Fault distance calculation method and system for power distribution network of power system

Abstract

The invention discloses a fault distance calculation method and system for a power system power distribution network. The method comprises the steps that a power engineer monitoring end sends a fault distance safety self-checking signal to a power distribution network real-time operation edge calculation gateway monitoring platform; after the power distribution network real-time operation edge computing gateway monitoring platform receives a fault distance safety self-checking signal, the fault distance safety self-checking signal is detected. The multi-modal information integration end under different user groups collects electrical parameters and load data of the power distribution network of the power system in each fault area under different user groups and equipment state parameters of the fault distance of the power distribution network of the power system in each fault area, stores the collected data and sends the collected data to the power engineer monitoring end; and the signal is sent to the power system power distribution network fault distance calculation model module through the signal collection processing server. According to the invention, more accurate fault positioning information can be provided for power engineers, the troubleshooting time is shortened, and safe and stable operation of the power distribution network is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of distribution network fault distance monitoring, and in particular to a method and system for calculating the fault distance of a power system distribution network. Background Art

[0002] With the continuous growth of electricity demand, the power distribution network of the power system undertakes the important task of efficiently and safely delivering electricity to each user. However, the distribution network is easily affected by external factors in a complex operating environment, such as short circuit faults, single-phase grounding, equipment aging and other problems. The occurrence of these faults will cause power supply interruptions in the power grid, affecting the stability of the power system and the normal power consumption of users. Therefore, the accurate calculation of the fault distance is of vital importance for quickly locating the fault point, shortening the repair time, and improving the efficiency of the power grid operation.

[0003] At present, the fault location of the power system mainly relies on traditional fault distance calculation methods, such as impedance method, current change method, voltage change method, etc. These methods calculate the location of the fault point by measuring electrical parameters such as current, voltage, impedance, etc., combined with the impedance characteristics of the line. However, in the complex distribution network structure, the traditional method has the problems of low calculation accuracy and slow response speed when facing multi-path faults, noise interference and nonlinear data characteristics, which makes it difficult to meet the needs of modern smart grids for rapid fault location and precise control. In order to solve the above problems, this application proposes a fault distance calculation method and system for the distribution network of the power system. Summary of the invention

[0004] In order to overcome the shortcomings and deficiencies of the prior art, the present invention provides a method and system for calculating the fault distance of a power distribution network.

[0005] An embodiment of the present invention provides a method for calculating a fault distance of a power distribution network, which includes:

[0006] S100, the power engineer monitoring terminal sends the fault distance safety self-check signal to the real-time operation edge computing gateway monitoring platform of the distribution network;

[0007] S200, after the real-time operation edge computing gateway monitoring platform of the distribution network receives the fault distance safety self-check signal, the multimodal information integration terminal under different user groups collects the electrical parameters and load data of different user groups of the power system distribution network in each fault area, and the equipment status parameters of the fault distance of the power system distribution network in each fault area, and stores and sends the collected data to the power engineer monitoring terminal;

[0008] S300, the power engineer monitoring terminal determines whether the electrical parameters, load data, and equipment status parameters of the different user groups are within the preset operation safety limit threshold; if the electrical parameters, load data, and equipment status parameters of the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server;

[0009] S400, the power system distribution network fault distance calculation model module, combines convolutional neural network and whale optimization algorithm to calculate fault distance.

[0010] Furthermore, the electrical parameters and load data for different user groups include: current, voltage, impedance, power, frequency, phase and load fluctuation.

[0011] Furthermore, the equipment status parameters include: transformer parameters, circuit breaker and switch equipment parameters.

[0012] Furthermore, it also includes: pre-setting a fault distance hazard level determination model analysis library in the power engineer monitoring terminal, and storing the electrical parameters and load data under the different user groups, the operating safety limit thresholds of the equipment status parameters, and the fault distance hazard level information in the fault distance hazard level determination model analysis library.

[0013] Furthermore, if the electrical parameters, load data and equipment status parameters of the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server, including:

[0014] The power engineer monitoring terminal determines the fault distance danger level in the fault distance danger level determination model analysis library with the received electrical parameters and load data of different user groups and equipment status parameters;

[0015] The power engineer monitoring terminal sends a corresponding distribution network fault distance to be calculated prompt signal to the signal collection processing server according to the determination result.

