A power distribution network fault real-time research and analysis system based on a figure polymorphism

Abstract

The application discloses a power distribution network fault real-time research and analysis system based on one picture multiple states, and particularly relates to the technical field of power grid fault analysis, and comprises a power distribution network operation time division module, a power distribution network monitoring data acquisition module, a power distribution network load prediction module, a power distribution network equipment working condition control module, a power distribution network fault prediction module, a power distribution network fault research and judgment module, a power distribution network power distribution intelligent monitoring module and a one picture multiple states comprehensive display interaction module. The power distribution network load prediction index and the power distribution network equipment working condition control index of each line of each monitoring sub-period of the operation time of a target power distribution network service command platform are calculated, the power distribution network fault trend early warning coefficient is further analyzed, power grid faults can be early warned, the reliability of power supply can be improved, and the fault repair efficiency can be improved. Through the power distribution network load operation early warning index and the power distribution network equipment working condition control effect evaluation index, the intelligent and refined management of the power distribution network is realized, and the overall operation benefit of the power grid is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid fault analysis, more particularly, the present application relates to a power distribution network fault real-time research and analysis system based on a graph polymorphism. BACKGROUND

[0002] With the rapid development of power systems and the continuous progress of smart grid technology, as an important part of the power system, the data collection, transmission and processing capacity of the power system has been significantly improved, and the reliability and stability of its operation have a decisive influence on the performance of the entire power system.

[0003] The modern power system has higher and higher requirements for the intelligence and automation level of power distribution network fault research and decision-making, and through the sensors and intelligent terminals installed in the key nodes of the power distribution network, real-time monitoring and analysis of power grid data are realized, which is of great significance for timely and accurate research and judgment of power distribution network faults.

[0004] However, in actual use, there are still some shortcomings, such as the existing power distribution network fault research and analysis method relies on manual experience judgment, and the intelligence and automation level is insufficient, resulting in long response time and low accuracy of fault research and judgment.

[0005] The existing power distribution network fault monitoring technology cannot fully integrate the real-time load operation condition of the power grid, the working condition of the power distribution network equipment and other key parameters to realize comprehensive analysis and statistics of the health condition of the power grid, which limits the dynamic display capability of the potential fault problem of the power grid line, and cannot provide real-time and accurate fault warning and positioning. SUMMARY

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a power distribution network fault real-time research and analysis system based on a graph polymorphism, which is used to solve the problems proposed in the background art.

[0007] In order to achieve the above-mentioned purpose, the present application provides the following technical scheme: a power distribution network fault real-time research and analysis system based on a graph polymorphism, comprising:

[0008] The power distribution network operation time division module is used for dividing the operation time of the target power distribution network service command platform into each monitoring sub-period according to the equal time division method, and numbering each monitoring sub-period of the operation time of the target power distribution network service command platform.

[0009] The power distribution network monitoring data acquisition module is used for acquiring the power distribution network data of each line in each monitoring sub-period through the power distribution network service command platform, and the power distribution network monitoring data acquisition module comprises a power distribution network load operation data acquisition unit and a power distribution network equipment working condition data acquisition unit.

[0010] The power distribution network load prediction module is configured to calculate the power distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform according to the power distribution network load operation data collected by the power distribution network load operation data collection unit.

[0011] The power distribution network equipment working condition management and control module is configured to calculate the power distribution network equipment working condition management and control index of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform according to the power distribution network equipment working condition data collected by the power distribution network equipment working condition data collection unit.

[0012] The power distribution network fault prediction module is configured to calculate the power distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform according to the power distribution network fault prediction model.

[0013] The power distribution network fault research and judgment module is configured to obtain the power distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, compare it with the preset power distribution network fault trend early warning coefficient, and process it.

[0014] The power distribution network intelligent monitoring module is configured to obtain the power distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, calculate the power distribution network load operation early warning index of each line of the target power distribution network service command platform, and early warn the power distribution network load abnormal line, obtain the power distribution network equipment working condition management and control index of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, calculate the power distribution network equipment working condition management and control effect evaluation index of each line of the target power distribution network service command platform, and manage the power distribution network equipment working condition of each line.

[0015] The one-map-multiple-state comprehensive display interaction module is configured to arrange the power distribution network load prediction index, the power distribution network equipment working condition management and control index, and the power distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform in the order of monitoring time, visually display the power distribution network of each line in combination with the map, and dynamically display the screened abnormal line.

