Intelligent distribution management method for operation and maintenance work orders of electric power system

Abstract

The invention discloses a power system operation and maintenance work order intelligent distribution management method, and relates to the field of data analysis, and the main scheme is as follows: calculating a work order abnormal index # imgabs4 # according to a comprehensive risk index # imgabs0 #, a user influence index # imgabs1 #, a power system influence index # imgabs2 # and a resource availability index # imgabs3 #; and the work order emergency degree is further determined according to the work order abnormal index # imgabs5 # and the emergency degree threshold set, so that optimization of the resource allocation efficiency is facilitated, and the problems that the assessment accuracy is reduced and the assessment efficiency is reduced due to the fact that data types for assessing the work order emergency degree are single and lack of diversity and the relation among various factors is ignored at the same time are solved. And the distribution sequence of the work orders is determined according to the priority sequence of the emergency degrees of the work orders, so that the service response speed is improved, and the reliability and the stability of the system are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to an intelligent dispatching management method for power system operation and maintenance work orders. Background Art

[0002] In the field of power equipment maintenance, the intelligent dispatch management method of power system operation and maintenance work orders is conducive to reducing manual intervention and lowering the error rate, thereby improving the efficiency and quality of maintenance work and enhancing system reliability and user satisfaction.

[0003] The working principle of the intelligent dispatch management method of operation and maintenance work orders in traditional power systems is to monitor the operation status of the power grid in real time through various sensors and monitoring equipment installed in the power grid. When an abnormal situation is detected, an alarm is automatically triggered and a corresponding operation and maintenance work order is generated. The work order dispatch order is generated according to the generation time of the operation and maintenance work order.

[0004] The existing technology still has the following shortcomings: the data type for evaluating the urgency of work orders is single and lacks diversity, and the relationship between various factors is ignored, which leads to reduced accuracy of the evaluation and affects resource allocation and maintenance efficiency. Summary of the invention

[0005] 1. Technical problems solved: In view of the shortcomings of the prior art, the present invention provides an intelligent dispatching management method for power system operation and maintenance work orders, which can , User Impact Indicators , Power system impact indicators and resource availability indicators Calculate work order abnormality indicators , according to the abnormal indicators of the work order The urgency of the work order is determined by a set of urgency thresholds, which solves the problem that the data type for evaluating the urgency of the work order is single and lacks diversity, and the relationship between various factors is ignored, which leads to reduced accuracy of the evaluation and affects resource allocation and maintenance efficiency.

[0006] (II) Technical solution: To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for intelligent dispatching and managing power system operation and maintenance work orders, comprising the following steps: collecting user data, equipment data, power system data, power outage data, economic data, environmental data, traffic data, power market data, personnel data and maintenance tool data corresponding to the work order; Calculate fault severity index based on user data, equipment data and power system data , calculate economic impact indicators based on power outage data and economic data , according to the fault severity index and economic impact indicators Calculate the composite risk index ; Calculate the difficulty of fault recovery based on environmental data and traffic data , according to the difficulty of fault recovery Calculate user impact indicators with user data ; Calculate power supply reliability based on power outage data and power system data , calculate the power market risk assessment index based on power market data and power system data , according to the reliability of power supply and power market risk assessment indicators Calculate power system impact indicators ; Calculate resource availability index based on personnel data and maintenance tool data ; Based on the comprehensive risk index , User Impact Indicators , Power system impact indicators and resource availability indicators Calculating the work order urgency index ; Preset urgency threshold set; Based on the work order urgency index The urgency of the work order is determined by the set of urgency thresholds, and the order of dispatching the work orders is determined according to the priority order of the urgency of the work orders.

[0007] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders described above: calculating the fault severity index The method is: User data includes the actual number of users without power and the total number of users in the power system ; Equipment data including damaged equipment importance score and equipment damage score ; Power system data including actual voltage values , Rated voltage , actual frequency value , Rated frequency value , harmonic voltage effective value And the fundamental voltage RMS ; Calculate fault severity index based on user data, equipment data and power system data , the formula based on is: ; in, For the The importance rating of the damaged equipment, It is the serial number corresponding to different damaged devices, and its value is ; is the total number of damaged devices, which is a positive integer; For the Damage severity score for each damaged device; For the The effective value of the subharmonic voltage, is the serial number corresponding to different harmonics, and its value is ; is the total number of harmonics, which is a positive integer.

[0008] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders mentioned above: calculating the economic impact index The method is: Power outage data including outage area importance score and power outage time ; Economic data including equipment maintenance costs , production interruption loss value , business operation loss value and social service interruption losses ; Calculate economic impact indicators based on outage data and economic data , the formula based on is: ; in, For the Importance rating of outage areas , It is the serial number corresponding to different power outage areas, and its value is ; is the total number of power outage areas, which is a positive integer; For the The power outage time in the power outage area.

[0009] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders mentioned above: calculating the comprehensive risk index The method is: According to the fault severity index and economic impact indicators Calculate the composite risk index , the formula based on is: ; in, Fault severity indicator The weight coefficient is between 0.3 and 0.7; Economic Impact Indicator The weight coefficient is between 0.3 and 0.7; and .