[0016] Furthermore, if the electrical parameters, load data and equipment status parameters of the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server, and also includes:

[0017] The power engineer monitoring terminal sends a power outage or power transmission start signal to the distribution control room according to the determination result to control the power supply of the power distribution network of the power system in the fault area.

[0018] Further, the signal set processing server sends the fault distance calculation model module of the power system distribution network, including: the signal set processing server sends the distribution network fault distance to be calculated prompt signal to the power system distribution network fault distance calculation model module through the cloud platform and the big data analysis platform.

[0019] The embodiment of the present invention also provides a fault distance calculation system for a power system distribution network, including a distribution network comprehensive information processing center, multiple power system distribution network fault distance monitoring points, a signal set processing server, and a power system distribution network fault distance calculation model module, wherein the distribution network comprehensive information processing center is provided with a power engineer monitoring terminal, and the multiple power system distribution network fault distance monitoring points are all provided with a distribution network real-time operation edge computing gateway monitoring platform;

[0020] The power engineer monitoring terminal is used to send a fault distance safety self-check signal to the real-time operation edge computing gateway monitoring platform of the distribution network;

[0021] The real-time operation edge computing gateway monitoring platform of the distribution network is used to collect electrical parameters and load data of different user groups of the power system distribution network in each fault area and equipment status parameters of the fault distance of the power system distribution network in each fault area after receiving the fault distance safety self-check signal, and store and send the collected data to the power engineer monitoring terminal;

[0022] The power engineer monitoring end is also used to determine whether the electrical parameters, load data and equipment status parameters of the different user groups are within the preset operation safety limit thresholds; if the electrical parameters, load data and equipment status parameters of the different user groups are not within the preset operation safety limit thresholds, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server.

[0023] Furthermore, the signal set processing server is used to send the distribution network fault distance to be calculated prompt signal to the power system distribution network fault distance calculation model module through the cloud platform and the big data analysis platform.

[0024] Furthermore, the power engineer monitoring terminal is used to judge the fault distance hazard level in the fault distance hazard level judgment model analysis library based on the received electrical parameters and load data of different user groups, equipment status parameters, and the fault distance hazard level judgment model analysis library; and according to the judgment result, send the corresponding distribution network fault distance to be calculated prompt signal to the signal collection processing server.

[0025] An embodiment of the present invention provides a fault distance calculation method and system for a power system distribution network, wherein the method includes: a power engineer monitoring end sends a fault distance safety self-check signal to a distribution network real-time operation edge computing gateway monitoring platform; after the distribution network real-time operation edge computing gateway monitoring platform receives the fault distance safety self-check signal, a multimodal information integration end under different user groups collects electrical parameters and load data under different user groups of the power system distribution network in each fault area, and equipment status parameters of the fault distance of the power system distribution network in each fault area, and stores and sends the collected data to the power engineer monitoring end; the power engineer monitoring end determines whether the electrical parameters, load data, and equipment status parameters under the different user groups are within a preset operation safety limit threshold; if the electrical parameters, load data, and equipment status parameters under the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated, and sent to the power system distribution network fault distance calculation model module through a signal collection processing server.

[0026] Beneficial effects:

[0027] The present invention greatly improves the calculation accuracy and efficiency of fault distance by introducing convolutional neural network and whale optimization algorithm in deep learning. Convolutional neural network has powerful feature extraction ability and can automatically learn the core features in fault signals, including the spatiotemporal relationship of complex electrical parameters such as current, voltage, impedance and frequency. Unlike the traditional physical model method, convolutional neural network does not need to manually set complex parameter models, and can adapt to the nonlinear and time-varying characteristics in the operation of distribution network, especially in complex situations such as load fluctuation, signal noise interference and multi-path fault propagation, it can still extract high-quality fault signal features. At the same time, in order to further improve the accuracy of fault distance calculation, the system introduces whale optimization algorithm to globally optimize the results of preliminary prediction of convolutional neural network. The whale algorithm simulates the predation behavior of whales, has powerful global search ability and fast convergence characteristics, and can effectively find the optimal solution of fault distance in the solution space to avoid falling into local optimum. Through the organic combination of convolutional neural network and whale optimization algorithm, the system can not only quickly identify the fault type and location, but also significantly improve the accuracy and robustness of fault distance prediction, ensuring that the results are more in line with actual working conditions. This method overcomes the limitations of traditional computing methods that are susceptible to noise interference and insufficient accuracy. It is particularly suitable for distribution network environments with complex topologies and multimodal data. It can provide power engineers with more accurate fault location information, shorten fault troubleshooting time, and ensure the safe and stable operation of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0029] Figure 1 A schematic diagram of a flow chart of a method for calculating a fault distance of a power distribution network provided by an embodiment of the present invention;