[0016] Preferably, the power distribution network operation time division module specifically comprises:

[0017] The power distribution network operation time of the target power distribution network service command platform is obtained, the power distribution network operation time of the target power distribution network service command platform is divided into monitoring sub-periods by an equal time division method, and the monitoring sub-periods of the power distribution network operation time of the target power distribution network service command platform are sequentially numbered as 1, 2, …, i, …, n.

[0018] Preferably, the power distribution network monitoring data collection module specifically comprises:

[0019] The power distribution network load operation data acquisition unit: through the power distribution network service command platform, the outage duration, the total number of power supply households, the outage involved households, and the load of each line in each monitoring sub-period are collected, respectively marked as wherein i = 1, 2, …, n, i represents the number of the i-th monitoring sub-period, q = 1, 2, …, m, q represents the number of the q-th line;

[0020] The power distribution network equipment working condition data acquisition unit: through the power distribution network service command platform, the outage times, the cable length, the power supply area, the active power, and the apparent power of each line in each monitoring sub-period are collected, respectively marked as

[0021] Preferably, the power distribution network load prediction module specifically comprises:

[0022] Step S41: the maximum load and the minimum load of each line in each monitoring sub-period are extracted, and the load fluctuation amplitude of each monitoring sub-period is calculated:

[0023]

[0024] wherein bhf i represents the load fluctuation amplitude of the i-th monitoring sub-period, represents the maximum load of the i-th monitoring sub-period, represents the minimum load of the i-th monitoring sub-period, represents the load of the q-th line in the i-th monitoring sub-period, and m represents the number of lines;

[0025] Step S42: the calculation formula of the power distribution network load prediction index is:

[0026]

[0027] wherein represents the power distribution network load prediction index of the q-th line in the i-th monitoring sub-period, bhf i represents the load fluctuation amplitude of the i-th monitoring sub-period, BHF 预 represents the preset load fluctuation amplitude, represents the outage duration of the q-th line in the i-th monitoring sub-period, represents the total number of power supply households of the q-th line in the i-th monitoring sub-period, represents the outage involved households of the q-th line in the i-th monitoring sub-period, Δht q represents the mean value of the outage duration of the q-th line.

[0028] Preferably, the power distribution network equipment working condition management and control module specifically comprises:

[0029] Step S51: calculating the power utilization efficiency of each line in each monitoring sub-period by the active power and the apparent power of each line in each monitoring sub-period:

[0030]

[0031] wherein, represents the power utilization efficiency of the qth line in the ith monitoring sub-period, represents the active power of the qth line in the ith monitoring sub-period, represents the apparent power of the qth line in the ith monitoring sub-period.

[0032] Step S52: calculating the power supply coverage area safety degree of each line in each monitoring sub-period by the outage frequency, the cable length and the power supply area of each line in each monitoring sub-period:

[0033]

[0034] wherein, represents the power supply coverage area safety degree of the qth line in the ith monitoring sub-period, represents the outage frequency of the qth line in the ith monitoring sub-period, represents the cable length of the qth line in the ith monitoring sub-period, represents the power supply area of the qth line in the ith monitoring sub-period.

[0035] Step S53: the calculation formula of the power distribution network equipment working condition management and control index is:

[0036]

[0037] wherein, β i q represents the power distribution network equipment working condition management and control index of the qth line in the ith monitoring sub-period, represents the power utilization efficiency of the qth line in the ith monitoring sub-period, represents the power supply coverage area safety degree of the qth line in the ith monitoring sub-period, represents the power supply coverage area safety degree of the qth line in the (i-1)th monitoring sub-period, λ1 and λ2 represent the influence factors of the power utilization efficiency and the power supply coverage area safety degree, respectively.

[0038] Preferably, the power distribution network fault prediction model is specifically:

[0039]

[0040] wherein, represents the power distribution network fault trend early warning coefficient of the qth line in the ith monitoring sub-period, a power grid load prediction index of the i-th monitoring sub-period and the q-th line, a power grid equipment working condition control index of the i-th monitoring sub-period and the q-th line.

[0041] Preferably, the power grid fault judgment module specifically comprises:

[0042] The power grid fault trend early warning coefficient of each line in each monitoring sub-period of the operation time of the target power grid service command platform is obtained, and is compared with the preset power grid fault trend early warning coefficient. If the power grid fault trend early warning coefficient of a certain line in a certain monitoring sub-period of the operation time of the target power grid service command platform is greater than the preset power grid fault trend early warning coefficient, it indicates that the greater the power grid load prediction index of the line in the monitoring sub-period, the greater the power grid equipment working condition control index, and the more unstable the operation of the power grid, and there is a risk of failure. All line numbers of the monitoring sub-period that exist a risk of failure should be screened out through the power grid service command platform and sent to the corresponding management personnel for failure processing. Otherwise, it indicates that the smaller the power grid load prediction index of the line in the monitoring sub-period, the smaller the power grid equipment working condition control index, and the more stable the operation of the power grid, and the power grid has no abnormal risk.