[0010] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders mentioned above: Calculating the difficulty of fault recovery The method is: Environmental data including current temperature , rainfall , wind speed , Lightning Impact Value and air quality impact value ; Traffic data including congestion-free travel time , Actual driving time and geographic environment score ; Calculate the difficulty of fault recovery based on environmental data and traffic data , the formula based on is: ; in, The driving time to reach the business area without congestion; For the The actual driving time to reach the business area. is the sequence number corresponding to different times, and its value is ; is the total number of times the area is reached, and its value is a positive integer.

[0011] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders described above: calculating the user impact index The method is: User data also includes the number of user complaints and the number of lost users ; According to the difficulty of fault recovery 、Total number of users in the power system , Number of user complaints and the number of lost users Calculating User Impact Indicators , the formula based on is: .

[0012] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders described above: calculating the power system impact index The method is: The power outage data also includes the unit time Power outage power in the event of power outage and duration of power outage ; Power system data also includes system redundancy Total installed capacity of the system ; According to the unit time Power outage power of power outage event , duration of power outage , System Redundancy Total installed capacity of the system Calculating power supply reliability , the formula based on is: ; in, Unit time Neidi The power outage power of the power outage event, It is the sequence number corresponding to different power outage events, and its value is ; Unit time The total number of power outage events within the system, which is a positive integer; Unit time Neidi The duration of the power outage during the power outage event; Electricity market data including electricity demand and power supply ; Based on electricity market data and system redundancy Calculating risk assessment indicators for the electricity market , the formula based on is: ; According to the reliability of power supply and power market risk assessment indicators Calculate power system impact indicators , the formula based on is: ; In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders mentioned above: calculating resource availability index The method is: Personnel data includes the number of skilled personnel who can repair the fault , Work order demand Distance between technical personnel and business areas ; Repair tool data including spare parts available quantity , Spare parts demand The distance between the spare parts storage location and the business area ; Calculate resource availability indicators based on personnel data and maintenance tool data , the formula based on is: ; in, is the weight coefficient of the maintenance personnel index, ranging from 0.4 to 0.6; is the weight coefficient of the maintenance tool index, ranging from 0.4 to 0.6; and .

[0013] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders mentioned above: calculating the abnormal index of the work order The method is: Based on the comprehensive risk index , User Impact Indicators , Power system impact indicators and resource availability indicators Calculating the work order urgency index , the formula based on is: ; in, A comprehensive risk indicator The weight coefficient is between 0.2 and 0.4; Impact indicators for users The weight coefficient is 0.2 to 0.3; Power system impact index The weight coefficient is 0.2 to 0.3; Resource availability indicator The weight coefficient is 0.3 to 0.4; and .

[0014] In the preferred embodiment of the intelligent dispatching management method for power system operation and maintenance work orders, the method for determining the urgency of the work order is: The urgency threshold set includes the high urgency threshold and low urgency threshold ; According to the work order urgency index The urgency level of a work order is determined by the set of urgency thresholds, based on the following criteria: ; Among them, the priority of the urgency of the work order is high urgency work order > medium urgency work order > low urgency work order.

[0015] (III) Beneficial effects: The present invention provides a method for intelligent dispatching and managing power system operation and maintenance work orders, which has the following beneficial effects: (1) By collecting user data, equipment data, power system data, power outage data, economic data, environmental data, traffic data, power market data, personnel data, and maintenance tool data corresponding to the work order, it can provide multi-dimensional data for judging the urgency of the work order, which is conducive to improving the accuracy of the judgment.

[0016] (2) Calculate comprehensive risk indicators based on user data, equipment data, power system data and economic data , which is conducive to the quantitative evaluation of the operation status of the power system from different perspectives, provides scientific support for power companies in the allocation of operation and maintenance resources, and calculates user impact indicators based on environmental data, traffic data and user data , can accurately locate the degree of trouble caused by fault repair to users, which is conducive to the power company to formulate targeted emergency plans, enhance user satisfaction and loyalty, and calculate the power system impact index based on power outage data, power system data and power system data , which is conducive to the flexible allocation of power resources by power companies, ensuring reliable power supply, and calculating resource availability indicators based on personnel data and maintenance tool data It can clearly present the emergency repair resource reserves and deployment capabilities, and quickly match the most appropriate combination of personnel and tools when a fault occurs, avoiding delays in emergency repairs due to resource shortages or mismatches, shortening the power outage time, and at the same time guiding the daily operation and maintenance resource reserve procurement plan to ensure that resource investment is in line with actual operation and maintenance needs, so that emergency management and daily operation and maintenance can work closely together and operate efficiently.

[0017] (3) Based on comprehensive risk indicators , User Impact Indicators , Power system impact indicators and resource availability indicators Calculate work order abnormality indicators , and further based on the abnormal indicators of the work order Determining the urgency of a work order based on a set of urgency thresholds is beneficial to optimizing resource allocation efficiency. It solves the problem that the data type used to evaluate the urgency of work orders is single and lacks diversity, while ignoring the relationship between various factors, which leads to reduced accuracy of the evaluation and affects resource allocation and maintenance efficiency. Determining the order of dispatching work orders based on the priority order of their urgency is beneficial to improving service response speed and enhancing system reliability and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a schematic diagram of the working steps of an intelligent dispatching management method for power system operation and maintenance work orders. DETAILED DESCRIPTION

[0019] 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.