[0030] Figure 2 A structural diagram of a fault distance calculation system for a power distribution network provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other. The present application is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0032] See also Figure 1 , a flow chart of a method for calculating a fault distance of a power distribution network provided by an embodiment of the present invention, the method comprising steps S100 to S400:

[0033] Step S100: The power engineer monitoring terminal sends a fault distance safety self-check signal to the real-time operation edge computing gateway monitoring platform of the distribution network;

[0034] Step S200: After the real-time operation edge computing gateway monitoring platform of the distribution network receives the fault distance safety self-check signal, the multimodal information integration terminal under different user groups collects electrical parameters and load data under different user groups of the power system distribution network in each fault area, and the equipment status parameters of the fault distance of the power system distribution network in each fault area, and stores and sends the collected data to the power engineer monitoring terminal;

[0035] Step S300, the power engineer monitoring terminal determines whether the electrical parameters, load data, and equipment status parameters of the different user groups are within the preset operation safety limit threshold; if the electrical parameters, load data, and equipment status parameters of the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server;

[0036] Step S400, the power system distribution network fault distance calculation model module combines the convolutional neural network and the whale optimization algorithm to perform fault distance calculation.

[0037] In the embodiment of the present invention, the power engineer monitoring terminal can send a fault distance safety self-check signal to the distribution network real-time operation edge computing gateway monitoring platform, and the distribution network real-time operation edge computing gateway monitoring platform can control the collection of electrical parameters and load data under different user groups and equipment status parameters according to the fault distance safety self-check signal and send it to the power engineer monitoring terminal, so that the power engineer monitoring terminal can determine whether the electrical parameters and load data and equipment status parameters under different user groups are within the operation safety limit threshold. If not, the distribution network fault distance to be calculated prompt signal is automatically generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server. The management personnel can timely understand the fault distance danger level judgment information of the power system distribution network in the fault area, and timely process the fault distance danger level judgment to prevent the power system distribution network in the fault area from being damaged. The method provided in the embodiment of the present invention can automatically perform inspections, and can timely send out the distribution network fault distance to be calculated prompt signal, which improves the inspection efficiency and reduces the cost. The fault distance calculation method of the power system distribution network provided in the embodiment of the present invention is mainly executed on the power engineer monitoring terminal and the distribution network real-time operation edge computing gateway monitoring platform, and the response speed is fast.

[0038] Specifically, in step S100, the power engineer monitoring end can send the fault distance safety self-check signal to the distribution network real-time operation edge computing gateway monitoring platform in different ways, for example, sending the fault distance safety self-check signal in a timed manner, that is, sending the fault distance safety self-check signal once every same period of time, which can be a system default period or a custom period.

[0039] In addition, the fault distance safety self-check signal can be sent irregularly, that is, the fault distance safety self-check signal is sent every different time intervals. In this way, it can be manually started by the management personnel, that is, the management personnel can determine whether it is necessary to send the fault distance safety self-check signal based on their own experience or the actual fault distance. It is also possible to divide each cycle into several different time periods in advance, and set a time interval for different time periods, so that within a time period, the fault distance safety self-check signal is sent regularly according to the corresponding time interval. This method is actually also a scheduled inspection, but the time interval is different in different time periods. The advantage of setting different time periods is that the detection frequency can be set in a targeted manner.

[0040] In the step S200, the multimodal information integration terminal under the different user groups is started, and the electrical parameters and load data under the different user groups of the power system distribution network in each fault area and the equipment status parameters of the fault distance of the power system distribution network in each fault area are collected according to the type of each multimodal information integration terminal in the multimodal information integration terminal group.

[0041] The electrical parameters and load data for different user groups include: current, voltage, impedance, power, frequency, phase and load fluctuation. The equipment status parameters include: transformer parameters, circuit breaker and switch equipment parameters.

