measurement devices, but also has good scientificity, a wide range of applications, and is stable and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of a method for configuring multi-dimensional measurement of a distribution network for improving risk perception capabilities according to an embodiment of the present invention;

[0024] Figure 2 It is a schematic diagram of the structure of a computing device in one embodiment of the present invention. DETAILED DESCRIPTION

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0026] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0027] The present invention provides a method and system for configuring multidimensional measurement of distribution networks for improving risk perception capabilities, including analyzing the data required for accurately perceiving the operating risks of distribution networks based on the types of disasters faced by distribution networks in a region; selecting multidimensional measurement devices for distribution networks based on the results of data demand analysis, taking into account the micro-meteorological factors in the region; and improving the accuracy of risk perception of distribution networks by considering the real-time data transmitted by the multidimensional measurement equipment configured in the distribution network. A genetic algorithm is also used to solve the number and location of multidimensional measurement configurations in the distribution network. The multidimensional measurement configuration method for distribution networks for improving risk perception capabilities provided by the present invention, through the objective technical design of the innovative multidimensional measurement configuration decision-making process, not only achieves the improvement of the ability to identify damage to distribution networks in the event of failure of electrical measurement devices, but also has good scientificity, a wide range of applicability, and is stable and reliable.

[0028] In one embodiment of the present invention, a method for configuring multi-dimensional measurement of a distribution network for improving risk perception capability is provided. This embodiment uses the method applied to a terminal as an example. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and implemented through the interaction between the terminal and the server. In this embodiment, Figure 1 As shown, the method includes the following steps:

[0029] 1) Analyze the data requirements for accurately sensing the operational risks of distribution networks based on the types of disasters they face in the region;

[0030] 2) Based on the analysis results of data requirements and taking into account the micro-meteorological factors in the region, select multi-dimensional measurement equipment for the distribution network;

[0031] 3) Considering the real-time data transmitted by the multi-dimensional measurement equipment configured in the distribution network, the line failure probability results obtained based on the distribution network disaster mechanism model are compared with the actual line failure probability, and a distribution network risk perception accuracy improvement method is adopted;

[0032] 4) With the goal of maximizing the risk perception capability of the distribution network and ensuring the economic efficiency of the measurement equipment configuration, and considering the observability of important load nodes, a genetic algorithm is used to solve the number and location of multidimensional measurement configurations in the distribution network.

[0033] In the above step 1), the data requirements include: electrical quantity data, meteorological quantity data and other types of data.

[0034] The electrical quantity data demand analysis includes: sensing the operating conditions of the power grid's switch information, network topology, unit output, and power flow;

[0035] To accurately perceive distribution network operational risks and formulate appropriate dispatch and repair plans, it's necessary to understand the network's real-time operational status. This requires understanding grid operational elements such as switch information, network topology, unit output, and power flow. Existing electrical measurement equipment in distribution networks primarily includes Supervisory Control and Data Acquisition (SCADA), Advanced Metering Infrastructure (AMI), and Phase Measurement Units (PMUs), all of which enable real-time measurement and acquisition of electrical quantities within the distribution network.

[0036] Meteorological data demand analysis includes the following: The actual power system environment and meteorological conditions are multifaceted and diverse, and multiple extreme weather conditions often occur simultaneously. To dynamically assess component failure rates in the distribution network, measured meteorological values ​​are used to replace key factors that change slowly, while weather forecast values ​​are used for other faster-changing factors to achieve accurate predictions of ice thickness.

[0037] Other types of data demand analysis include: Micrometeorology can be affected by certain special terrains, so to achieve accurate risk assessment, it is necessary to collect a large amount of terrain and geomorphological information along the line. It is also necessary to understand the model, safety factor, design standard, tower height, span, and longitude and latitude design background information of the line and tower; at the same time, in order to compare with the actual values, it is also necessary to obtain dynamic data of the distribution network lines under historical icing scenarios.

[0038] In the above step 2), selecting the multi-dimensional measurement equipment of the distribution network includes: using a line micro-meteorological monitoring unit for line condition monitoring; monitoring meteorological parameters around the line through the line micro-meteorological monitoring unit;

[0039] The line micrometeorological monitoring unit includes a rainfall sensor, a humidity sensor, a temperature sensor, a wind speed sensor and a wind direction sensor.