[0043] Preferably, the calculation formula of the power grid load operation early warning index is:

[0044]

[0045] wherein ω q a power grid load operation early warning index of the q-th line, a power grid load prediction index of the i-th monitoring sub-period and the q-th line, α 预 a preset power grid load prediction index, and n represents the number of monitoring sub-periods;

[0046] The power grid load operation early warning index of each line of the operation time of the target power grid service command platform is obtained, and is compared with the preset power grid load operation early warning index. If the power grid load operation early warning index of a certain line is greater than the preset power grid load operation early warning index, it indicates that the grid load fluctuation range of the line exceeds the expectation, and the line number of the line with load abnormality should be screened out through the power grid service command platform and power grid load abnormality early warning is performed. Otherwise, it indicates that the grid load fluctuation range of the line meets the expectation.

[0047] Preferably, the calculation formula of the power grid equipment working condition control effect evaluation index is:

[0048]

[0049] wherein ψq a power distribution network equipment working condition management and control effect evaluation index of the qth line, a power distribution network equipment working condition management and control index of the qth line in the ith monitoring sub-period, β 预 a preset power distribution network equipment working condition management and control index;

[0050] The power distribution network equipment working condition management and control effect evaluation index of each line of the target power distribution network service command platform at the running time is obtained, and is compared with the preset power distribution network equipment working condition management and control effect evaluation index. When the power supply coverage area safety degree of a line is greater, the power utilization efficiency is smaller, and the management and control degree of the power distribution network equipment manager is heavier, the power distribution network equipment working condition management and control effect evaluation index of the line is greater than the preset power distribution network equipment working condition management and control effect evaluation index. When the power supply coverage area safety degree of a line is smaller, the power utilization efficiency is greater, and the management and control degree of the power distribution network equipment manager is lighter, the power distribution network equipment working condition management and control effect evaluation index of the line is smaller than the preset power distribution network equipment working condition management and control effect evaluation index.

[0051] Technical effects and advantages of the present application:

[0052] 1. The present application provides a power distribution network fault real-time research and analysis system based on one graph multiple states. The power distribution network data of each line in each monitoring sub-period is collected through the power distribution network service command platform. The power distribution network service command platform provides unified data storage and access and exchange mode through information interaction, which provides reliable data support for power distribution network fault research. According to the power distribution network load operation data of the power distribution network load operation data acquisition unit, the power distribution network load prediction index of each line of the target power distribution network service command platform in each monitoring sub-period at the running time is calculated. According to the power distribution network equipment working condition data of the power distribution network equipment working condition data acquisition unit, the power distribution network equipment working condition management and control index of each line of the target power distribution network service command platform in each monitoring sub-period at the running time is calculated. Through comprehensive analysis of historical load data and current power distribution network operation data, it is beneficial to provide decision support for the management department, to early warn power grid faults, to improve the reliability of power supply, and to further calculate the power distribution network fault trend early warning coefficient of each line of the target power distribution network service command platform in each monitoring sub-period at the running time according to the power distribution network fault prediction model. The preset power distribution network fault trend early warning coefficient is compared, and the fault is quickly analyzed and positioned according to the fault research logic. It is beneficial to shorten the power grid fault repair time and improve the power grid fault repair efficiency. Through the one graph multiple states comprehensive display interaction module, the power grid lines are combined with the map to realize regional visual display, and the abnormal lines are dynamically displayed, realizing the display effect of “one graph multiple states”, so that the repair personnel can intuitively understand the running state and fault condition of the power distribution network.

[0053] 2, The application provides a power distribution network fault real-time research and analysis system based on a figure polymorphism, which utilizes a power distribution network intelligent monitoring module, calculates power distribution network load operation early warning indexes of each line of the target power distribution network service command platform in the operation time of each monitoring sub-period through power distribution network load prediction indexes of each line of the target power distribution network service command platform in the operation time of each monitoring sub-period, early warns power distribution network abnormal lines, calculates power distribution network equipment working condition management and control effect evaluation indexes of each line of the target power distribution network service command platform in the operation time through power distribution network equipment working condition management and control indexes of each line of the target power distribution network service command platform in the operation time of each monitoring sub-period, and manages power distribution network equipment working conditions of each line, so as to realize an intelligent monitoring system of each line in the power distribution network service command platform, improve the management efficiency of the power distribution network, facilitate the intelligent and refined management of the power distribution network, and improve the overall operation benefit of the power grid. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 It is a structural schematic diagram of the power distribution network fault real-time research and analysis system based on a figure polymorphism.