[0020] See also Figure 1 The present invention provides a method for intelligent dispatching and managing power system operation and maintenance work orders, comprising the following steps: Step 1: Collect user data, equipment data, power system data, power outage data, economic data, environmental data, traffic data, power market data, personnel data and maintenance tool data corresponding to the work order.

[0021] Combined with the content of step 1: By collecting user data, equipment data, power system data, power outage data, economic data, environmental data, traffic data, power market data, personnel data and maintenance tool data corresponding to the work order, it is possible to provide multi-dimensional data for judging the urgency of the work order, which is conducive to improving the accuracy of the judgment.

[0022] Step 2: Calculate the fault severity index based on user data, equipment data, and power system data , calculate economic impact indicators based on power outage data and economic data , according to the fault severity index and economic impact indicators Calculate the composite risk index ; Calculate the difficulty of fault recovery based on environmental data and traffic data , according to the difficulty of fault recovery Calculate user impact indicators with user data ; Calculate power supply reliability based on power outage data and power system data , calculate the power market risk assessment index based on power market data and power system data , according to the reliability of power supply and power market risk assessment indicators Calculate power system impact indicators ; Calculate resource availability index based on personnel data and maintenance tool data .

[0023] Step 2 includes the following steps: Step 201: Calculate the fault severity index The method is: User data includes the actual number of users without power and the total number of users in the power system .

[0024] It should be noted that the actual number of users without power It refers to the number of users whose power supply is interrupted due to equipment failure, natural disasters, etc., reflecting the scale of the power outage event. The method of obtaining it is: counting the number of users with power outages by checking the interruption of meter data. When the communication signal of the meter is lost or the meter reading stops updating, the system can determine that the user is in a power outage state. By counting these power outage meters, the actual number of users with power outages can be obtained. . Total number of users in the power system It refers to the total number of users who have signed power supply contracts with power supply enterprises and connected to the power grid within the coverage area of ​​the power system corresponding to the work order. It reflects the service scale of the power system. The basic information of all users connected to the power grid is recorded in the user information management database, including user number, user type, access time, etc. The total number of users in the power system can be determined by statistically querying the database. .

[0025] Equipment data including damaged equipment importance score and equipment damage score .

[0026] It should be noted that the importance score of damaged equipment It is used to quantitatively evaluate the criticality of equipment in the entire power system or related business processes, reflecting the impact that equipment failure may have on system operation, production activities, safety assurance, etc. The determination method is: if the equipment failure will cause power outages for more than 1,000 households, the importance score of the damaged equipment will be 10 points. If the equipment failure will cause power outage for 600 to 1,000 households, the importance score of the damaged equipment is 6 points, if the equipment failure will cause less than 600 households to lose power, the importance score of the damaged equipment 3 points. Equipment damage score It is a quantitative indicator used to measure the damage to the performance parameters of the equipment after it suffers a failure, accident or other damage factors. It reflects the severity of the equipment damage. The determination method is: perform performance testing on the damaged equipment. If the decline in its main performance parameters is within 10% of the normal operating range, the equipment damage degree score is 3 points, the decline of main performance parameters is between 10% and 30% of the normal operating range, and the equipment damage degree score is 6 points, the decline of main performance parameters exceeds 30% of the normal operating range, and the equipment damage degree score is The score is 10 points, among which the main performance parameters include output power, frequency stability, insulation and other parameters. The normal operating range of the main performance parameters is determined by referring to the equipment operation manual.

[0027] Power system data including actual voltage values , Rated voltage , actual frequency value , Rated frequency value , harmonic voltage effective value And the fundamental voltage RMS .

[0028] It should be noted that the actual voltage value It refers to the voltage actually measured at both ends of electrical equipment or circuits during the operation of the power system. The actual voltage value is collected by smart meters or data acquisition terminals installed at each node. . Rated voltage It refers to the normal operating voltage specified in the design of electrical equipment, which is determined by referring to the equipment nameplate information. Actual frequency value It refers to the number of cycles actually completed by the AC signal per unit time during the operation of the power system, measured by a fixed frequency meter installed near the electrical equipment. Refers to the operating frequency specified when the power system is designed, which is clearly defined by the national or regional power industry standards and can be obtained by consulting national power standard documents or power industry specifications. It refers to the effective value of each harmonic voltage component in a periodically changing non-sinusoidal voltage signal, which is measured and obtained by a power quality monitoring system installed in a substation or user end. It refers to the effective value of the sinusoidal voltage component with the same frequency as the rated frequency in a non-sinusoidal periodic voltage signal, which is measured and obtained by an online power quality monitoring device, such as The device can directly separate and calculate the effective value of the fundamental voltage.

[0029] Calculate fault severity index based on user data, equipment data and power system data , the formula based on is: ; in, For the The importance rating of the damaged equipment, It is the serial number corresponding to different damaged devices, and its value is ; is the total number of damaged devices, which is a positive integer; For the Damage severity score for each damaged device; For the The effective value of the subharmonic voltage, is the serial number corresponding to different harmonics, and its value is ; is the total number of harmonics, which is a positive integer.

[0030] It should be noted that the operating principle of this formula is: Used to measure the scope of power outage. The larger the ratio, the wider the power outage, and the more serious the fault. The higher it is, the greater the risk the power system faces. Used to measure the impact of damaged equipment on the power system. The larger the value, the more serious the fault. The higher it is, the greater the risk the power system faces. It is used to measure the degree of deviation between the actual operating parameters of the power system and the rated parameters. The larger the value, the greater the deviation and the more serious the fault. The higher it is, the greater the risk to the power system.