[0042] The above data can be collected by the corresponding multimodal information integration terminal. The combination of each multimodal information integration terminal can be collectively referred to as a multimodal information integration terminal group. A multimodal information integration terminal group can be set up on each fault area power system distribution network to collect electrical parameters and load data for different user groups of each fault area power system distribution network, and equipment status parameters of each fault area power system distribution network at the fault distance, thereby realizing the remote danger level determination function of each fault area power system distribution network.

[0043] The electrical parameters, load data and equipment status parameters under the above-mentioned different user groups have different functions. For example, the electrical parameters and load data under different user groups can directly reflect the current state of the power system distribution network in the fault area, and can determine whether the power system distribution network in the fault area has a fault distance danger level judgment. The equipment status parameters of the fault distance of the power system distribution network in the fault area can directly reflect the current fault distance of the power system distribution network in the fault area, such as whether the fault distance of the power system distribution network in the fault area has changed significantly, or whether the fault distance has deteriorated. In this way, it can be expected whether the power system distribution network in the fault area will have a fault distance danger level judgment, so as to deal with it in time.

[0044] The distribution network real-time operation edge computing gateway monitoring platform can store the data collected by the multimodal information integration terminal group and finally send it to the power engineer monitoring terminal.

[0045] In step S300, after receiving the electrical parameters, load data and equipment status parameters of the different user groups, the power engineer monitoring terminal can determine whether the electrical parameters, load data and equipment status parameters of the different user groups are within the preset operating safety limit thresholds.

[0046] If the electrical parameters, load data and equipment status parameters under the different user groups are not within the preset operating safety limit thresholds, that is, the electrical parameters and load data under the different user groups are not within the preset operating safety limit thresholds, and the equipment status parameters are not within the preset operating safety limit thresholds, then it is necessary to generate a distribution network fault distance to be calculated prompt signal and send it to the power system distribution network fault distance calculation model module through the signal collection processing server.

[0047] The power system distribution network fault distance calculation model module can be a power system distribution network fault distance calculation model module for maintenance personnel, so that maintenance personnel can promptly process the fault distance danger level judgment that is occurring or the fault distance danger level judgment that is about to occur in the power system distribution network in the fault area. The power system distribution network fault distance calculation model module can also be a power system distribution network fault distance calculation model module for management personnel, so that management personnel can arrange personnel to handle it according to the area to which the power system distribution network in the fault area belongs.

[0048] The fault distance calculation model module of the power system distribution network combines the convolutional neural network (CNN) and the whale optimization algorithm to use intelligent algorithms to perform efficient and accurate fault distance calculations on fault data. The specific calculation process can be divided into the following steps:

[0049] Data preprocessing and feature extraction,First, after receiving the fault safety self-test signal, the real-time edge computing gateway monitoring platform of the distribution network collects the electrical parameters and load data of each fault area, including key data such as current, voltage, impedance, power, frequency, phase and load fluctuation. In addition, the collected equipment status parameters (such as transformer status, circuit breaker and switchgear status) are also recorded.

[0050] After these data are transmitted to the signal collection processing server, they are converted into a format suitable for input into the convolutional neural network (CNN) through preprocessing steps such as data cleaning, denoising, and normalization.

[0051] The convolutional neural network is responsible for feature extraction of multi-dimensional data. It uses convolutional layers and pooling layers to capture local features and reduce the dimensionality of the input data, extracting high-dimensional features that reflect the fault characteristics. The CNN structure can effectively capture data patterns under different fault types, including voltage fluctuations, current mutations, and phase changes, thereby providing accurate input features for subsequent calculations of fault distance.

[0052] Convolutional Neural Network (CNN) fault identification and preliminary distance calculation,In the fault identification and location stage, the convolutional neural network automatically learns the mapping relationship between fault signals and fault distances by training and analyzing feature data. Through multiple forward and back propagation, the network can optimize weight parameters and improve the accuracy of fault distance prediction.

[0053] For multimodal data from different user groups, CNN can identify the type of fault (such as short circuit, grounding) and the temporal and spatial characteristics of the fault signal, and output preliminary fault distance prediction results. The results of this stage serve as basic predictions and provide input for subsequent optimization steps.

[0054] The fault distance result optimization of the whale optimization algorithm. In order to further improve the accuracy of the fault distance calculation, the fault distance calculation module introduces the whale optimization algorithm to optimize the preliminary prediction results of the convolutional neural network. The whale algorithm is an intelligent optimization algorithm based on the predation behavior of whale groups, which has the advantages of strong global search ability and fast convergence speed.