[0055] Figure 2 It is a structural schematic diagram of the power distribution network monitoring data acquisition module. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0057] Please refer to Figure 1 The application provides a power distribution network fault real-time research and analysis system based on a figure polymorphism, which includes a power distribution network operation time division module, a power distribution network monitoring data acquisition module, a power distribution network load prediction module, a power distribution network equipment working condition management and control module, a power distribution network fault prediction module, a power distribution network fault research and judgment module, a power distribution network intelligent monitoring module, and a figure polymorphism comprehensive display and interaction module.

[0058] The power distribution network operation time division module is connected with the power distribution network monitoring data acquisition module, the power distribution network monitoring data acquisition module is connected with the power distribution network load prediction module and the power distribution network equipment working condition management and control module, the power distribution network load prediction module and the power distribution network equipment working condition management and control module are connected with the power distribution network fault prediction module and the power distribution network intelligent monitoring module, the power distribution network fault prediction module is connected with the power distribution network fault research and judgment module, and the power distribution network fault research and judgment module and the power distribution network intelligent monitoring module are connected with the figure polymorphism comprehensive display and interaction module.

[0059] The power distribution network operation time division module is used for dividing the operation time of the target power distribution network service command platform into each monitoring sub-period according to an equal time division manner, and numbering each monitoring sub-period of the operation time of the target power distribution network service command platform, so as to realize fine management of the power distribution network operation time, and to monitor and statistically analyze the power distribution network operation condition in the time dimension, which is beneficial to optimizing the operation and maintenance process.

[0060] In a possible design, the power distribution network operation time division module specifically includes:

[0061] The operation time of the target power distribution network service command platform is acquired, and the operation time of the target power distribution network service command platform is divided into each monitoring sub-period according to an equal time division manner, and each monitoring sub-period of the operation time of the target power distribution network service command platform is numbered in sequence as 1, 2, …, i, …, n.

[0062] Please refer to Figure 2 The power distribution network monitoring data acquisition module is used for acquiring the power distribution network data of each line in each monitoring sub-period through the power distribution network service command platform, and includes a power distribution network load operation data acquisition unit and a power distribution network equipment working condition data acquisition unit. The power distribution network data includes power distribution network load operation data and power distribution network equipment working condition data. Through information interaction of the power distribution network service command platform, a unified data storage and access and exchange mode are provided, and reliable data support is provided for power distribution network fault research and judgment.

[0063] In a possible design, the power distribution network monitoring data acquisition module specifically includes:

[0064] The power distribution network load operation data acquisition unit is used for acquiring the outage duration, the total number of power supply households, the number of outage involved households, and the load of each line in each monitoring sub-period through the power distribution network service command platform, and is marked as Wherein, i=1, 2, …, n, i represents the number of the i th monitoring sub-period, and q=1, 2, …, m, q represents the number of the q th line.

[0065] The power distribution network equipment working condition data acquisition unit is used for acquiring the outage frequency, the cable length, the power supply area, the active power, and the apparent power of each line in each monitoring sub-period through the power distribution network service command platform, and is marked as

[0066] The power distribution network load prediction module is used for calculating the power distribution network load prediction index of each line of each monitoring sub-period of the target power distribution network service command platform according to the power distribution network load operation data of the power distribution network load operation data acquisition unit, and is beneficial to providing decision support for the management department, early warning of power grid faults and improvement of power supply reliability through comprehensive analysis of historical load data and current power distribution network operation data.

[0067] In a possible design, the power distribution network load prediction module specifically comprises:

[0068] Step S41: the load fluctuation amplitude of each monitoring sub-period is calculated by extracting the maximum load and the minimum load of each line of each monitoring sub-period.

[0069]

[0070] Wherein, bhf i represents the load fluctuation amplitude of the i th monitoring sub-period, represents the maximum load of the i th monitoring sub-period, represents the minimum load of the i th monitoring sub-period, represents the load of the q th line of the i th monitoring sub-period, and m represents the number of lines;

[0071] Step S42: the calculation formula of the power distribution network load prediction index is as follows:

[0072]

[0073] Wherein, represents the power distribution network load prediction index of the q th line of the i th monitoring sub-period, bhf i represents the load fluctuation amplitude of the i th monitoring sub-period, BHF 预 represents the preset load fluctuation amplitude, represents the outage duration of the q th line of the i th monitoring sub-period, represents the total number of households supplied with power of the q th line of the i th monitoring sub-period, represents the number of households involved in the outage of the q th line of the i th monitoring sub-period, and Δht q represents the mean value of the outage duration of the q th line;

[0074] Wherein, n represents the number of monitoring sub-periods.