[0031] Step 202: Calculate economic impact indicators The method is: Power outage data including outage area importance score and power outage time .

[0032] It should be noted that the importance score of the power outage area An indicator for quantitatively evaluating the importance of a specific area where a power outage occurs in terms of economy, society, safety and other dimensions. The determination method is as follows: the load level information of users in the power outage area is obtained from the power user information management system, the power outage area is divided according to the user load level, and the importance score of the power outage area where the first-level load users are located is calculated. 10 points, the importance score of the power outage area where the secondary load users are located 7 points, the importance score of the power outage area in the area where the third-level load users are located 4 points, among which, the first-level load refers to the power load that will cause personal injury or death, or damage major equipment that is difficult to repair for a long time, or cause huge losses to the national economy if the power supply is interrupted, such as large hospitals and steel mills, etc. The second-level load refers to the power load that will cause great political and economic losses if the power supply is interrupted, such as banks and railway passenger stations, etc. The third-level load refers to the general power load that does not belong to the first and second-level loads, and the losses caused by the interruption of power supply are relatively small, such as residential buildings. It is the length of time from the start of power outage to the restoration of power supply. It is obtained by extracting the start and end time of power outage from the power system monitoring software platform or database, and determining the power outage time by calculating the difference between the two. .

[0033] Economic data including equipment maintenance costs , production interruption loss value , business operation loss value and social service interruption losses .

[0034] It should be noted that the equipment maintenance cost Refers to all costs incurred to restore damaged or faulty equipment to normal operation, including equipment material costs, labor costs, replacement parts costs, and commissioning costs after repair, etc. EPR The system calculates, EPR The system can record the purchase cost of raw materials required for maintenance, the man-hours and corresponding wage rates of maintenance personnel, as well as the allocated indirect costs such as equipment depreciation and energy consumption, and automatically calculate the equipment maintenance cost based on the preset cost accounting method. It refers to the economic losses caused by the interruption of production process of industrial enterprises in the power outage area due to equipment failure, power outage, etc. Calculated. Business operation loss value It refers to the economic losses caused by the normal business operations of shopping malls, supermarkets, restaurants and other commercial places in the power outage area being affected by power outages, equipment failures and other events. The determination method is: extract the sales data of normal operation days and affected operation days from the sales record system of the commercial enterprise, calculate the difference between the two, which is the reduction in sales revenue, and accumulate the reductions of all commercial places in the power outage area as the commercial operation loss value . Social service interruption loss value It refers to the loss caused to the public and the overall welfare of society by social public service institutions such as hospitals, schools, public transportation systems, and government service departments due to service interruption. The determination method is: determine the cost and benefit indicators of normal operation of social services and the cost and benefit indicators of interruption, calculate the difference between the two, and use it as the loss value of social service interruption .

[0035] Calculate economic impact indicators based on outage data and economic data , the formula based on is: ; in, For the Importance rating of outage areas , It is the serial number corresponding to different power outage areas, and its value is ; is the total number of power outage areas, which is a positive integer; For the The power outage time in the power outage area.

[0036] It should be noted that the operating principle of this formula is: The impact on users is measured by classifying users in the power outage area and multiplying the corresponding power outage time. The larger the value, the greater the impact on users and the higher the possibility of economic losses. The economic impact index The higher, The average value of economic damage reflects the impact of power outage on economic benefits. The higher the economic damage value, the higher the economic impact index. The higher it is, the greater the economic losses will be.

[0037] Step 203: Calculate the comprehensive risk index The method is: According to the fault severity index and economic impact indicators Calculate the composite risk index , the formula based on is: ; in, Fault severity indicator The weight coefficient is 0.3 to 0.7, based on the fault severity index. Comprehensive risk index The degree of impact is determined. Economic Impact Indicator The weight coefficient is 0.3 to 0.7, based on the economic impact index. Comprehensive risk index The degree of impact is determined, and .

[0038] It should be noted that this formula obtains the comprehensive risk index by comprehensively considering the severity of the failure and the economic losses caused. , comprehensive risk index The higher it is, the higher the urgency of the work order.

[0039] Step 204: Calculate the difficulty of fault recovery The method is: Environmental data including current temperature , rainfall , wind speed , Lightning Impact Value and air quality impact value .

[0040] It should be noted that the current temperature It is measured by temperature sensor. It is obtained through weather radar measurement. By emitting electromagnetic waves and receiving echo signals, weather radar can detect information such as the size, quantity and movement speed of precipitation particles, and then estimate the rainfall and its distribution range. Obtained through measurement with a three-cup anemometer. Lightning impact value It is an indicator for comprehensively evaluating the impact of lightning work orders on the corresponding area. The determination method is: when the peak value of the return current of lightning is less than 10 When the lightning impact value 2 points, when the peak value of the return current of lightning is 10 ~50 When the lightning impact value 4 points, when the peak value of the return current of lightning is 50 ~100 When the lightning impact value 6 points, when the peak value of the return current of lightning exceeds 100 When the lightning impact value The air quality impact value is 8 points. It is used to evaluate the quality of the atmospheric environment. The determination method is: measure the air quality index through a gas analyzer. When the air quality index is less than 50, the air quality impact value 1 point, when the air quality index is 50-150, the air quality impact value 3 points, when the air quality index is 150-200, the air quality impact value 6 points. When the air quality index exceeds 200, the air quality impact value It is 8 points.