[0055] Specifically, the whale algorithm optimizes the fault distance results through the following steps:

[0056] Initialize the population: Use the fault distance results output by the convolutional neural network as the initial solution and randomly generate a whale population (optimize candidate solutions).

[0057] Fitness function: Set the error minimization objective of the fault distance as the fitness function to evaluate the quality of each candidate solution.

[0058] Search and update: The whale algorithm simulates the whale's hunting process. It continuously updates candidate solutions and approaches the optimal solution through three mechanisms: surrounding prey, spiral update, and random search.

[0059] Global optimal solution output: After multiple iterations, the whale algorithm converges to the global optimal solution, which is the most accurate fault distance calculation result.

[0060] Output of fault distance results and control decisions. Finally, the fault distance results optimized by convolutional neural network and whale algorithm are sent to the monitoring end of power engineers. The monitoring end makes a judgment based on the fault distance and danger level judgment model and generates corresponding fault response signals, such as power failure or power transmission start signals. The distribution control room takes emergency control measures according to the instructions, isolates the fault area, and ensures the stable operation of the power system.

[0061] The model combines convolutional neural networks with the whale optimization algorithm, making full use of the strong feature extraction capabilities of CNN and the global optimization capabilities of the whale optimization algorithm to achieve accurate calculation of the fault distance of the power system distribution network. Through the synergy of the cloud platform and the big data analysis platform, the system can quickly process fault data and accurately locate and control the fault area, improving the safety and reliability of the power system.

[0062] In order to better analyze the fault distance hazard level determination of the power system distribution network in the fault area, the embodiment of the present invention preferably simultaneously collects the electrical parameters and load data of different user groups of the power system distribution network in the fault area and the equipment status parameters of the fault distance of the power system distribution network in the fault area, and analyzes the fault distance hazard level determination based on these two types of information. When the electrical parameters, load data and equipment status parameters of the different user groups are within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is not generated. When any of the electrical parameters, load data and equipment status parameters of the different user groups is not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated. In this way, it can ensure that the fault distance hazard level determination is discovered in a timely manner and the fault distance hazard level determination is processed.

[0063] In one embodiment, the method for calculating the fault distance of the power system distribution network further includes:

[0064] A fault distance danger level determination model analysis library is pre-set in the power engineer monitoring terminal, and the electrical parameters and load data of the different user groups, the operation safety limit threshold of the equipment status parameters, and the fault distance danger level information are stored in the fault distance danger level determination model library.

[0065] In this embodiment, the operating safety limit thresholds of electrical parameters and load data and equipment status parameters under different user groups can be stored in advance in the fault distance hazard level determination model analysis library, so that the power engineer monitoring end can retrieve the corresponding operating safety limit threshold at any time and make a determination when performing fault distance hazard level determination analysis. At the same time, the information on the fault distance hazard level can also be stored in the fault distance hazard level determination model analysis library, so that the type of fault distance hazard level determination can be determined, which is convenient for maintenance personnel to perform fault distance hazard level determination processing.

[0066] In one embodiment, if the electrical parameters, load data and equipment status parameters of the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server, including:

[0067] The power engineer monitoring terminal determines the fault distance danger level in the fault distance danger level determination model analysis library with the received electrical parameters and load data of different user groups and equipment status parameters;

[0068] The power engineer monitoring terminal sends a corresponding distribution network fault distance to be calculated prompt signal to the signal collection processing server according to the determination result.

[0069] After determining that the electrical parameters, load data, and equipment status parameters of different user groups are not within the preset operating safety limit threshold, the electrical parameters, load data, and equipment status parameters of different user groups can be used to determine the fault distance danger level in the fault distance danger level determination model analysis library, such as determining whether it belongs to the voltage fault distance danger level determination, the current fault distance danger level determination, or other fault distance danger level determination. Then, the distribution network fault distance to be calculated prompt signal is sent to the signal collection processing server, and then sent to the power system distribution network fault distance calculation model module through the signal collection processing server. In this way, not only can the information of the fault distance danger level determination that has occurred or is about to occur in the power system distribution network in the fault area be obtained, but also the information of the fault distance danger level determination that has occurred in the power system distribution network in the fault area can be obtained, so as to facilitate targeted processing.