[0075] The power distribution network equipment working condition management and control module is configured to calculate power distribution network equipment working condition management and control indexes of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform according to the power distribution network equipment working condition data of the power distribution network equipment working condition data acquisition unit, and visualize abnormal change trends in the power distribution network equipment based on data mining and prediction models, which is conducive to early warning of power grid faults and improvement of power supply reliability.

[0076] In a possible design, the power distribution network equipment working condition management and control module specifically includes:

[0077] Step S51: Calculate the power utilization efficiency of each line in each monitoring sub-period based on the active power and the apparent power of each line in each monitoring sub-period.

[0078]

[0079] wherein, denotes the power utilization efficiency of the qth line in the ith monitoring sub-period, denotes the active power of the qth line in the ith monitoring sub-period, denotes the apparent power of the qth line in the ith monitoring sub-period.

[0080] Step S52: Calculate the power supply coverage area safety degree of each line in each monitoring sub-period based on the outage frequency, the cable length, and the power supply area of each line in each monitoring sub-period.

[0081]

[0082] wherein, denotes the power supply coverage area safety degree of the qth line in the ith monitoring sub-period, denotes the outage frequency of the qth line in the ith monitoring sub-period, denotes the cable length of the qth line in the ith monitoring sub-period, denotes the power supply area of the qth line in the ith monitoring sub-period.

[0083] Step S53: The calculation formula of the power distribution network equipment working condition management and control index is as follows:

[0084]

[0085] wherein, β i q denotes the power distribution network equipment working condition management and control index of the qth line in the ith monitoring sub-period, ygp i q denotes the power utilization efficiency of the qth line in the ith monitoring sub-period, denotes the power supply coverage area safety degree of the qth line in the ith monitoring sub-period, represents the power supply coverage area safety degree of the qth line in the i-1th monitoring sub-period, and λ1 and λ2 represent the influence factors of the power utilization efficiency and the power supply coverage area safety degree respectively.

[0086] The power distribution network fault prediction module is configured to calculate, according to the power distribution network fault prediction model, the power distribution network fault trend early warning coefficients of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, and perform comprehensive analysis on the obtained parameters to obtain clearer data results, so as to analyze and predict the fault trend of the power distribution network.

[0087] In a possible design, the power distribution network fault prediction model is specifically as follows:

[0088]

[0089] wherein, represents the power distribution network fault trend early warning coefficient of the qth line in the i th monitoring sub-period, represents the power distribution network load prediction index of the qth line in the i th monitoring sub-period, represents the power distribution network equipment working condition control index of the qth line in the i th monitoring sub-period.

[0090] The power distribution network fault research and judgment module is configured to obtain the power distribution network fault trend early warning coefficients of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, compare the obtained power distribution network fault trend early warning coefficients with preset power distribution network fault trend early warning coefficients, and process the obtained power distribution network fault trend early warning coefficients according to fault research and judgment logic to perform rapid fault analysis and positioning, so as to shorten the power grid fault repair time and improve the power grid fault repair efficiency.

[0091] In a possible design, the power distribution network fault research and judgment module is specifically as follows:

[0092] The power distribution network fault research and judgment module is configured to obtain the power distribution network fault trend early warning coefficients of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, compare the obtained power distribution network fault trend early warning coefficients with preset power distribution network fault trend early warning coefficients, and process the obtained power distribution network fault trend early warning coefficients according to fault research and judgment logic to perform rapid fault analysis and positioning, so as to shorten the power grid fault repair time and improve the power grid fault repair efficiency.

[0093] The power distribution network power distribution intelligent monitoring module is used for obtaining power distribution network load prediction indexes of each line in each monitoring sub-period of the running time of the target power distribution network service command platform, calculating power distribution network load operation early warning indexes of each line in the running time of the target power distribution network service command platform, early warning of power distribution network load abnormal lines, obtaining power distribution network equipment working condition control indexes of each line in each monitoring sub-period of the running time of the target power distribution network service command platform, calculating power distribution network equipment working condition control effect evaluation indexes of each line in the running time of the target power distribution network service command platform, and managing the power distribution network equipment working conditions of each line, so as to realize an intelligent monitoring system for each line in the power distribution network service command platform, improve the management efficiency of the power distribution network, facilitate intelligent and refined management of the power distribution network, and improve the overall operation benefit of the power grid.

