Power distribution operation and maintenance system and method based on intelligent power distribution

Abstract

The invention relates to the technical field of power distribution network operation and maintenance, and discloses a power distribution operation and maintenance system and method based on intelligent power distribution, and the system comprises an operation data collection module, a fault area recognition module, a recovery benefit calculation module, a recovery strategy setting module, and a recovery strategy execution module. In the prior art, traditional manual intervention or static control is difficult to realize real-time and accurate self-healing operation and maintenance especially under the conditions of large-scale load change and a complex power distribution network topological structure. According to the intelligent power distribution operation and maintenance method provided by the invention, the fault area can be intelligently identified in real time, and optimization recovery is carried out according to the weighted load priority, so that the problems of time delay and inaccuracy of recovery in a traditional method are avoided, and the reliability and automation degree of self-healing operation and maintenance of the power distribution network are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution network operation and maintenance, and in particular to a power distribution operation and maintenance system and method based on smart power distribution. Background Art

[0002] Currently, the operation and maintenance of distribution networks largely rely on manual inspections and traditional automated control systems. While this approach can ensure power supply security to a certain extent, it has some significant shortcomings. For example, traditional fault detection and recovery systems often require manual intervention and lack the ability to coordinate multiple fault areas and complex topologies in real time. Furthermore, most existing technologies rely on static topologies and limited fault response mechanisms, resulting in an inability to quickly and accurately isolate faults and restore power when loads fluctuate significantly and multiple fault areas occur simultaneously. Existing technologies cannot fully meet the needs for automated, efficient, and accurate operation and maintenance in complex power grid environments, especially in situations such as large-scale load fluctuations and rapid fault expansion. Therefore, there is an urgent need for a distribution operation and maintenance system and method based on smart distribution. Through a series of innovative technologies such as real-time data analysis, fault identification and isolation, weighted load assessment, and optimized recovery strategies, it can achieve efficient and automated grid restoration even in complex fault situations, thereby greatly improving the operation and maintenance efficiency and system reliability of the distribution network and compensating for the shortcomings of traditional methods. Summary of the Invention

[0003] In response to the above-mentioned technical deficiencies, the purpose of the present invention is to propose a power distribution operation and maintenance system and method based on smart power distribution, aiming to solve the technical problem of traditional manual intervention or static control in the existing technology, especially the difficulty in achieving real-time and accurate self-healing operation and maintenance under conditions of large-scale load changes and complex distribution network topology.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a power distribution operation and maintenance system based on smart power distribution.

[0005] The power distribution operation and maintenance system based on smart power distribution includes:

[0006] The operation data acquisition module is used to collect the distribution network operation data in real time, including the node voltage set V, the branch current set E and the switch topology state set S, and build the electrical diagram model of the distribution network based on the grid operation data ;

[0007] The fault area identification module is used to extract current change characteristics, voltage change characteristics and switch state characteristics from the electrical diagram model, identify the fault area based on the current change characteristics and voltage change characteristics, and automatically isolate the fault based on the switch state characteristics;

[0008] The restoration benefit calculation module is used to automatically isolate the fault, detect the currently affected area, and obtain a set of power-off areas. Based on the set of power-off areas, it calculates a weighted load restoration benefit index.

[0009] The restoration strategy setting module is used to obtain the available branch connection capacity and the corresponding tie switch list from the adjacent feeder bus agents corresponding to the power outage area set. Based on the available branch connection capacity and the corresponding tie switch list, the restoration strategy objective function and voltage and current constraints are constructed. The restoration strategy objective function is solved by combining the ant colony algorithm to obtain the optimized restoration strategy.

[0010] The recovery strategy execution module is used to perform operation and maintenance recovery in a distributed manner according to the optimized recovery strategy.

[0011] Preferably, in the operation data acquisition module, the step of collecting the distribution network operation data in real time specifically includes: collecting the distribution network operation data in real time by setting voltage sensors, current transformers and intelligent switch sensors in the feeder lines, branch lines and section switch areas of the distribution network.