[0041] Traffic data including congestion-free travel time , Actual driving time and geographic environment score .

[0042] It should be noted that the driving time without congestion is It refers to the driving time to reach the business area corresponding to the work order when there is no traffic congestion on the road. It reflects the shortest travel time under ideal traffic conditions. It is an important reference indicator for measuring road capacity and traffic efficiency. It is calculated by dividing the distance by the average driving speed of the vehicle under no congestion. It is the actual time taken by the vehicle to travel from the starting point to the end point during the actual driving process. The method of determining it is: check the historical maintenance record system, filter the departure time and arrival time corresponding to the maintenance event in the business area, calculate the difference between the two, and use it as the actual driving time . Geographical environment score It is a quantitative score to measure the geographical environment of the business area corresponding to the work order. The determination method is: when the poster height is between 0 and 300 meters, the geographical environment score 2 points. When the poster height is between 300 and 500 meters, the geographical environment score is 6 points. When the poster height exceeds 500 meters, the geographical environment score is It is 8 points.

[0043] Calculate the difficulty of fault recovery based on environmental data and traffic data , the formula based on is: ; in, The driving time to reach the business area without congestion; For the The actual driving time to reach the business area. is the sequence number corresponding to different times, and its value is ; is the total number of times the area is reached, and its value is a positive integer.

[0044] It should be noted that the operating principle of this formula is: It is used to measure the deviation between the actual temperature, rainfall and wind speed data and the standard temperature, rainfall and wind speed data, and to obtain the environmental impact value by taking into account the impact of lightning and air quality. It is used to measure the difficulty of reaching the corresponding business area. This formula comprehensively considers the impact of environmental data and traffic data to obtain the difficulty of fault recovery. .

[0045] Step 205: Calculate user impact index The method is: User data also includes the number of user complaints and the number of lost users .

[0046] It should be noted that the number of user complaints It refers to the total number of complaints and feedback calls received by the customer service center of the power company regarding power problems. It is an important indicator for measuring user satisfaction. It is obtained by querying the customer service management system of the power company. The customer service management system will record the complaint time, complaint channel, complaint content, user basic information, etc. in detail. By counting these records, the number of user complaints can be obtained. . Number of lost users Refers to the number of users who stop using the power supply company's power services. The determination method is: query the number of users who terminated their power contracts and the number of users with long-term zero power consumption through the user account management system, calculate the sum of the two numbers of users, and use it as the number of lost users .

[0047] According to the difficulty of fault recovery 、Total number of users in the power system , Number of user complaints and the number of lost users Calculating User Impact Indicators , the formula based on is: ; It should be noted that the operating principle of this formula is: Used to reflect the difficulty of fault recovery The synergy between the three factors of the number of complaints and the proportion of lost users. The sine function is used to further amplify the overall impact of the three factors, and the indicators have a more obvious change trend within different value ranges, which can more sensitively reflect the impact of the comprehensive changes of various factors on the results.

[0048] Step 206: Calculate power system impact indicators The method is: The power outage data also includes the unit time Power outage power in the event of power outage and duration of power outage .

[0049] It should be noted that the power outage power It refers to the total power of all users and equipment whose power supply is interrupted due to a power outage. It is an indicator to measure the scope and extent of the power outage event. The determination method is: in the power grid monitoring system, check the power data records at the boundary of the power outage area before and after the power outage event. The power before the power outage is the normal power supply power, and the power after the power outage drops to zero. The difference between the two is the power outage power of the power outage event. . Duration of power outage It refers to the time interval from the moment the power supply is interrupted to the moment the power supply is restored, reflecting the length of time the power outage event affects the user. The determination method is as follows: the fault recording device in the power system will record the occurrence time and recovery time of each fault, and the record corresponding to the power outage event is searched in the power grid fault recording system to obtain the power outage start time and recovery time. The power outage duration can be obtained by subtracting the two. .

[0050] Power system data also includes system redundancy Total installed capacity of the system .

[0051] It should be noted that the system redundancy It refers to the ratio of the additional capacity or equipment capacity configured in power generation, transmission, transformation, distribution and other links to the capacity or equipment capacity required for normal operation in order to ensure the reliability and stability of power supply. It is an important indicator to ensure uninterrupted power supply of the power system in response to equipment failures, sudden peak power consumption, natural disasters, etc. The determination method is: total installed capacity of the system It is calculated by the redundancy of the power generation link + the redundancy of the transmission link + the redundancy of the substation and distribution link. The calculation method of the redundancy of the power generation link is: obtain the total installed capacity of the generator set from the equipment management database of the power system or the installed capacity record of the power generation enterprise , collect historical load data and find out the maximum load demand of the system , the redundancy of the power generation link is achieved through The calculation method of transmission link redundancy is as follows: obtain the total designed transmission capacity of the transmission line from the transmission line design document or the power grid operation management system , count the historical transmission power and find the maximum transmission power of the transmission line , the redundancy of the transmission link is achieved through The calculation method for redundancy of substation and distribution links is as follows: Get the total rated capacity of transformers from the substation equipment ledger , calculate the actual maximum transformer capacity requirement through power system analysis software or actual operation data , the redundancy of the substation and distribution links is achieved through Calculated. Total installed capacity of the system It refers to the sum of the rated power of all power generation equipment in the power system, such as thermal power generating units, hydropower generating units, wind power generating units, solar power generating units, etc. It reflects the maximum power output capacity that the power system can provide under ideal conditions. It is an important indicator for measuring the power generation scale of the power system. The determination method is: extract the rated power data of the power generation equipment from the energy management system database of the power grid dispatching center, add up the rated powers of all generating units, and then get the total installed capacity of the system. .