[0094] In a possible design, a calculation formula of the power distribution network load operation early warning index is as follows:

[0095]

[0096] wherein ω q represents the power distribution network load operation early warning index of the qth line, represents the power distribution network load prediction index of the qth line in the ith monitoring sub-period, and a 预 represents a preset power distribution network load prediction index, and n represents the number of monitoring sub-periods.

[0097] The power distribution network load operation early warning index of each line in the running time of the target power distribution network service command platform is obtained, and is compared with a preset power distribution network load operation early warning index. If the power distribution network load operation early warning index of a line is greater than the preset power distribution network load operation early warning index, it indicates that the grid load fluctuation range of the line exceeds the expectation, the line number of the line with load abnormality should be screened out through the power distribution network service command platform, and power distribution network load abnormality early warning is performed, otherwise, it indicates that the grid load fluctuation range of the line meets the expectation.

[0098] In a possible design, a calculation formula of the power distribution network equipment working condition control effect evaluation index is as follows:

[0099]

[0100] wherein ψ q represents the power distribution network equipment working condition control effect evaluation index of the qth line, represents the power distribution network equipment working condition control index of the qth line in the ith monitoring sub-period, and β 预 represents a preset power distribution network equipment working condition control index.

[0101] The operation time line of the target power distribution network service command platform is acquired. The power distribution network equipment working condition management and control effect evaluation index of each line is compared with a preset power distribution network equipment working condition management and control effect evaluation index. When the power supply coverage area safety degree of a line is greater, the power utilization efficiency is smaller, and the power distribution network equipment management personnel control degree is heavier, the power distribution network equipment working condition management and control effect evaluation index of the line is greater than the preset power distribution network equipment working condition management and control effect evaluation index. When the power supply coverage area safety degree of a line is smaller, the power utilization efficiency is greater, and the power distribution network equipment management personnel control degree is lighter, the power distribution network equipment working condition management and control effect evaluation index of the line is smaller than the preset power distribution network equipment working condition management and control effect evaluation index.

[0102] The one-map-multiple-state comprehensive display interaction module is used for sequentially displaying the power distribution network load prediction index, the power distribution network equipment working condition management and control index, and the power distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the target power distribution network service command platform with the monitoring time as the sequence, visually displaying the power grid lines in combination with a map, dynamically displaying the screened abnormal lines, and realizing the one-map-multiple-state display effect, so that the repair personnel can intuitively understand the operation state and fault condition of the power distribution network.

[0103] In the embodiment, it needs to be particularly pointed out that the power distribution network service command platform is used for collecting the power distribution network data of each line in each monitoring sub-period, the information interaction of the power distribution network service command platform is used for providing a unified data storage and access and exchange mode, and reliable data support is provided for power distribution network fault research and judgment. According to the power distribution network load operation data of the power distribution network load operation data acquisition unit, the power distribution network load prediction index of each line in each monitoring sub-period of the target power distribution network service command platform is calculated. According to the power distribution network equipment working condition data of the power distribution network equipment working condition data acquisition unit, the power distribution network equipment working condition management and control index of each line in each monitoring sub-period of the target power distribution network service command platform is calculated. Through comprehensive analysis of historical load data and current power distribution network operation data, decision support is provided for the management department, power grid fault warning is facilitated, the reliability of power supply is improved, and the power distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the target power distribution network service command platform is calculated according to the power distribution network fault prediction model. The power distribution network fault trend early warning coefficient is compared with a preset power distribution network fault trend early warning coefficient. According to the fault research and judgment logic, the fault is quickly analyzed and positioned, the power grid fault repair time is shortened, the power grid fault repair efficiency is improved, the one-map-multiple-state display effect is realized through the one-map-multiple-state comprehensive display interaction module, the power grid lines are visually displayed in combination with a map, the screened abnormal lines are dynamically displayed, and the repair personnel can intuitively understand the operation state and fault condition of the power distribution network.

[0104] The application utilizes the power distribution network power distribution intelligent monitoring module, obtains the power distribution network load operation early warning index of each line of the target power distribution network service command platform through the power distribution network load prediction index of each line of each monitoring sub-period of the operation time of the target power distribution network service command platform, early warns the power distribution network load abnormal line, obtains the power distribution network equipment working condition management and control effect evaluation index of each line of the target power distribution network service command platform through the power distribution network equipment working condition management and control index of each line of each monitoring sub-period of the operation time of the target power distribution network service command platform, manages the power distribution network equipment working condition of each line, so as to realize the intelligent monitoring system of each line in the power distribution network service command platform, improve the management efficiency of the power distribution network, be conducive to realizing the intelligent and fine management of the power distribution network, and improve the overall operation benefit of the power grid.