[0012] Preferably, in the fault area identification module, the electrical diagram model The steps of extracting current change characteristics, voltage change characteristics, and switch state characteristics, identifying the fault area according to the current change characteristics and voltage change characteristics, and automatically isolating the fault based on the switch state characteristics specifically include:

[0013] Preset time window T, first from the electrical diagram model The current of each branch i at time t is extracted by the time series feature extraction method ,Voltage and switch status , and then after the preset time window T, from the electrical diagram model Extract the current of each branch i at time t+T ,Voltage and switch status ;

[0014] According to the current ,Voltage and switch status and current ,Voltage and switch status Calculate the current change characteristics , voltage change characteristics and switch state characteristics ;

[0015] Based on the current change characteristics , voltage change characteristics and switch state characteristics Determine whether branch i has a fault within the preset time window T, and then obtain the fault area;

[0016] Automatically isolate the fault area based on the switch status characteristics.

[0017] Preferably, in the restoration benefit calculation module, the formula for the power-off area set is expressed as:

[0018] ;

[0019] in, is the set of power-off areas, is the branch j in the set of power-off areas, is the voltage of branch j, is the fault area;

[0020] For each branch j in the power outage area set, obtain the corresponding current load demand , and introduce recovery priority weight , based on current load demand and recovery priority weights Defining weighted load restoration benefit indicators for in It is the adjustment coefficient of weighted load recovery benefit index.

[0021] Preferably, in the recovery strategy setting module, the voltage and current constraints constructed are ,in, is a preset first voltage threshold, is a preset second voltage threshold, the first voltage threshold is less than the second voltage threshold; is the new voltage value after connecting to the healthy feeder, is the new current value after connecting to the healthy feeder, is a preset first current threshold.

[0022] Preferably, in the recovery strategy setting module, the recovery strategy objective function constructed is:

[0023] ;

[0024] in, is the objective function of the recovery strategy, is the weighted load restoration benefit index, is the number of tie switches obtained from the corresponding tie switch list, is the number of regions that could not be restored due to capacity limitations, and is the weight coefficient of the objective function of the recovery strategy.

[0025] Preferably, in the recovery strategy setting module, the recovery strategy objective function constructed is:

[0026] ;

[0027] in, is the objective function of the recovery strategy, is the weighted load restoration benefit index, is the number of tie switches obtained from the corresponding tie switch list, is the number of regions that could not be restored due to capacity limitations, and is the weight coefficient of the objective function of the recovery strategy.

[0028] The present invention also provides a power distribution operation and maintenance method based on smart power distribution, comprising:

[0029] Step S10: Real-time collection of distribution network operation data, including node voltage set V, branch current set E and switch topology state set S, and construction of the electrical diagram model of the distribution network based on the grid operation data ;

[0030] Step S20: extracting current variation characteristics, voltage variation characteristics, and switch state characteristics from the electrical diagram model, identifying the fault area based on the current variation characteristics and voltage variation characteristics, and automatically isolating the fault based on the switch state characteristics;

[0031] Step S30: After the fault is automatically isolated, the currently affected area is detected to obtain a set of power-off areas, and a weighted load restoration benefit index is calculated based on the set of power-off areas;

[0032] Step S40: Obtain the available branch capacity and the corresponding tie switch list from the adjacent feeder bus agents corresponding to the power outage area set, construct a restoration strategy objective function and voltage and current constraints based on the available branch capacity and the corresponding tie switch list, and solve the restoration strategy objective function in combination with the ant colony algorithm to obtain an optimized restoration strategy;

[0033] Step S50: Perform operation and maintenance recovery in a distributed manner according to the optimized recovery strategy.

[0034] The present invention also provides a computer program product, including a power distribution operation and maintenance program based on smart power distribution, which implements the power distribution operation and maintenance method based on smart power distribution when executed by a processor.

[0035] The beneficial effects of the present invention are as follows: compared with the traditional manual intervention or static control in the prior art, the technical problem of difficulty in achieving real-time and accurate self-healing operation and maintenance is solved, especially under the conditions of large-scale load changes and complex distribution network topology; because the intelligent distribution operation and maintenance method of the present invention can intelligently identify the fault area in real time and optimize recovery based on weighted load priority, thereby avoiding the recovery delay and inaccuracy problems in traditional methods, and improving the reliability and automation level of distribution network self-healing operation and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 This is a system diagram of a first embodiment of a power distribution operation and maintenance system based on smart power distribution according to the present invention.

[0038] Figure 2 This is a schematic diagram of the equipment of a power distribution operation and maintenance system based on smart power distribution in the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0040] Example 1: Figure 1 As shown, it is a flow chart of the first embodiment of the power distribution operation and maintenance system based on smart power distribution of the present invention, and the first embodiment of the power distribution operation and maintenance system based on smart power distribution of the present invention is proposed.

