Power distribution network fault real-time research, judgment and analysis system based on one-graph multi-state

Abstract

The invention discloses a power distribution network fault real-time studying, judging and analyzing system based on one graph and multiple states, and particularly relates to the technical field of power grid fault analysis. Comprising 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 power distribution intelligent monitoring module and a one-graph multi-state comprehensive display interaction module. According to the method, the power distribution network load prediction index and 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 are calculated, the power distribution network fault trend early warning coefficient is further analyzed, power grid fault early warning is facilitated, the power supply reliability is improved, and the fault repair efficiency is improved. Through the power distribution network load operation early warning index and the power distribution network equipment working condition management and control effect evaluation index, 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 invention relates to the technical field of power grid fault analysis, and more specifically, to a real-time fault judgment and analysis system for distribution network based on one-graph-multiple-states. Background Art

[0002] With the rapid development of power systems and the continuous advancement of smart grid technology, distribution networks, as an important part of power systems, have significantly improved their data collection, transmission and processing capabilities. The reliability and stability of their operations have a decisive impact on the performance of the entire power system.

[0003] Modern power systems have increasingly higher requirements for the intelligence and automation of distribution network fault analysis and decision-making. By installing sensors and smart terminals at key nodes of the distribution network, real-time monitoring and analysis of power grid data can be achieved, which is of great significance for the timely and accurate analysis of distribution network faults.

[0004] However, there are still some shortcomings in its actual use. For example, the existing distribution network fault judgment and analysis methods rely on manual experience judgment, and the level of intelligence and automation is insufficient, resulting in long response time and low accuracy of fault judgment.

[0005] Existing distribution network fault monitoring technology cannot fully integrate the real-time load operation status of the power grid, the operating conditions of distribution network equipment and other key parameters to achieve a comprehensive analysis and statistics of the health status of the power grid. This limitation leads to insufficient dynamic display capabilities of potential fault problems in power grid lines and is unable to provide real-time and accurate fault warning and positioning. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a real-time fault determination and analysis system for a distribution network based on one graph and multiple states, which is used to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solution: a real-time fault judgment and analysis system for distribution network based on one graph and multiple states, comprising:

[0008] Distribution network operation time division module: used to divide the operation time of the target distribution network service command platform into various monitoring sub-periods according to the equal time division method, and number each monitoring sub-period of the operation time of the target distribution network service command platform.

[0009] Distribution network monitoring data acquisition module: used to collect distribution network data of each line in each monitoring sub-period through the distribution network service command platform. The distribution network monitoring data acquisition module includes a distribution network load operation data acquisition unit and a distribution network equipment operating condition data acquisition unit.

[0010] Distribution network load forecasting module: used to calculate the distribution network load forecasting index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform according to the distribution network load operation data of the distribution network load operation data acquisition unit.

[0011] Distribution network equipment condition control module: used to calculate the distribution network equipment condition control index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform based on the distribution network equipment condition data of the distribution network equipment condition data acquisition unit.

[0012] Distribution network fault prediction module: used to calculate the distribution network fault trend warning coefficient of each line in each monitoring sub-period of the operation time of the target distribution network service command platform according to the distribution network fault prediction model.

[0013] Distribution network fault analysis module: used to obtain the distribution network fault trend warning coefficient of each line in each monitoring sub-period of the operation time of the target distribution network service command platform, compare it with the preset distribution network fault trend warning coefficient, and process it.

[0014] Distribution network intelligent monitoring module: used to obtain the distribution network load prediction index of each line in each monitoring sub-period during the operation time of the target distribution network service command platform, calculate the distribution network load operation warning index of each line during the operation time of the target distribution network service command platform, warn the abnormal load lines of the distribution network, obtain the distribution network equipment condition control index of each line in each monitoring sub-period during the operation time of the target distribution network service command platform, calculate the distribution network equipment condition control effect evaluation index of each line during the operation time of the target distribution network service command platform, and manage the distribution network equipment condition of each line.

[0015] One-picture-multiple-states comprehensive display interactive module: It is used to display the distribution network load forecast index, distribution network equipment condition control index and distribution network fault trend warning coefficient of each line in each monitoring sub-period of the target distribution network service command platform in the order of monitoring time, and combine each line of the power grid with the map for regional visualization and intuitive display, and dynamically display the screened abnormal lines.