[0070] In one embodiment, the signal set processing server sends the signal to the power system distribution network fault distance calculation model module, including:

[0071] The signal collection processing server sends the distribution network fault distance to be calculated prompt signal to the power system distribution network fault distance calculation model module through the cloud platform and the big data analysis platform.

[0072] In one embodiment, if the electrical parameters, load data and equipment status parameters of the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server, and also includes:

[0073] The power engineer monitoring terminal sends a power outage or power transmission start signal to the distribution control room according to the determination result to control the power supply of the power distribution network of the power system in the fault area.

[0074] In this embodiment, when it is determined that the electrical parameters and load data and equipment status parameters under the different user groups are not within the preset operational safety limit thresholds and a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module, the maintenance personnel can handle it in time. In the embodiment of the present invention, the power engineer monitoring end can also send a power-off signal or a power transmission start signal to the distribution control room to control the power supply of the power system distribution network in the fault area. For example, when it is detected that the load at the fault distance of the power system distribution network in the fault area is too high, a power-off signal can be sent to the relay in the distribution control room to cut off the power supply, or a power transmission start signal can be sent to the relay in the distribution control room to transmit power to the air conditioner.

[0075] In other embodiments, a neural network model may be used to predict the collected data, thereby obtaining advance information on the distance hazard level of an impending fault, which is helpful in avoiding risks such as burnout of the power distribution network in the fault area.

[0076] Generally speaking, if a certain state of the power distribution network in the fault area continues to change or some parameters in the fault distance continue to deviate from normal values ​​during use, the risk of damage to the power distribution network in the fault area is relatively high. Therefore, the embodiment of the present invention can collect historical fault distance danger level determination data, and the historical fault distance danger level determination data includes the type of fault distance danger level determination and the electrical parameters, load data and equipment status parameters of different user groups before the fault distance danger level determination occurs.

[0077] Then, the above historical fault distance danger level determination data is preprocessed, and the preprocessing content may include normalization, etc., so that each type of data is classified into the same dimension, and then the historical fault distance danger level determination data is divided into a sample set and a test set. Then, a neural network model is used to train the sample set of the historical fault distance danger level determination data, and then the trained neural network model is tested using the test set, and finally the preset accuracy requirement is met.

[0078] See also Figure 2 , an embodiment of the present invention also provides a fault distance calculation system for a power system distribution network, which includes a distribution network comprehensive information processing center, multiple power system distribution network fault distance monitoring points, a signal set processing server and a power system distribution network fault distance calculation model module, the distribution network comprehensive information processing center is provided with a power engineer monitoring terminal, and the multiple power system distribution network fault distance monitoring points are all provided with a distribution network real-time operation edge computing gateway monitoring platform;

[0079] The power engineer monitoring terminal is used to send a fault distance safety self-check signal to the real-time operation edge computing gateway monitoring platform of the distribution network;

[0080] The real-time operation edge computing gateway monitoring platform of the distribution network is used to collect electrical parameters and load data of different user groups of the power system distribution network in each fault area and equipment status parameters of the fault distance of the power system distribution network in each fault area after receiving the fault distance safety self-check signal, and store and send the collected data to the power engineer monitoring terminal;

[0081] The power engineer monitoring end is also used to determine whether the electrical parameters, load data and equipment status parameters of the different user groups are within the preset operation safety limit thresholds; if the electrical parameters, load data and equipment status parameters of the different user groups are not within the preset operation safety limit thresholds, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server.

[0082] In one embodiment, the signal set processing server is used to send the distribution network fault distance to be calculated prompt signal to the power system distribution network fault distance calculation model module through the cloud platform and the big data analysis platform.

[0083] In one embodiment, the power engineer monitoring terminal is used to judge the fault distance hazard level in the fault distance hazard level judgment model analysis library based on the received electrical parameters and load data of different user groups, equipment status parameters and the fault distance hazard level judgment model analysis library; and according to the judgment result, send the corresponding distribution network fault distance to be calculated prompt signal to the signal collection processing server.