[0052] According to the unit time Power outage power of power outage event , duration of power outage , System Redundancy Total installed capacity of the system Calculating power supply reliability , the formula based on is: ; in, Unit time Neidi The power outage power of the power outage event, It is the sequence number corresponding to different power outage events, and its value is ; Unit time The total number of power outage events within the system, which is a positive integer; Unit time Neidi The duration of the power outage event.

[0053] It should be noted that the operating principle of this formula is: is the proportion of power supply reliability loss caused by power outage events, It is the remaining proportion of power supply reliability after considering the impact of power outages, multiplied by the system redundancy Adjust to get power supply reliability .

[0054] Electricity market data including electricity demand and power supply .

[0055] It should be noted that the power demand It refers to the total amount of electricity required by power users to meet their production, life and other activities within a certain period of time. The determination method is: the power company regularly records the user's meter data, summarizes the meter readings of all users, and obtains the power demand . Power supply It refers to the total amount of electric energy that power suppliers such as power generation companies and power grid companies can provide to power users within a certain period of time. The determination method is: power generation companies regularly report the operating status and power generation data of their power generation equipment to the power regulatory department or power grid dispatching agency, and the power grid dispatching agency summarizes and sums the data reported by all power generation companies to obtain the power supply amount. .

[0056] Based on electricity market data and system redundancy Calculating risk assessment indicators for the electricity market , the formula based on is: ; It should be noted that this formula is used to measure the risk level of supply and demand imbalance in the electricity market, while taking into account system redundancy. The buffering effect of the power market risk assessment index is obtained When the gap between supply and demand is large and the system redundancy is low, the power market risk assessment index Higher.

[0057] According to the reliability of power supply and power market risk assessment indicators Calculate power system impact indicators , the formula based on is: ; It should be noted that this formula takes into account the reliability of power supply and power market risk assessment indicators The impact of the power system is obtained ,in, is the base of the natural logarithm in the exponential function.

[0058] Step 207: Calculate resource availability index The method is: Personnel data includes the number of skilled personnel who can repair the fault , Work order demand Distance between technical personnel and business areas .

[0059] It should be noted that the number of skilled personnel who can repair the fault Refers to the total number of personnel who have the skills and knowledge required to repair the fault corresponding to the work order. The determination method is: obtain the maintenance personnel skill list database, set screening conditions according to the fault type, for example, for power equipment faults, screen out personnel with power equipment maintenance qualifications, relevant training experience and maintenance experience, and count the number of qualified personnel as the number of skilled personnel who can repair the fault . Work order demand Refers to the number of maintenance personnel required to handle faults and problems in systems, equipment or services. The determination method is as follows: when receiving an operation and maintenance work order, the operation and maintenance personnel first determine the fault type based on user feedback, monitoring system alarms and other information, and then query the number of maintenance personnel required for historical maintenance of this type of fault from the customer service system or operation and maintenance management system and calculate the average value as the work order demand. . Distance between technical personnel and business areas It refers to the geographical distance between the location of a technician with maintenance skills and the business area where a fault occurs and needs to be repaired. It is obtained by using a geographic information system to obtain the technician's location information and calculate the distance between him and the business area.

[0060] Repair tool data including spare parts available quantity , Spare parts demand The distance between the spare parts storage location and the business area .

[0061] It should be noted that the number of spare parts available It refers to the number of spare parts needed to repair a fault that are actually available for repair work in inventory, which is determined by querying the inventory management system. Refers to the number of spare parts required for the normal implementation of this maintenance work. The method of determination is: obtain the maintenance plan document of the power system, check the equipment list and maintenance tasks planned for maintenance, determine the name and quantity of the spare parts required for replacement or maintenance for each maintenance task, and summarize the number of spare parts required for all maintenance tasks to obtain the spare parts demand . Distance between spare parts storage location and business area It refers to the spatial distance between the geographical location of the power system spare parts storage warehouse and the business area where equipment failures occur and need to be repaired. By using geographic information system software, by inputting the geographic coordinates of the spare parts storage location and the business area, the actual traffic route distance between the two is calculated as the distance between the spare parts storage location and the business area. .

[0062] Calculate resource availability indicators based on personnel data and maintenance tool data , the formula based on is: ; in, is the weight coefficient of the maintenance personnel indicator, ranging from 0.4 to 0.6. The degree of impact is determined. is the weight coefficient of the maintenance tool indicator, ranging from 0.4 to 0.6. The degree of impact is determined, and .

[0063] It should be noted that the operating principle of this formula is: It is used to measure the availability of maintenance personnel resources and comprehensively consider the distance factor to obtain the maintenance personnel index. The higher the maintenance personnel index, the higher the resource availability index. The higher it is, the more urgent the work order is. It is used to measure the availability of maintenance tool resources and take distance factors into consideration to obtain the resource availability index. The higher it is, the more urgent the work order is.