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

[0017] The operating time of the target distribution network service command platform is obtained, and the operating time of the target distribution network service command platform is divided into monitoring sub-periods by equal time division, and the monitoring sub-periods of the operating time of the target distribution network service command platform are numbered as 1, 2, ..., i, ..., n in sequence.

[0018] Preferably, the distribution network monitoring data acquisition module is specifically:

[0019] Distribution network load operation data collection unit: The distribution network service command platform collects the outage duration of each line in each monitoring sub-period, the total number of households powered, the number of households involved in the outage, and the load, and marks them as Where 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] Distribution network equipment operating condition data collection unit: The distribution network service command platform collects the outage times, cable length, power supply area, active power, and apparent power of each line in each monitoring sub-period, and marks them as

[0021] Preferably, the distribution network load forecasting module is specifically:

[0022] Step S41: Calculate the load fluctuation amplitude of each monitoring sub-period by extracting the maximum load and minimum load of each line in each monitoring sub-period:

[0023]

[0024] Among them, bhf i It is expressed as the load fluctuation amplitude of the ith monitoring sub-period, is represented as the maximum load of the ith monitoring sub-period, It is expressed as the minimum load of the ith monitoring sub-period, It is represented as the load of the qth line in the ith monitoring sub-period, and m is the number of lines;

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

[0026]

[0027] in, It is expressed as the distribution network load forecast index of the qth line in the ith monitoring sub-period, bhf i It is expressed as the load fluctuation amplitude of the ith monitoring sub-period, BHF 预 Expressed as the preset load fluctuation amplitude, It is expressed as the outage duration of the qth line in the ith monitoring sub-period, It is expressed as the total number of households powered by the qth line in the ith monitoring sub-period, It is expressed as the number of households affected by the outage of the qth line in the ith monitoring sub-period, Δht q It is expressed as the mean outage duration of the qth line.

[0028] Preferably, the distribution network equipment operating condition control module is specifically:

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

[0030]

[0031] in, It is expressed as the power utilization efficiency of the qth line in the i-th monitoring sub-period, It is expressed as the active power of the qth line in the ith monitoring sub-period, Expressed as the apparent power of the qth line in the ith monitoring sub-period;

[0032] Step S52: Calculate the safety of the power supply coverage area of ​​each line in each monitoring sub-period based on the number of outages of each line in each monitoring sub-period, the cable length, and the power supply area:

[0033]

[0034] in, It is expressed as the safety degree of the power supply coverage area of ​​the qth line in the i-th monitoring sub-period, It is expressed as the outage times of the qth line in the ith monitoring sub-period, It is expressed as the cable length of the qth line in the ith monitoring sub-period, It is expressed as the power supply area of ​​the qth line in the ith monitoring sub-period;

[0035] Step S53: The calculation formula of the distribution network equipment condition control index is:

[0036]

[0037] Among them, β i q It is expressed as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period, It is expressed as the power utilization efficiency of the qth line in the i-th monitoring sub-period, It is expressed as the safety degree of the power supply coverage area of ​​the qth line in the i-th monitoring sub-period, It is represented as the safety degree of the power supply coverage area of ​​the qth line in the i-1th monitoring sub-period, and λ1 and λ2 are the influencing factors of the power utilization efficiency and the safety degree of the power supply coverage area, respectively.

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

[0039]

[0040] in, It is expressed as the distribution network fault trend warning coefficient of the qth line in the i-th monitoring sub-period, It is expressed as the distribution network load forecast index of the qth line in the ith monitoring sub-period, It is expressed as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period.

[0041] Preferably, the distribution network fault analysis module is specifically:

[0042] Obtain the distribution network fault trend warning coefficient of each line in each monitoring sub-period during the operation time of the target distribution network service command platform, and compare it with the preset distribution network fault trend warning coefficient. If the distribution network fault trend warning coefficient of a line in a certain monitoring sub-period during the operation time of the target distribution network service command platform is greater than the preset distribution network fault trend warning coefficient, it indicates that the larger the distribution network load prediction index of the line in the monitoring sub-period, the larger the distribution network equipment condition control index, the more unstable the operation of the distribution network, and the existence of failure risks. The distribution network service command platform should be used to screen out the numbers of all lines with failure risks in the monitoring sub-period, and send them to the corresponding management personnel for fault handling. Otherwise, it indicates that the smaller the distribution network load prediction index of the route in the monitoring sub-period, the smaller the distribution network equipment condition control index, the more stable the operation of the distribution network, and there is no abnormal risk in the distribution network.