[0105] Finally: the above only for the preferred embodiment of the application has, and is not used to limit the application, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application, should be included in the protection scope of the application.

Claims

1. A power distribution network fault real-time research and analysis system based on a figure polymorphism, characterized in that, Comprise: Power distribution network operation time division module: for dividing the operation time of the target power distribution network service command platform into each monitoring sub-period according to the equal time division method, and numbering each monitoring sub-period of the operation time of the target power distribution network service command platform; Power distribution network monitoring data acquisition module: for acquiring power distribution network data of each line in each monitoring sub-period through the power distribution network service command platform, the power distribution network monitoring data acquisition module comprising a power distribution network load operation data acquisition unit and a power distribution network equipment working condition data acquisition unit; Power distribution network load prediction module: for calculating power distribution network load prediction indexes of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform according to power distribution network load operation data of the power distribution network load operation data acquisition unit; Power distribution network equipment working condition control module: for calculating power distribution network equipment working condition control indexes of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform according to power distribution network equipment working condition data of the power distribution network equipment working condition data acquisition unit; The power utilization efficiency of each line in each monitoring sub-period is calculated through the active power and the apparent power of each line in each monitoring sub-period: ； wherein, represents the electrical energy utilization efficiency of the qth line in the ith monitoring sub-period, represents the active power of the qth line in the ith monitoring sub-period, represents the apparent power of the qth line in the ith monitoring sub-period; The power supply coverage area safety degree of each line in each monitoring sub-period is calculated through the outage frequency, the cable length and the power supply area of each line in each monitoring sub-period: ； wherein, represents the power supply coverage area safety degree of the qth line in the ith monitoring sub-period, represents the outage frequency of the qth line in the ith monitoring sub-period, represents the cable length of the qth line in the ith monitoring sub-period, represents the power supply area of the qth line in the ith monitoring sub-period; The calculation formula of the power distribution network equipment working condition control index is: ； wherein, represents the power grid equipment working condition control index of the qth line in the ith monitoring sub-period, represents the power utilization efficiency of the qth line in the ith monitoring sub-period, represents the power supply coverage area safety degree of the qth line in the ith monitoring sub-period, represents the power supply coverage area safety degree of the qth line in the (i-1)th monitoring sub-period, respectively represent the influence factors of the power utilization efficiency and the power supply coverage area safety degree.​ Power distribution network fault prediction module: for calculating power distribution network fault trend early warning coefficients of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform according to a power distribution network fault prediction model; Power distribution network fault research and judgment module: for acquiring power distribution network fault trend early warning coefficients of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, comparing with preset power distribution network fault trend early warning coefficients, and processing; Power distribution network intelligent monitoring module: for acquiring power distribution network load prediction indexes of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, calculating power distribution network load operation early warning indexes of each line of the target power distribution network service command platform, early warning power distribution network load abnormal lines, acquiring power distribution network equipment working condition control indexes of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform, calculating power distribution network equipment working condition control effect evaluation indexes of each line of the target power distribution network service command platform, and managing power distribution network equipment working conditions of each line; One figure multiple state comprehensive display interaction module: for sequentially arranging power distribution network load prediction indexes, power distribution network equipment working condition control indexes and power distribution network fault trend early warning coefficients of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform in monitoring time, visually displaying each line of the power grid in combination with a map in a regional visual manner, and dynamically displaying abnormal lines screened out. 2.The power distribution network fault real-time research and analysis system based on a figure polymorphism of claim 1, characterized in that: The power distribution network operation time division module specifically comprises: The operation time of the target power distribution network service command platform is obtained, the operation time of the target power distribution network service command platform is divided into monitoring sub-periods by an equal time division method, and the operation time of the target power distribution network service command platform is sequentially numbered as 1, 2, …, i, …, n. 3.The power distribution network fault real-time research and analysis system based on a figure polymorphism of claim 1, characterized in that: The power distribution network monitoring data acquisition module specifically comprises: The power distribution network load operation data acquisition unit: through the power distribution network service command platform, the outage duration, the total number of power supply households, the outage involved households and the load of each line in each monitoring sub-period are collected, respectively marked as , , , , wherein i=1, 2, …, n, i represents the number of the i-th monitoring sub-period, q=1, 2, …, m, q represents the number of the q-th line. The power distribution network equipment working condition data collection unit: through the power distribution network service command platform, the outage times, cable length, power supply area, active power and apparent power of each line in each monitoring sub-period are collected and marked as , , , , .