[0064] Step 208: Calculate the work order abnormality index The method is: Based on the comprehensive risk index , User Impact Indicators , Power system impact indicators and resource availability indicators Calculating the work order urgency index , the formula based on is: ; in, A comprehensive risk indicator The weight coefficient is 0.2 to 0.4, based on the comprehensive risk index. Urgency indicator for work orders The degree of impact is determined. Impact indicators for users The weight coefficient is 0.2 to 0.3, based on the user impact index Urgency indicator for work orders The degree of impact is determined. Power system impact index The weight coefficient is 0.2 to 0.3, based on the power system impact index. Urgency indicator for work orders The degree of impact is determined. Resource availability indicator The weight coefficient is 0.3 to 0.4, based on the resource availability index. Urgency indicator for work orders The degree of impact is determined, and .

[0065] It should be noted that the operating principle of this formula is: is the geometric mean. When all four indicators are good, the geometric mean is larger. The harmonic mean value pays more attention to the smaller value of the four indicators and is more sensitive to the imbalance of the indicators. This formula takes the reciprocal of the geometric mean and the reciprocal of the harmonic mean into account, and can comprehensively consider the balance and imbalance of the indicators to obtain the work order urgency index. .

[0066] Combined with the contents of step 201 to step 208: Calculate comprehensive risk indicators based on user data, equipment data, power system data and economic data , which is conducive to the quantitative evaluation of the operation status of the power system from different perspectives, provides scientific support for power companies in the allocation of operation and maintenance resources, and calculates user impact indicators based on environmental data, traffic data and user data , can accurately locate the degree of trouble caused by fault repair to users, which is conducive to the power company to formulate targeted emergency plans, enhance user satisfaction and loyalty, and calculate the power system impact index based on power outage data, power system data and power system data , which is conducive to the flexible allocation of power resources by power companies, ensuring reliable power supply, and calculating resource availability indicators based on personnel data and maintenance tool data It can clearly present the emergency repair resource reserves and deployment capabilities, and quickly match the most appropriate combination of personnel and tools when a fault occurs, avoiding delays in emergency repairs due to resource shortages or mismatches, shortening the power outage time, and at the same time guiding the daily operation and maintenance resource reserve procurement plan to ensure that resource investment is in line with actual operation and maintenance needs, so that emergency management and daily operation and maintenance can work closely together and operate efficiently.

[0067] Step 3: Based on comprehensive risk indicators , User Impact Indicators , Power system impact indicators and resource availability indicators Calculating the work order urgency index ; Preset urgency threshold set; Based on the work order urgency index The urgency of the work order is determined by the set of urgency thresholds, and the order of dispatching the work orders is determined according to the priority order of the urgency of the work orders.

[0068] Step 3 includes the following steps: Step 301: The method for determining the urgency of the work order is: The urgency threshold set includes the high urgency threshold and low urgency threshold .

[0069] It should be noted that the high urgency threshold and low urgency threshold The method for determining is: collect a large amount of historical work order data, calculate the work order urgency index of the historical work order data according to the above method, filter out the smaller 30% of the data and calculate its average and standard deviation, and calculate the value of the average plus two times the standard deviation as the high urgency threshold The reference value is calculated by subtracting two times the standard deviation from the mean value as the low urgency threshold. reference value.

[0070] According to the work order urgency index The urgency level of a work order is determined by the set of urgency thresholds, based on the following criteria: ; Among them, the priority of the urgency of the work order is high urgency work order > medium urgency work order > low urgency work order. The higher the priority, the higher the position in the dispatch order.

[0071] Combined with the content of step 301: Based on the comprehensive risk index , User Impact Indicators , Power system impact indicators and resource availability indicators Calculate work order abnormality indicators , and further based on the abnormal indicators of the work order Determining the urgency of a work order based on a set of urgency thresholds is beneficial to optimizing resource allocation efficiency. It solves the problem that the data type used to evaluate the urgency of work orders is single and lacks diversity, while ignoring the relationship between various factors, which leads to reduced accuracy of the evaluation and affects resource allocation and maintenance efficiency. Determining the order of dispatching work orders based on the priority order of their urgency is beneficial to improving service response speed and enhancing system reliability and stability.

[0072] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0073] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for intelligent dispatching and managing power system operation and maintenance work orders, characterized in that: The following steps are involved: Collect user data, equipment data, power system data, power outage data, economic data, environmental data, traffic data, power market data, personnel data and maintenance tool data corresponding to the work order; Calculate fault severity index based on user data, equipment data and power system data , calculate economic impact indicators based on power outage data and economic data , according to the fault severity index and economic impact indicators Calculate the composite risk index ; Calculate the difficulty of fault recovery based on environmental data and traffic data , according to the difficulty of fault recovery Calculate user impact indicators with user data ; Calculate power supply reliability based on power outage data and power system data , calculate the power market risk assessment index based on power market data and power system data , according to the reliability of power supply and power market risk assessment indicators Calculate power system impact indicators ; Calculate resource availability index based on personnel data and maintenance tool data ; Based on the comprehensive risk index , User Impact Indicators , Power system impact indicators and resource availability indicators Calculating the work order urgency index ; Preset urgency threshold set; based on the work order urgency index The urgency of the work order is determined by the set of urgency thresholds, and the order of dispatching the work orders is determined according to the priority order of the urgency of the work orders.