[0043] Preferably, the calculation formula of the distribution network load operation warning index is:

[0044]

[0045] Among them, ω q It is represented as the load operation warning index of the distribution network of the qth line, It is expressed as the distribution network load forecast index of the qth line in the i-th monitoring sub-period, α 预 It is represented by the preset distribution network load forecast index, and n is represented by the number of monitoring sub-periods;

[0046] Obtain the distribution network load operation warning index of each line during the operation time of the target distribution network service command platform, and compare it with the preset distribution network load operation warning index. If the distribution network load operation warning index of a line is greater than the preset distribution network load operation warning index, it indicates that the grid load fluctuation amplitude of the line exceeds expectations. The distribution network service command platform should be used to screen out the line numbers with abnormal loads, and issue a distribution network load abnormality warning. Otherwise, it indicates that the grid load fluctuation amplitude of the line is in line with expectations.

[0047] Preferably, the calculation formula of the distribution network equipment condition control effect evaluation index is:

[0048]

[0049] Among them, ψq It is expressed as the evaluation index of the operating condition control effect of the distribution network equipment of the qth line, It is expressed as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period, β 预 It is expressed as a preset distribution network equipment condition control index;

[0050] The distribution network equipment condition control effect evaluation index of each line during the operation time of the target distribution network service command platform is obtained, and compared with the preset distribution network equipment condition control effect evaluation index. When the safety degree of the power supply coverage area of ​​a certain line is greater, the electric energy utilization efficiency is lower, and the control degree of the distribution network equipment management personnel is heavier, then the distribution network equipment condition control effect evaluation index of the line is greater than the preset distribution network equipment condition control effect evaluation index; when the safety degree of the power supply coverage area of ​​a certain line is lower, the electric energy utilization efficiency is higher, and the control degree of the distribution network equipment management personnel is lighter, then the distribution network equipment condition control effect evaluation index of the line is less than the preset distribution network equipment condition control effect evaluation index.

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

[0052] 1. The present invention provides a real-time fault judgment and analysis system for distribution network based on one graph and multiple states. The distribution network data of each line in each monitoring sub-period is collected through the distribution network service command platform. Through the information interaction of the distribution network service command platform, a unified data storage, access and exchange method is provided, which provides reliable data support for the fault judgment of the distribution network. According to the distribution network load operation data of the distribution network load operation data collection unit, the distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform is calculated. According to the distribution network equipment condition data of the distribution network equipment condition data collection unit, the distribution network equipment condition control index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform is calculated. By comparing the historical load data and the current distribution network operation data Comprehensive analysis is conducive to providing decision-making support for management departments, early warning of power grid faults, and improving the reliability of power supply. Further, based on the distribution network fault prediction model, the distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the target distribution network service command platform is calculated, and compared with the preset distribution network fault trend early warning coefficient. According to the fault judgment logic, the fault is quickly analyzed and located, which is conducive to shortening the power grid fault repair time and improving the power grid fault repair efficiency. Through the one-picture multi-state comprehensive display interactive module, the power grid lines are combined with the map for regional visualization and intuitive display in the order of monitoring time, and the screened abnormal lines are dynamically displayed, realizing the display effect of "one picture multi-state", so that the repair personnel can intuitively understand the operation status and fault conditions of the distribution network;

[0053] 2. The present invention provides a real-time fault assessment and analysis system for distribution network based on one graph and multiple states. The system utilizes the distribution network intelligent monitoring module to calculate the distribution network load forecast index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform through the distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform, and obtain the distribution network load operation warning index of each line in the operation time of the target distribution network service command platform. The abnormal load lines of the distribution network are warned, and the distribution network equipment condition control effect evaluation index of each line in the operation time of the target distribution network service command platform is calculated through the distribution network equipment condition control index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform. The distribution network equipment condition of each line is managed, thereby realizing the intelligent monitoring system of each line in the distribution network service command platform, improving the management efficiency of the distribution network, and being conducive to realizing the intelligent and refined management of the distribution network and improving the overall operating efficiency of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 The present invention is a structural schematic diagram of a real-time fault judgment and analysis system for distribution network based on one graph and multiple states.