4. The power distribution network fault real-time research and analysis system based on a figure polymorphism of claim 1, characterized in that: The power distribution network load prediction module specifically comprises: Step S41: The maximum load and the minimum load of each line in each monitoring sub-period are extracted, and the load fluctuation amplitude of each monitoring sub-period is calculated. ； wherein, represents the load fluctuation amplitude of the i-th monitoring sub-period, represents the maximum load of the i-th monitoring sub-period, represents the minimum load of the i-th monitoring sub-period, represents the load of the q-th line of the i-th monitoring sub-period, m represents the number of lines; Step S42: The calculation formula of the power distribution network load prediction index is: ； wherein, represents the distribution network load prediction index for the qth line in the ith monitoring sub-period, represents the load fluctuation amplitude in the ith monitoring sub-period, represents the preset load fluctuation amplitude, represents the outage duration for the qth line in the ith monitoring sub-period, represents the total number of households served by the qth line in the ith monitoring sub-period, represents the number of households involved in the outage of the qth line in the ith monitoring sub-period, represents the mean value of the outage duration for the qth line.

5. The real-time analysis system for power distribution network fault based on one picture multiple states according to claim 1, characterized in that: The power distribution network fault prediction model specifically comprises: ； wherein, represents a power distribution network fault trend early warning coefficient of the qth line in the ith monitoring sub-period, represents a power distribution network load prediction index of the qth line in the ith monitoring sub-period, represents a power distribution network equipment working condition control index of the qth line in the ith monitoring sub-period.

6. The real-time research and analysis system for power distribution network fault based on one picture multiple states according to claim 1, characterized in that: The power distribution network fault research and judgment module specifically comprises: The power distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the operation time of the target power distribution network service command platform is obtained, and is compared with a preset power distribution network fault trend early warning coefficient. If the power distribution network fault trend early warning coefficient of a certain line in a certain monitoring sub-period of the operation time of the target power distribution network service command platform is greater than the preset power distribution network fault trend early warning coefficient, it indicates that the greater the power distribution network load prediction index of the line in the monitoring sub-period, the greater the power distribution network equipment working condition control index, and the more unstable the operation of the power distribution network, and there is a risk of failure. The number of all lines with a failure risk in the monitoring sub-period should be screened out through the power distribution network service command platform and sent to the corresponding management personnel for failure processing. Otherwise, it indicates that the smaller the power distribution network load prediction index of the line in the monitoring sub-period, the smaller the power distribution network equipment working condition control index, and the more stable the operation of the power distribution network, and there is no abnormal risk of the power distribution network.

7. The real-time analysis system for power distribution network fault based on one picture multiple states according to claim 1, characterized in that: The calculation formula of the power distribution network load operation early warning index is: ； wherein, a power distribution network load operation early warning index of the qth line, a power distribution network load prediction index of the qth line in the ith monitoring sub-period, a preset power distribution network load prediction index, and n represents the number of monitoring sub-periods. The power distribution network load operation early warning index of each line is obtained, and is compared with a preset power distribution network load operation early warning index. If the power distribution network load operation early warning index of a certain line is greater than the preset power distribution network load operation early warning index, it indicates that the power grid load fluctuation amplitude of the line exceeds the expectation, and the line number of the line with load abnormality should be screened out through the power distribution network service command platform and a power distribution network load abnormality early warning is performed. Otherwise, it indicates that the power grid load fluctuation amplitude of the line meets the expectation. 8.The power distribution network fault real-time research and analysis system based on a figure polymorphism of claim 1, characterized in that: The calculation formula of the power distribution network equipment working condition control effect evaluation index is: ； wherein, an index representing the effect of the power distribution network equipment working condition management and control, an index representing the power distribution network equipment working condition management and control of the qth line in the ith monitoring sub-period, an index representing the preset power distribution network equipment working condition management and control. The power distribution network equipment working condition control effect evaluation index of each line of the target power distribution network service command platform is obtained, and is compared with a preset power distribution network equipment working condition control effect evaluation index. When the power supply coverage area safety degree of a certain line is greater, the power energy utilization efficiency is smaller, and the power distribution network equipment management personnel control degree is heavier, the power distribution network equipment working condition control effect evaluation index of the line is greater than the preset power distribution network equipment working condition control effect evaluation index. When the power supply coverage area safety degree of a certain line is smaller, the power energy utilization efficiency is greater, and the power distribution network equipment management personnel control degree is lighter, the power distribution network equipment working condition control effect evaluation index of the line is smaller than the preset power distribution network equipment working condition control effect evaluation index.

Images