[0040] In this embodiment, due to the continuous upgrading of power system measurement equipment and the development of information and communication technologies, power system measurement has basically achieved real-time data transmission. Currently, the most important measurement data in China comes from Supervisory Control and Data Acquisition (SCADA), Advanced Measurement Infrastructure (AMI), and Phase Measurement Units (PMUs). Table 1 compares the differences between SCADA, AMI, and PMUs.

[0041] Table 1 Comparison of SCADA, AMI, and PMU

[0042]

[0043] Existing equipment used for line condition monitoring includes line microclimate monitoring units. Because disasters exhibit typical microtopographic and microclimate characteristics, these units can be used to monitor meteorological parameters such as humidity, temperature, sunshine intensity, rainfall, wind speed, wind direction, and air pressure in the surrounding environment. The meteorological sensing units in these microclimate monitoring sensors include rainfall sensors, humidity sensors, temperature sensors, wind speed sensors, and wind direction sensors.

[0044] In step 3) above, the method for improving the accuracy of distribution network risk perception includes:

[0045] Considering the real-time meteorological data transmitted by the line micrometeorological monitoring unit configured in the distribution network, and comparing the line failure probability result obtained based on the distribution network disaster mechanism model with the actual line failure probability, the accuracy of distribution network component fault judgment is obtained.

[0046] In this embodiment, the real-time meteorological data transmitted by the micro-meteorological monitoring unit configured in the distribution network is considered, and the line failure probability result obtained based on the distribution network disaster mechanism model is compared with the actual line failure probability. The accuracy rate of distribution network component fault judgment is obtained as follows:

[0047]

[0048] Where C W represents the annual equivalent forecast error; N t Indicates the number of disasters that occurred in a year; N n represents the number of nodes in the network; y represents the percentage error between the calculated line failure probability and the actual line failure probability.

[0049]

[0050] Where A represents the calculated value of component failure rate; A * Indicates the actual value of component failure.

[0051] By distributing micro-meteorological monitoring units at different nodes in the distribution network and calculating the fault judgment accuracy of all components in the distribution network, it can be found that when the calculated value of y is the smallest, it means that the calculation error of the overall component failure rate of the distribution network is the smallest. Configuring micro-meteorological monitoring units at these nodes can maximize the improvement of the risk perception accuracy of the distribution network.

[0052] In step 4) above, a genetic algorithm is used to solve the number and location of multi-dimensional measurement configurations in the distribution network, including:

[0053] 4.1) Establish an indicator system to measure the effectiveness of multi-dimensional measurement configuration;

[0054] (1) Economical:

[0055] The indicator system includes: the cost of configuring multi-dimensional meteorological measurements, including the one-time investment cost of new equipment and the annual operation and maintenance cost of the new equipment.

[0056] C I =C inv +C ma +C on (3)

[0057] Where: C I represents the annual equivalent investment cost; C inv represents the purchase cost of configuring the micro-meteorological monitoring unit; C ma represents the annual maintenance cost of the micrometeorological monitoring unit; C on Represents the annual operating cost of the micrometeorological monitoring unit.

[0058] a. One-time investment cost of micrometeorological monitoring unit

[0059] C inv =P T NA(r,n) (4)

[0060] Where: P T represents the present unit price of the micrometeorological monitoring system; N represents the total number of micrometeorological detection systems configured; A(r,n) represents the factor measuring economic efficiency;

[0061]

[0062] Where r represents the discount rate; n represents the service life of the micrometeorological monitoring system.

[0063] b. Annual maintenance cost of micrometeorological monitoring unit

[0064] C ma =ρC inv (6)

[0065] Where: ρ represents the proportion of the operation and maintenance cost of the micrometeorological monitoring system to the purchase cost.

[0066] c. Annual operating costs of the micrometeorological monitoring unit

[0067]

[0068] Where: a represents the unit electricity operation cost; Δt represents the length of the time period; P 1i Represents the working power consumption of the micro-meteorological monitoring unit; P 2i Indicates the standby power consumption of the micro-meteorological monitoring unit; b1 and b2 indicate the working state of the micro-meteorological monitoring unit. When in working state, b1 is 1 and b2 is 0. When in standby state, b1 is 0 and b2 is 1.