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

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] See also Figure 1 As shown, the present invention provides a real-time fault assessment and analysis system for distribution network based on one graph and multiple states, including a distribution network operation time division module, a distribution network monitoring data acquisition module, a distribution network load forecasting module, a distribution network equipment condition control module, a distribution network fault prediction module, a distribution network fault assessment module, a distribution network power distribution intelligent monitoring module and a one graph and multiple states comprehensive display interaction module.

[0058] The distribution network operation time division module is connected to the distribution network monitoring data acquisition module, the distribution network monitoring data acquisition module is connected to the distribution network load prediction module and the distribution network equipment condition control module, the distribution network load prediction module and the distribution network equipment condition control module are connected to the distribution network fault prediction module and the distribution network power distribution intelligent monitoring module, the distribution network fault prediction module is connected to the distribution network fault analysis module, and the distribution network fault analysis module and the distribution network power distribution intelligent monitoring module are connected to the one-picture-multi-state comprehensive display interaction module.

[0059] The distribution network operation time division module is used to divide the operation time of the target distribution network service command platform into various monitoring sub-periods according to an equal time division method, and number each monitoring sub-period of the operation time of the target distribution network service command platform, thereby realizing the refined management of the distribution network operation time, monitoring and statistically analyzing the distribution network operation status in the dimension of time, and facilitating the optimization of the operation and maintenance process.

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

[0061] The operating time of the target distribution network service command platform is obtained, and the operating time of the target distribution network service command platform is divided into monitoring sub-periods by equal time division, and the monitoring sub-periods of the operating time of the target distribution network service command platform are numbered as 1, 2, ..., i, ..., n in sequence.

[0062] See also Figure 2 As shown, the distribution network monitoring data acquisition module is used to collect the distribution network data of each line in each monitoring sub-period through the distribution network service command platform. The distribution network monitoring data acquisition module includes a distribution network load operation data acquisition unit and a distribution network equipment operating condition data acquisition unit. The distribution network data includes distribution network load operation data and distribution network equipment operating condition data. Through the information interaction of the distribution network service command platform, a unified data storage, access and exchange method is provided, which provides reliable data support for distribution network fault analysis.

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

[0064] Distribution network load operation data collection unit: The distribution network service command platform collects the outage duration of each line in each monitoring sub-period, the total number of households powered, the number of households involved in the outage, and the load, and marks them as Where 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;

[0065] Distribution network equipment operating condition data collection unit: The distribution network service command platform collects the outage times, cable length, power supply area, active power, and apparent power of each line in each monitoring sub-period, and marks them as

[0066] The distribution network load prediction module is used to calculate the distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform according to the distribution network load operation data of the distribution network load operation data acquisition unit. Through the comprehensive analysis of historical load data and current distribution network operation data, it is beneficial to provide decision support for the management department, to warn of power grid failures, and to improve the reliability of power supply.

[0067] In a possible design, the distribution network load forecasting module is specifically:

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

[0069]

[0070] Among them, bhf i It is expressed as the load fluctuation amplitude of the ith monitoring sub-period, is represented as the maximum load of the ith monitoring sub-period, It is expressed as the minimum load of the ith monitoring sub-period, It is represented as the load of the qth line in the ith monitoring sub-period, and m is the number of lines;

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

[0072]

[0073] in, It is expressed as the distribution network load forecast index of the qth line in the ith monitoring sub-period, bhf i It is expressed as the load fluctuation amplitude of the ith monitoring sub-period, BHF 预 Expressed as the preset load fluctuation amplitude, It is expressed as the outage duration of the qth line in the ith monitoring sub-period, It is expressed as the total number of households powered by the qth line in the ith monitoring sub-period, It is expressed as the number of households affected by the outage of the qth line in the ith monitoring sub-period, Δht q It is expressed as the mean of the outage duration of the qth line;

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

[0075] The distribution network equipment operating condition control module is used to calculate the distribution network equipment operating condition control index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform according to the distribution network equipment operating condition data of the distribution network equipment operating condition data acquisition unit, and visualize the abnormal change trend in the distribution network equipment based on data mining and prediction models, which is conducive to early warning of power grid failures and improving the reliability of power supply.