[0041] In a first embodiment, the power distribution operation and maintenance system based on smart power distribution includes:

[0042] The operation data acquisition module is used to collect the distribution network operation data in real time, including the node voltage set V, the branch current set E and the switch topology state set S, and build the electrical diagram model of the distribution network based on the grid operation data ;

[0043] It should be noted that in the operation data acquisition module, the step of collecting distribution network operation data in real time specifically includes: setting voltage sensors, current transformers and intelligent switch sensors in the feeder lines, branch lines and section switch areas of the distribution network to collect distribution network operation data in real time.

[0044] It is understandable that the above-mentioned sensor deployment method can fully cover the key nodes and substation topology connection points of the power grid, not only meeting the monitoring of static parameters (such as steady-state voltage and current), but also timely capturing the dynamic characteristics of emergencies (such as voltage sags, current surges, and switch tripping), effectively supporting subsequent fault identification and recovery strategy decision-making.

[0045] It should be understood that compared with traditional systems that rely solely on centralized data collection at the SCADA master control node, this module introduces a multi-point, distributed data collection strategy into the distribution network, which helps improve the system's fault tolerance and data coverage density, allowing the system to maintain the continuity and reliability of grid operation data when facing changes in feeder structure (such as switch reversal, load transfer) or local communication interruptions.

[0046] For example, after deploying 12 distributed collection points in an actual urban distribution network, the system's response time when detecting light ground faults (single-phase short-time tripping) was reduced from an average of 2.5 seconds in the original system to 0.6 seconds, and the fault identification accuracy rate increased from 86% to 96.5%, effectively demonstrating the technical effectiveness of this module in improving fault response speed and identification accuracy.

[0047] The fault area identification module is used to extract current change characteristics, voltage change characteristics and switch state characteristics from the electrical diagram model, identify the fault area based on the current change characteristics and voltage change characteristics, and automatically isolate the fault based on the switch state characteristics;

[0048] It should be noted that in the fault area identification module, the electrical diagram model The steps of extracting current change characteristics, voltage change characteristics, and switch state characteristics, identifying the fault area according to the current change characteristics and voltage change characteristics, and automatically isolating the fault based on the switch state characteristics specifically include:

[0049] Preset time window T, first from the electrical diagram model The current of each branch i at time t is extracted by the time series feature extraction method ,Voltage and switch status , and then after the preset time window T, from the electrical diagram model Extract the current of each branch i at time t+T ,Voltage and switch status ;

[0050] According to the current ,Voltage and switch status and current ,Voltage and switch status Calculate the current change characteristics , voltage change characteristics and switch state characteristics ;

[0051] Based on the current change characteristics , voltage change characteristics and switch state characteristics Determine whether branch i has a fault within the preset time window T, and then obtain the fault area;

[0052] Automatically isolate the fault area based on the switch status characteristics.

[0053] It's easy to understand that extracting current, voltage, and switch status data within a continuous time window effectively captures dynamic changes in grid operation. When a fault occurs, the current and voltage signals will exhibit abnormal changes, particularly noticeable in the case of short or open circuit faults. Therefore, by comparing pre- and post-fault data, the abnormal area can be clearly identified, effectively locating the fault.

[0054] It should be understood that this module not only relies on static monitoring data but also captures the impact of dynamic events on the distribution network through time series feature analysis. Unlike traditional methods that rely on single-point anomaly monitoring, continuous analysis of time series data can detect faults and locate their occurrence areas in the shortest possible time. This improves the system's responsiveness to sudden faults and reduces the possibility of misjudgments and missed detections.

[0055] For example, in a real-world test case, a short circuit occurred on a branch of the distribution network. By comparing data 30 seconds before and after the fault, the system detected a sudden increase in current accompanied by a rapid drop in voltage. By extracting and calculating the branch's current and voltage characteristics within a time window of T = 30 seconds, the system successfully identified the branch as the fault area. By further analyzing the switch status characteristics, the system instructed the relevant switches to disconnect, successfully isolating the fault area.

[0056] The restoration benefit calculation module is used to automatically isolate the fault, detect the currently affected area, and obtain a set of power-off areas. Based on the set of power-off areas, it calculates a weighted load restoration benefit index.

[0057] It should be noted that in the restoration benefit calculation module, the formula for the power outage area set is expressed as:

[0058] ;

[0059] in, is the set of power-off areas, is the branch j in the set of power-off regions, is the voltage of branch j, is the fault area;

[0060] For each branch j in the power outage area set, obtain the corresponding current load demand , and introduce recovery priority weight , based on current load demand and recovery priority weights Defining weighted load restoration benefit indicators for in It is the adjustment coefficient of weighted load recovery benefit index.