[0069] (2) Observability:

[0070] Accurately perceive the damage situation of the lines where important load nodes are located. Since the difference in micro-meteorological conditions is small within a range of one to two kilometers, the distance between the micro-meteorological monitoring unit and the important load nodes is set;

[0071] 0≤d i ≤1.8km (8)

[0072] Where: d i It represents the straight-line distance from the micrometeorological monitoring unit closest to the important load node i.

[0073] 4.2) Perform multi-dimensional measurement optimization configuration of the distribution network, set the objective function and constraints, including the number of measurements and the observability constraints of important load nodes.

[0074] In this embodiment, the objective function is: by configuring micrometeorological monitoring units in the distribution network, the risk perception capability of the distribution network is improved. Two goals are to be achieved: one is to minimize the annual equivalent investment cost of configuring the micrometeorological monitoring units, and the other is to minimize the error between the calculated value of the failure rate of all components of the distribution network after the micrometeorological monitoring units are configured and the actual value of the component failure rate, so as to achieve the maximum improvement of the risk perception capability of the distribution network while ensuring that the configuration of the measurement equipment has good economy.

[0075]

[0076] Where: C I represents the annual equivalent investment cost; C W represents the annual equivalent forecast error.

[0077] In this embodiment, the constraints include:

[0078] a. Measurement quantity constraints:

[0079] Because microclimate monitoring units are relatively expensive, it is not feasible to install them at every node in the distribution network. Therefore, we can only configure them at appropriate nodes within the distribution network, with a fixed number of microclimate monitoring units, to maximize the risk perception capabilities of the distribution network. Therefore, the number of measurement configurations is constrained as follows:

[0080] 0≤n≤7 (10)

[0081] Where: n represents the number of configured micrometeorological monitoring units.

[0082] b. Observability constraints on important load nodes

[0083] 0≤d i ≤1.8km (10)

[0084] Where: d i It indicates the straight-line distance from the micro-meteorological monitoring unit closest to the important load node.

[0085] In one embodiment of the present invention, a distribution network multi-dimensional measurement configuration system for improving risk perception capability is provided, which includes:

[0086] The demand analysis module analyzes the data needs for accurately sensing the operation risks of the distribution network based on the types of disasters faced by the distribution network in the region;

[0087] Selection module: Based on the analysis results of data requirements and taking into account the micro-meteorological factors in the area, select the multi-dimensional measurement equipment for the distribution network;

[0088] The comparison module considers the real-time data transmitted by the multi-dimensional measurement equipment configured in the distribution network, compares the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopts the distribution network risk perception accuracy improvement method;

[0089] The solution module aims to maximize the risk perception capability of the distribution network while ensuring the economic efficiency of the measurement equipment configuration. At the same time, it considers the observability of important load nodes and uses a genetic algorithm to solve the number and location of multidimensional measurement configurations in the distribution network.

[0090] The system provided in this embodiment is used to execute the above-mentioned method embodiments. Please refer to the above-mentioned embodiments for specific processes and detailed contents, which will not be repeated here.

[0091] like Figure 2FIG. 1 is a schematic diagram of the structure of a computing device provided in one embodiment of the present invention. The computing device may be a terminal and may include: a processor, a communication interface, a memory, a display screen, and an input device. The processor, communication interface, and memory communicate with each other via a communication bus. The processor is used to provide computing and control capabilities. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. When the computer program is executed by the processor, it implements a multi-dimensional measurement configuration method. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The communication interface is used to communicate with an external terminal via wired or wireless communication. The wireless communication may be achieved via Wi-Fi, a management network, NFC (near field communication), or other technologies. The display screen may be a liquid crystal display or an electronic ink display screen. The input device may be a touch screen covering the display screen, or may be a key, trackball, or touchpad provided on the computing device housing, or may be an external keyboard, touchpad, or mouse. The processor can call the logic instructions in the memory to execute the following method: analyze the data requirements for accurately perceiving the operation risks of the distribution network based on the disaster types faced by the distribution network in the region; based on the analysis results of the data requirements and taking into account the micro-meteorological factors in the region, select the multi-dimensional measurement equipment of the distribution network; consider the real-time data transmitted by the multi-dimensional measurement equipment configured in the distribution network, compare the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopt a distribution network risk perception accuracy improvement method; with the goal of maximizing the risk perception capability of the distribution network while ensuring the good economic efficiency of the measurement equipment configuration, and taking into account the observability of important load nodes, adopt a genetic algorithm to solve the number and location of the multi-dimensional measurement configuration in the distribution network.