[0076] In a possible design, the distribution network equipment operating condition control module is specifically:

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

[0078]

[0079] in, It is expressed as the power utilization efficiency of the qth line in the i-th monitoring sub-period, It is expressed as the active power of the qth line in the ith monitoring sub-period, Expressed as the apparent power of the qth line in the ith monitoring sub-period;

[0080] Step S52: Calculate the safety of the power supply coverage area of ​​each line in each monitoring sub-period based on the number of outages of each line in each monitoring sub-period, the cable length, and the power supply area:

[0081]

[0082] in, It is expressed as the safety degree of the power supply coverage area of ​​the qth line in the i-th monitoring sub-period, It is expressed as the outage times of the qth line in the ith monitoring sub-period, It is expressed as the cable length of the qth line in the ith monitoring sub-period, It is expressed as the power supply area of ​​the qth line in the ith monitoring sub-period;

[0083] Step S53: The calculation formula of the distribution network equipment condition control index is:

[0084]

[0085] Among them, β i q It is expressed as the distribution network equipment condition control index of the qth line in the ith monitoring sub-period, ygp i q It is expressed as the power utilization efficiency of the qth line in the i-th monitoring sub-period, It is expressed as the safety degree of the power supply coverage area of ​​the qth line in the i-th monitoring sub-period, It is represented as the safety degree of the power supply coverage area of ​​the qth line in the i-1th monitoring sub-period, and λ1 and λ2 are the influencing factors of the power utilization efficiency and the safety degree of the power supply coverage area, respectively.

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

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

[0088]

[0089] in, It is expressed as the distribution network fault trend warning coefficient of the qth line in the i-th monitoring sub-period, It is expressed as the distribution network load forecast index of the qth line in the ith monitoring sub-period, It is expressed as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period.

[0090] The distribution network fault analysis module is used to obtain the distribution network fault trend warning coefficient of each line in each monitoring sub-period of the operation time of the target distribution network service command platform, compare it with the preset distribution network fault trend warning coefficient, and process it, and perform rapid fault analysis and positioning according to the fault analysis logic, which is conducive to shortening the power grid fault repair time and improving the power grid fault repair efficiency.

[0091] In a possible design, the distribution network fault analysis module is specifically:

[0092] Obtain the distribution network fault trend warning coefficient of each line in each monitoring sub-period of the operation time of the target distribution network service command platform, and compare it with the preset distribution network fault trend warning coefficient. If the distribution network fault trend warning coefficient of a line in a certain monitoring sub-period of the operation time of the target distribution network service command platform is greater than the preset distribution network fault trend warning coefficient, it indicates that the larger the distribution network load prediction index of the line in the monitoring sub-period, the larger the distribution network equipment condition control index, the more unstable the operation of the distribution network, and the existence of failure risks. The distribution network service command platform should be used to screen out the numbers of all lines with failure risks in the monitoring sub-period, and send them to the corresponding management personnel for fault handling. Otherwise, it indicates that the smaller the distribution network load prediction index of the route in the monitoring sub-period, the smaller the distribution network equipment condition control index, the more stable the operation of the distribution network, and there is no abnormal risk in the distribution network.

[0093] The distribution network intelligent monitoring module is used to obtain the distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform, calculate the distribution network load operation warning index of each line in the operation time of the target distribution network service command platform, warn the abnormal load lines of the distribution network, obtain the distribution network equipment condition control index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform, calculate the distribution network equipment condition control effect evaluation index of each line in the operation time of the target distribution network service command platform, manage the distribution network equipment condition of each line, thereby realizing the intelligent monitoring system of each line in the distribution network service command platform, improving the management efficiency of the distribution network, and being conducive to realizing the intelligent and refined management of the distribution network and improving the overall operating efficiency of the power grid.

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

[0095]

[0096] Among them, ω q It is represented as the load operation warning index of the distribution network of the qth line, It is expressed as the distribution network load forecast index of the qth line in the i-th monitoring sub-period, α 预 It is represented by the preset distribution network load forecast index, and n is represented by the number of monitoring sub-periods;

[0097] Obtain the distribution network load operation warning index of each line during the operation time of the target distribution network service command platform, and compare it with the preset distribution network load operation warning index. If the distribution network load operation warning index of a line is greater than the preset distribution network load operation warning index, it indicates that the grid load fluctuation amplitude of the line exceeds expectations. The distribution network service command platform should be used to screen out the line numbers with abnormal loads, and issue a distribution network load abnormality warning. Otherwise, it indicates that the grid load fluctuation amplitude of the line is in line with expectations.