[0084] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for calculating fault distance of a power distribution network, characterized in that: include: S100, the power engineer monitoring terminal sends the fault distance safety self-check signal to the real-time operation edge computing gateway monitoring platform of the distribution network; S200, after the real-time operation edge computing gateway monitoring platform of the distribution network receives the fault distance safety self-check signal, the multimodal information integration terminal under different user groups collects the electrical parameters and load data of different user groups of the power system distribution network in each fault area, and the equipment status parameters of the fault distance of the power system distribution network in each fault area, and stores and sends the collected data to the power engineer monitoring terminal; S300, the power engineer monitoring terminal determines whether the electrical parameters, load data, and equipment status parameters of the different user groups are within the preset operation safety limit threshold; if the electrical parameters, load data, and equipment status parameters of the different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server; S400, the power system distribution network fault distance calculation model module, combines convolutional neural network and whale optimization algorithm to calculate fault distance.

2. The method for calculating fault distance of a power distribution network according to claim 1, characterized in that: The electrical parameters and load data for different user groups include: current, voltage, impedance, power, frequency, phase and load fluctuation.

3. The method for calculating fault distance of a power distribution network according to claim 1, characterized in that: The equipment status parameters include: transformer parameters, circuit breaker and switch equipment parameters.

4. The method for calculating fault distance of a power distribution network according to claim 1, characterized in that: Also includes: A fault distance hazard level determination model analysis library is pre-set in the power engineer monitoring terminal, and the electrical parameters and load data under the different user groups, the operation safety limit thresholds of the equipment status parameters, and the information of the fault distance hazard level are stored in the fault distance hazard level determination model analysis library.

5. The method for calculating fault distance of a power distribution network according to claim 4, characterized in that: If the electrical parameters, load data and equipment status parameters of different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server, including: The power engineer monitoring terminal determines the fault distance danger level in the fault distance danger level determination model analysis library with the received electrical parameters and load data of different user groups and equipment status parameters; The power engineer monitoring terminal sends a corresponding distribution network fault distance to be calculated prompt signal to the signal collection processing server according to the determination result.

6. The method for calculating fault distance of a power distribution network according to claim 5, characterized in that: If the electrical parameters, load data and equipment status parameters of different user groups are not within the preset operation safety limit threshold, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server, and also includes: The power engineer monitoring terminal sends a power outage or power transmission start signal to the distribution control room according to the determination result to control the power supply of the power distribution network of the power system in the fault area.

7. The method for calculating fault distance of a power distribution network according to claim 1, characterized in that: The signal collection processing server is sent to the power system distribution network fault distance calculation model module, including: The signal collection processing server sends the distribution network fault distance to be calculated prompt signal to the power system distribution network fault distance calculation model module through the cloud platform and the big data analysis platform.

8. A fault distance calculation system for a power distribution network, characterized in that: It includes a distribution network comprehensive information processing center, multiple power system distribution network fault distance monitoring points, a signal collection processing server and a power system distribution network fault distance calculation model module. The distribution network comprehensive information processing center is provided with a power engineer monitoring terminal, and the multiple power system distribution network fault distance monitoring points are all provided with a distribution network real-time operation edge computing gateway monitoring platform; The power engineer monitoring terminal is used to send a fault distance safety self-check signal to the real-time operation edge computing gateway monitoring platform of the distribution network; The real-time operation edge computing gateway monitoring platform of the distribution network is used to collect electrical parameters and load data of different user groups of the power system distribution network in each fault area and equipment status parameters of the fault distance of the power system distribution network in each fault area after receiving the fault distance safety self-check signal, and store and send the collected data to the power engineer monitoring terminal; The power engineer monitoring end is also used to determine whether the electrical parameters, load data and equipment status parameters of the different user groups are within the preset operation safety limit thresholds; if the electrical parameters, load data and equipment status parameters of the different user groups are not within the preset operation safety limit thresholds, a distribution network fault distance to be calculated prompt signal is generated and sent to the power system distribution network fault distance calculation model module through the signal collection processing server.

9. The fault distance calculation system for the power distribution network of claim 8, characterized in that: The signal collection processing server is used to send the distribution network fault distance to be calculated prompt signal to the power system distribution network fault distance calculation model module through the cloud platform and the big data analysis platform.

10. The fault distance calculation system for the power distribution network of claim 8, characterized in that: The power engineer monitoring terminal is used to determine the fault distance danger level in the fault distance danger level determination model analysis library based on the received electrical parameters and load data of different user groups and equipment status parameters; And according to the determination result, a corresponding distribution network fault distance to be calculated prompt signal is sent to the signal collection processing server.

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