[0092] In addition, the logical instructions in the above-mentioned memory can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0093] Those skilled in the art will understand that Figure 2 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computing device to which the solution of the present application is applied. The specific computing device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0094] In one embodiment of the present invention, a computer program product is provided, comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided by the above-mentioned method embodiments, for example, including: analyzing data requirements for accurately perceiving distribution network operation risks based on the types of disasters faced by distribution networks in a region; selecting multidimensional measurement equipment for the distribution network based on the analysis results of the data requirements and taking into account micro-meteorological factors in the region; comparing line failure probability results obtained based on a distribution network disaster-causing mechanism model with actual line failure probability, taking into account real-time data transmitted by the multidimensional measurement equipment configured in the distribution network, and adopting a method for improving the accuracy of distribution network risk perception; and using a genetic algorithm to solve the number and location of multidimensional measurement configurations in the distribution network with the goal of maximizing the risk perception capability of the distribution network while ensuring good economic efficiency of the measurement equipment configuration and taking into account the observability of important load nodes.

[0095] In one embodiment of the present invention, a non-transitory computer-readable storage medium is provided, which stores server instructions, and the computer instructions enable a computer to execute the methods provided by the above embodiments, for example, including: analyzing the data requirements for accurately perceiving the operation risks of the distribution network based on the types of disasters faced by the distribution network in the region; selecting multidimensional measurement equipment for the distribution network based on the analysis results of the data requirements and taking into account the micro-meteorological factors in the region; considering the real-time data transmitted by the multidimensional measurement equipment configured in the distribution network, comparing the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopting a method for improving the accuracy of distribution network risk perception; with the goal of maximizing the risk perception capability of the distribution network while ensuring the good economic efficiency of the measurement equipment configuration, and taking into account the observability of important load nodes, adopting a genetic algorithm to solve the number and location of the multidimensional measurement configuration in the distribution network.

[0096] The above embodiment provides a computer-readable storage medium, whose implementation principle and technical effects are similar to those of the above method embodiment, and will not be repeated here.

[0097] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0098] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A multi-dimensional measurement configuration method for distribution network for improving risk perception capability, characterized in that: include: Analyze the data needs for accurately sensing the operational risks of distribution networks based on the types of disasters they face in the region; Based on the analysis results of data requirements and taking into account the micro-meteorological factors in the area, select multi-dimensional measurement equipment for the distribution network; Considering the real-time data transmitted by the multi-dimensional measurement equipment configured in the distribution network, the line failure probability results obtained based on the distribution network disaster mechanism model are compared with the actual line failure probability, and a distribution network risk perception accuracy improvement method is adopted; With the goal of maximizing the risk perception capability of the distribution network while ensuring the economic efficiency of the measurement equipment configuration, and taking into account the observability of important load nodes, a genetic algorithm is used to solve the number and location of multi-dimensional measurement configurations in the distribution network; The method for improving the accuracy of distribution network risk perception includes: Considering the real-time meteorological data transmitted by the line micro-meteorological monitoring unit configured in the distribution network, and comparing the line fault probability results obtained based on the distribution network disaster mechanism model with the actual line fault probability, the accuracy of distribution network component fault judgment is obtained; The goal is to maximize the risk perception capability of the distribution network while ensuring the economic efficiency of the measurement equipment configuration. The objective function is: by configuring micrometeorological monitoring units in the distribution network, the risk perception capability of the distribution network can be improved. Two goals must be achieved: one is to minimize the annual equivalent investment cost of configuring the micrometeorological monitoring units, and the other is to minimize the error between the calculated value of the failure rate of all components in the distribution network after the micrometeorological monitoring units are configured and the actual value of the component failure rate, so as to achieve the maximum improvement of the risk perception capability of the distribution network while ensuring the economic efficiency of the measurement equipment configuration.