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

[0099]

[0100] Among them, ψ q It is expressed as the evaluation index of the operating condition control effect of the distribution network equipment of the qth line, It is expressed as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period, β 预 It is expressed as a preset distribution network equipment condition control index;

[0101] The distribution network equipment condition control effect evaluation index of each line during the operation time of the target distribution network service command platform is obtained, and compared with the preset distribution network equipment condition control effect evaluation index. When the safety degree of the power supply coverage area of ​​a certain line is greater, the electric energy utilization efficiency is lower, and the control degree of the distribution network equipment management personnel is heavier, then the distribution network equipment condition control effect evaluation index of the line is greater than the preset distribution network equipment condition control effect evaluation index; when the safety degree of the power supply coverage area of ​​a certain line is lower, the electric energy utilization efficiency is higher, and the control degree of the distribution network equipment management personnel is lighter, then the distribution network equipment condition control effect evaluation index of the line is less than the preset distribution network equipment condition control effect evaluation index.

[0102] The one-picture-multiple-states comprehensive display interaction module is used to display the distribution network load prediction index, distribution network equipment condition control index and distribution network fault trend warning coefficient of each line in each monitoring sub-period of the operation time of the target distribution network service command platform in the order of monitoring time, and to combine each line of the power grid with a map for an intuitive regional visualization, and to dynamically display the screened abnormal lines, thereby achieving a "one-picture-multiple-states" display effect, so that emergency repair personnel can intuitively understand the operating status and fault conditions of the distribution network.

[0103] In the present embodiment, it is necessary to specifically explain that the present invention collects the distribution network data of each line in each monitoring sub-period through the distribution network service command platform, and provides a unified data storage, access and exchange method through the information interaction of the distribution network service command platform, so as to provide reliable data support for the distribution network fault analysis and judgment. According to the distribution network load operation data of the distribution network load operation data acquisition unit, the distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform is calculated. According to the distribution network equipment condition data of the distribution network equipment condition data acquisition unit, the distribution network equipment condition control index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform is calculated. Through the comprehensive analysis of the historical load data and the current distribution network operation data, there is It is conducive to providing decision-making support for management departments, early warning of power grid faults, and improving the reliability of power supply. Further, according to the distribution network fault prediction model, the distribution network fault trend early warning coefficient of each line in each monitoring sub-period of the operation time of the target distribution network service command platform is calculated, and compared with the preset distribution network fault trend early warning coefficient. According to the fault judgment logic, the fault is quickly analyzed and located, which is conducive to shortening the power grid fault repair time and improving the power grid fault repair efficiency. Through the one-picture multi-state comprehensive display interactive module, the power grid lines are combined with the map for regional visualization and intuitive display in the order of monitoring time, and the screened abnormal lines are dynamically displayed, realizing the display effect of "one picture multi-state", so that the repair personnel can intuitively understand the operation status and fault conditions of the distribution network;

[0104] The present invention utilizes a power distribution intelligent monitoring module for a distribution network, calculates a distribution network load operation warning index for each line during the operation time of a target distribution network service command platform through a distribution network load prediction index for each line during each monitoring sub-period during the operation time of a target distribution network service command platform, warns of abnormal distribution network load lines, calculates a distribution network equipment condition control effect evaluation index for each line during the operation time of the target distribution network service command platform through a distribution network equipment condition control index for each line during each monitoring sub-period during the operation time of the target distribution network service command platform, manages the distribution network equipment condition of each line, thereby realizing an intelligent monitoring system for each line in the distribution network service command platform, improving the management efficiency of the distribution network, being conducive to realizing intelligent and refined management of the distribution network, and improving the overall operating efficiency of the power grid.