2. According to claim 1, a method for intelligent dispatching and managing power system operation and maintenance work orders is characterized by: Calculate the fault severity index The method is: User data includes the actual number of users without power and the total number of users in the power system ; Equipment data including damaged equipment importance score and equipment damage score ; Power system data including actual voltage values , Rated voltage , actual frequency value , Rated frequency value , harmonic voltage effective value And the fundamental voltage RMS ; Calculate fault severity index based on user data, equipment data and power system data , the formula based on is: ； in, For the The importance rating of the damaged equipment, It is the serial number corresponding to different damaged devices, and its value is ; is the total number of damaged devices, which is a positive integer; For the Damage severity score for each damaged device; For the The effective value of the subharmonic voltage, is the serial number corresponding to different harmonics, and its value is ; is the total number of harmonics, which is a positive integer.

3. According to claim 2, a method for intelligent dispatching and managing power system operation and maintenance work orders is characterized by: Calculating economic impact indicators The method is: Power outage data including outage area importance score and power outage time ; Economic data including equipment maintenance costs , production interruption loss value , business operation loss value and social service interruption losses ; Calculate economic impact indicators based on outage data and economic data , the formula based on is: ； in, For the Importance rating of outage areas , It is the serial number corresponding to different power outage areas, and its value is ; is the total number of power outage areas, which is a positive integer; For the The power outage time in the power outage area.

4. The method for intelligent dispatching and managing power system operation and maintenance work orders according to claim 3 is characterized by: Calculate the composite risk index The method is: According to the fault severity index and economic impact indicators Calculate the composite risk index , the formula based on is: ； in, Fault severity indicator The weight coefficient is between 0.3 and 0.7; Economic Impact Indicator The weight coefficient is between 0.3 and 0.7; and .

5. The method for intelligent dispatching and managing power system operation and maintenance work orders according to claim 4 is characterized by: Calculating Failure Recovery Difficulty The method is: Environmental data including current temperature , rainfall , wind speed , Lightning Impact Value and air quality impact value ; Traffic data including congestion-free travel time , Actual driving time and geographic environment score ; Calculate the difficulty of fault recovery based on environmental data and traffic data , the formula based on is: ； in, The driving time to reach the business area without congestion; For the The actual driving time to reach the business area. is the sequence number corresponding to different times, and its value is ; is the total number of times the area is reached, and its value is a positive integer.

6. A method for intelligent dispatching and managing power system operation and maintenance work orders according to claim 5, characterized in that: Calculating User Impact Indicators The method is: User data also includes the number of user complaints and the number of lost users ; According to the difficulty of fault recovery 、Total number of users in the power system , Number of user complaints and the number of lost users Calculating User Impact Indicators , the formula based on is: 。 7. The method for intelligent dispatching and managing power system operation and maintenance work orders according to claim 6 is characterized by: Calculate power system impact indicators The method is: The power outage data also includes the unit time Power outage power in the event of power outage and duration of power outage ; Power system data also includes system redundancy Total installed capacity of the system ; According to the unit time Power outage power of power outage event , duration of power outage , System Redundancy Total installed capacity of the system Calculating power supply reliability , the formula based on is: ； in, Unit time Neidi The power outage power of the power outage event, It is the sequence number corresponding to different power outage events, and its value is ; Unit time The total number of power outage events within the system, which is a positive integer; Unit time Neidi The duration of the power outage during the power outage event; Electricity market data including electricity demand and power supply ; Based on electricity market data and system redundancy Calculating risk assessment indicators for the electricity market , the formula based on is: ； According to the reliability of power supply and power market risk assessment indicators Calculate power system impact indicators , the formula based on is: 。 8. The method for intelligent dispatching and managing power system operation and maintenance work orders according to claim 7 is characterized by: Compute resource availability indicators The method is: Personnel data includes the number of skilled personnel who can repair the fault , Work order demand Distance between technical personnel and business areas ; Repair tool data including spare parts available quantity , Spare parts demand The distance between the spare parts storage location and the business area ; Calculate resource availability indicators based on personnel data and maintenance tool data , the formula based on is: ； in, is the weight coefficient of the maintenance personnel index, ranging from 0.4 to 0.6; is the weight coefficient of the maintenance tool index, ranging from 0.4 to 0.6; and .

9. The method for intelligent dispatching and managing power system operation and maintenance work orders according to claim 8, characterized in that: Calculate work order abnormality indicators The method is: Based on the comprehensive risk index , User Impact Indicators , Power system impact indicators and resource availability indicators Calculating the work order urgency index , the formula based on is: ； in, A comprehensive risk indicator The weight coefficient is between 0.2 and 0.4; Impact indicators for users The weight coefficient is 0.2 to 0.3; Power system impact index The weight coefficient is 0.2 to 0.3; Resource availability indicator The weight coefficient is 0.3 to 0.4; and .

10. The method for intelligent dispatching and managing power system operation and maintenance work orders according to claim 9, characterized in that: The method to determine the urgency of a work order is: The urgency threshold set includes the high urgency threshold and low urgency threshold ; According to the work order urgency index The urgency level of a work order is determined by the set of urgency thresholds, based on the following criteria: ； Among them, the priority of the urgency of the work order is high urgency work order > medium urgency work order > low urgency work order.

Images