2. The method for configuring multi-dimensional measurement of distribution network for improving risk perception capability according to claim 1, characterized in that: The data requirements include: electrical quantity data, meteorological quantity data and other types of data.

3. The multi-dimensional measurement configuration method for distribution network for improving risk perception capability according to claim 2, characterized in that: The electrical quantity data demand analysis includes: sensing the status of operating elements such as grid switch information, network topology, unit output and power flow; The meteorological data demand analysis includes: dynamically evaluating component failure rates in the distribution network, using actual meteorological measurement values ​​to replace key factors that change slowly, and using weather forecast values ​​for other factors that change quickly, to achieve accurate prediction of ice thickness; The analysis of other types of data needs includes: collecting topographic information along the line, and understanding the model, safety factor, design standard, tower height, span, and longitude and latitude design background information of the line and tower; at the same time, in order to compare with the actual values, it is also necessary to obtain dynamic data of the distribution network lines under historical icing scenarios.

4. The method for configuring multi-dimensional measurement of distribution network for improving risk perception capability according to claim 1, characterized in that: The multi-dimensional measurement equipment for the power distribution network is selected to include: using a line micro-meteorological monitoring unit for line condition monitoring; monitoring meteorological parameters around the line through the line micro-meteorological monitoring unit; The line micro-meteorological monitoring unit includes a rainfall sensor, a humidity sensor, a temperature sensor, a wind speed sensor and a wind direction sensor.

5. The method for configuring multi-dimensional measurement of distribution network for improving risk perception capability according to claim 1, characterized in that: The method of using a genetic algorithm to solve the number and location of multi-dimensional measurement configurations in a distribution network includes: Establish an indicator system to measure the effectiveness of multi-dimensional measurement configuration, accurately perceive the damage situation of the lines where important load nodes are located, and set the distance between the micro-meteorological monitoring unit and the important load nodes; Perform multi-dimensional measurement optimization configuration of the distribution network, set the objective function and constraints, including measurement number constraints and observability constraints of important load nodes.

6. The method for configuring multi-dimensional measurement of distribution network for improving risk perception capability according to claim 5, characterized in that: The indicator system includes: the cost of configuring multi-dimensional meteorological measurements, including the one-time investment cost of new equipment and the annual operation and maintenance cost of the new equipment.

7. A multi-dimensional measurement configuration system for distribution network aimed at improving risk perception capability, characterized in that: include: The demand analysis module analyzes the data needs for accurately sensing the operation risks of the distribution network based on the types of disasters faced by the distribution network in the region; Selection module: Based on the analysis results of data requirements and taking into account the micro-meteorological factors in the area, select the multi-dimensional measurement equipment for the distribution network; The comparison module considers the real-time data transmitted by the multi-dimensional measurement equipment configured in the distribution network, compares the line failure probability results obtained based on the distribution network disaster mechanism model with the actual line failure probability, and adopts the distribution network risk perception accuracy improvement method; The solution module aims to maximize the risk perception capability of the distribution network while ensuring the economic efficiency of the measurement equipment configuration. It also considers the observability of important load nodes and uses a genetic algorithm to solve the number and location of multi-dimensional measurement configurations in the distribution network. The method for improving the accuracy of distribution network risk perception includes: Considering the real-time meteorological data transmitted by the line micro-meteorological monitoring unit configured in the distribution network, and comparing the line fault probability results obtained based on the distribution network disaster mechanism model with the actual line fault probability, the accuracy of distribution network component fault judgment is obtained; The goal is to maximize the risk perception capability of the distribution network while ensuring the economic efficiency of the measurement equipment configuration. The objective function is: by configuring micrometeorological monitoring units in the distribution network, the risk perception capability of the distribution network can be improved. Two goals must be achieved: one is to minimize the annual equivalent investment cost of configuring the micrometeorological monitoring units, and the other is to minimize the error between the calculated value of the failure rate of all components in the distribution network after the micrometeorological monitoring units are configured and the actual value of the component failure rate, so as to achieve the maximum improvement of the risk perception capability of the distribution network while ensuring the economic efficiency of the measurement equipment configuration.

8. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any one of the methods of claims 1 to 6 .

9. A computing device, characterized in that include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any one of the methods according to claims 1 to 6.

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