[0105] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time fault judgment and analysis system for distribution network based on one graph and multiple states, characterized in that: include: Distribution network operation time division module: used to divide the operation time of the target distribution network service command platform into various monitoring sub-periods according to the equal time division method, and number each monitoring sub-period of the operation time of the target distribution network service command platform; Distribution network monitoring data acquisition module: used to collect distribution network data of each line in each monitoring sub-period through the distribution network service command platform, and the distribution network monitoring data acquisition module includes a distribution network load operation data acquisition unit and a distribution network equipment operating condition data acquisition unit; Distribution network load prediction module: used to calculate the distribution network load prediction index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform according to the distribution network load operation data of the distribution network load operation data acquisition unit; Distribution network equipment condition control module: used to calculate the distribution network equipment condition control index of each line in each monitoring sub-period of the operation time of the target distribution network service command platform according to the distribution network equipment condition data of the distribution network equipment condition data acquisition unit; Distribution network fault prediction module: used to calculate the distribution network fault trend warning coefficient of each line in each monitoring sub-period of the operation time of the target distribution network service command platform according to the distribution network fault prediction model; Distribution network fault analysis module: used to obtain the distribution network fault trend warning coefficient of each line in each monitoring sub-period during the operation time of the target distribution network service command platform, compare it with the preset distribution network fault trend warning coefficient, and process it; Distribution network intelligent monitoring module: used to obtain the distribution network load prediction index of each line in each monitoring sub-period during the operation time of the target distribution network service command platform, calculate the distribution network load operation warning index of each line during the operation time of the target distribution network service command platform, warn the abnormal distribution network load lines, obtain the distribution network equipment condition control index of each line in each monitoring sub-period during the operation time of the target distribution network service command platform, calculate the distribution network equipment condition control effect evaluation index of each line during the operation time of the target distribution network service command platform, and manage the distribution network equipment condition of each line; One-picture-multiple-states comprehensive display interactive module: It is used to display the distribution network load forecast index, distribution network equipment condition control index and distribution network fault trend warning coefficient of each line in each monitoring sub-period of the target distribution network service command platform in the order of monitoring time, and combine each line of the power grid with the map for regional visualization and intuitive display, and dynamically display the screened abnormal lines.

2. According to claim 1, a distribution network fault real-time judgment and analysis system based on one graph and multiple states is characterized by: The distribution network operation time division module is specifically: The operating time of the target distribution network service command platform is obtained, and the operating time of the target distribution network service command platform is divided into monitoring sub-periods by equal time division, and the monitoring sub-periods of the operating time of the target distribution network service command platform are numbered as 1, 2, ..., i, ..., n in sequence.

3. The real-time fault judgment and analysis system for distribution network based on one graph and multiple states according to claim 1 is characterized by: The distribution network monitoring data acquisition module is specifically: Distribution network load operation data collection unit: The distribution network service command platform collects the outage duration of each line in each monitoring sub-period, the total number of households powered, the number of households involved in the outage, and the load, and marks them as Where 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; Distribution network equipment operating condition data collection unit: The distribution network service command platform collects the outage times, cable length, power supply area, active power, and apparent power of each line in each monitoring sub-period, and marks them as 4. The real-time fault judgment and analysis system for distribution network based on one graph and multiple states according to claim 1 is characterized in that: The distribution network load prediction module is specifically: Step S41: Calculate the load fluctuation amplitude of each monitoring sub-period by extracting the maximum load and minimum load of each line in each monitoring sub-period: Among them, bhf i It is expressed as the load fluctuation amplitude of the ith monitoring sub-period, is represented as the maximum load of the ith monitoring sub-period, It is expressed as the minimum load of the ith monitoring sub-period, It is represented as the load of the qth line in the ith monitoring sub-period, and m is the number of lines; Step S42: The calculation formula of the distribution network load prediction index is: in, It is expressed as the distribution network load forecast index of the qth line in the ith monitoring sub-period, bhf i It is expressed as the load fluctuation amplitude of the ith monitoring sub-period, BHF 预 Expressed as the preset load fluctuation amplitude, It is expressed as the outage duration of the qth line in the ith monitoring sub-period, It is expressed as the total number of households powered by the qth line in the ith monitoring sub-period, It is expressed as the number of households affected by the outage of the qth line in the ith monitoring sub-period, Δht q It is expressed as the mean outage duration of the qth line.

5. The real-time fault judgment and analysis system for distribution network based on one graph and multiple states according to claim 1 is characterized in that: The distribution network equipment operating condition control module is specifically: Step S51: Calculate the power utilization efficiency of each line in each monitoring sub-period through the active power and apparent power of each line in each monitoring sub-period: in, It is expressed as the power utilization efficiency of the qth line in the i-th monitoring sub-period, It is expressed as the active power of the qth line in the ith monitoring sub-period, Expressed as the apparent power of the qth line in the ith monitoring sub-period; Step S52: Calculate the safety of the power supply coverage area of ​​each line in each monitoring sub-period based on the number of outages of each line in each monitoring sub-period, the cable length, and the power supply area: in, It is expressed as the safety degree of the power supply coverage area of ​​the qth line in the i-th monitoring sub-period, It is expressed as the outage times of the qth line in the ith monitoring sub-period, It is expressed as the cable length of the qth line in the ith monitoring sub-period, It is expressed as the power supply area of ​​the qth line in the ith monitoring sub-period; Step S53: The calculation formula of the distribution network equipment condition control index is: in, It is expressed as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period, It is expressed as the power utilization efficiency of the qth line in the i-th monitoring sub-period, It is expressed as the safety degree of the power supply coverage area of ​​the qth line in the i-th monitoring sub-period, It is represented as the safety degree of the power supply coverage area of ​​the qth line in the i-1th monitoring sub-period, and λ1 and λ2 are the influencing factors of the power utilization efficiency and the safety degree of the power supply coverage area, respectively.

6. The real-time fault judgment and analysis system for distribution network based on one graph and multiple states according to claim 1 is characterized by: The distribution network fault prediction model is specifically: in, It is expressed as the distribution network fault trend warning coefficient of the qth line in the i-th monitoring sub-period, It is expressed as the distribution network load forecast index of the qth line in the ith monitoring sub-period, It is expressed as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period.

7. The real-time fault judgment and analysis system for distribution network based on one graph and multiple states according to claim 1 is characterized by: The distribution network fault analysis module is specifically: Obtain the distribution network fault trend warning coefficient of each line in each monitoring sub-period during the operation time of the target distribution network service command platform, and compare it with the preset distribution network fault trend warning coefficient. If the distribution network fault trend warning coefficient of a line in a certain monitoring sub-period during the operation time of the target distribution network service command platform is greater than the preset distribution network fault trend warning coefficient, it indicates that the larger the distribution network load prediction index of the line in the monitoring sub-period, the larger the distribution network equipment condition control index, the more unstable the operation of the distribution network, and the existence of failure risks. The distribution network service command platform should be used to screen out the numbers of all lines with failure risks in the monitoring sub-period, and send them to the corresponding management personnel for fault handling. Otherwise, it indicates that the smaller the distribution network load prediction index of the route in the monitoring sub-period, the smaller the distribution network equipment condition control index, the more stable the operation of the distribution network, and there is no abnormal risk in the distribution network.

8. The real-time fault judgment and analysis system for distribution network based on one graph and multiple states according to claim 1 is characterized by: The calculation formula of the distribution network load operation warning index is: Among them, ω q It is expressed as the distribution network load operation warning index of the qth line, It is expressed as the distribution network load forecast index of the qth line in the i-th monitoring sub-period, α 预 It is represented by the preset distribution network load forecast index, and n is represented by the number of monitoring sub-periods; Obtain the distribution network load operation warning index of each line during the operation time of the target distribution network service command platform, and compare it with the preset distribution network load operation warning index. If the distribution network load operation warning index of a line is greater than the preset distribution network load operation warning index, it indicates that the grid load fluctuation amplitude of the line exceeds expectations. The distribution network service command platform should be used to screen out the line numbers with abnormal loads, and issue a distribution network load abnormality warning. Otherwise, it indicates that the grid load fluctuation amplitude of the line is in line with expectations.

9. The real-time fault judgment and analysis system for distribution network based on one graph and multiple states according to claim 1 is characterized by: The calculation formula of the distribution network equipment condition control effect evaluation index is: ψ q Among them, represents the evaluation index of the operating condition control effect of the distribution network equipment of the qth line, Table β 预 denoted as the distribution network equipment condition control index of the qth line in the i-th monitoring sub-period, and denoted as the preset distribution network equipment condition control index; The distribution network equipment condition control effect evaluation index of each line during the operation time of the target distribution network service command platform is obtained, and compared with the preset distribution network equipment condition control effect evaluation index. When the safety degree of the power supply coverage area of ​​a certain line is greater, the electric energy utilization efficiency is lower, and the control degree of the distribution network equipment management personnel is heavier, then the distribution network equipment condition control effect evaluation index of the line is greater than the preset distribution network equipment condition control effect evaluation index; when the safety degree of the power supply coverage area of ​​a certain line is lower, the electric energy utilization efficiency is higher, and the control degree of the distribution network equipment management personnel is lighter, then the distribution network equipment condition control effect evaluation index of the line is less than the preset distribution network equipment condition control effect evaluation index.

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