[0061] Understandably, this restoration benefit calculation method not only considers regional load demand but also incorporates the importance weights of different regions. Compared to traditional methods that prioritize restoration based solely on load size, this method prioritizes the restoration of critical loads (such as public safety and emergency response centers), effectively improving the distribution network's post-accident recovery efficiency and its ability to provide social services.

[0062] It should be understood that the introduction of the adjustment coefficient The purpose of this is to flexibly adjust different restoration strategies: when the overall power supply capacity of the power grid is limited, the This increases the weighting of high-priority areas to achieve optimal resource allocation. Furthermore, unlike existing methods that rely solely on manual priority setting, this invention combines calculated weights with real-time load dynamics to achieve a more accurate, data-driven recovery decision-making mechanism.

[0063] For example, in a certain urban area, both branch A (residential area) and branch B (hospital area) lose power due to a feeder fault. The collected data is as follows: , (normal priority), , (high priority), set , then the weighted restoration benefit indicators of the two are: , Although branch A carries a greater load, branch B has a higher weighted benefit. Therefore, in the restoration strategy, the system prioritizes restoring power to the hospital area. This strategy significantly improves the rationality and social benefits of restoration decisions.

[0064] The restoration strategy setting module is used to obtain the available branch connection capacity and the corresponding tie switch list from the adjacent feeder bus agents corresponding to the power outage area set. Based on the available branch connection capacity and the corresponding tie switch list, the restoration strategy objective function and voltage and current constraints are constructed. The restoration strategy objective function is solved by combining the ant colony algorithm to obtain the optimized restoration strategy.

[0065] It should be noted that in the recovery strategy setting module, the recovery strategy objective function constructed is:

[0066] ;

[0067] in, is the objective function of the recovery strategy, is the weighted load restoration benefit index, is the number of tie switches obtained from the corresponding tie switch list, is the number of regions that could not be restored due to capacity limitations, and is the weight coefficient of the objective function of the recovery strategy.

[0068] It's understandable that the restoration strategy objective function constructed in this module takes into account load restoration benefits, the number of switch operations, and the number of unrestored areas. By weighting these factors, the system automatically optimizes the restoration strategy based on the grid's actual load restoration needs, operational complexity, and capacity constraints. Compared to traditional static restoration strategies, the objective function design of this invention is more flexible, capable of handling complex distribution network environments and providing more efficient and accurate restoration solutions.

[0069] It should be understood that the two weight coefficients in the restoration strategy objective function are and Different factors are given different priorities, so that the system can flexibly adjust in the recovery strategy. For example, if the current load of the power grid is high, the The weight of the grid is adjusted to give priority to the areas with larger loads. When the grid needs to reduce the number of operations, it can be adjusted To balance the number of operating switches and recovery efficiency. In addition, the ant colony algorithm is combined with the solution, so that under complex constraints, the system can search for the optimal recovery strategy in an adaptive manner, improving the automation and intelligence level of recovery decision-making.

[0070] For example, assume that the set of power-lost areas in the distribution network includes two areas: Area A (load demand 150 kW, priority weight 2) and Area B (load demand 80 kW, priority weight 1). From the tie-breaker list, the system obtains that the number of tie-breakers that need to be operated is 3, and the number of areas that cannot be restored due to capacity limitations is 1. Set the weight coefficient in the objective function of the restoration strategy and , for region A, the weighted load restoration benefit is: , for region B, the weighted load restoration benefit is: , therefore, the calculation result of the recovery strategy objective function is: Suppose the ant colony algorithm solves a new restoration strategy that restores area A to 100% load and area B to 50%. At this point, the adjusted weighted load restoration benefit is recalculated to achieve the optimal restoration strategy. The ultimate goal is to minimize the value of the restoration strategy's objective function, maximizing the weighted load restoration benefit while minimizing the number of switches operated and the number of unrestored areas. Through this intelligent solution, the system optimizes grid restoration efficiency while balancing load restoration and operational complexity.

[0071] The recovery strategy execution module is used to perform operation and maintenance recovery in a distributed manner according to the optimized recovery strategy.

[0072] It should be noted that in the recovery strategy execution module, the steps of distributed operation and maintenance recovery according to the optimized recovery strategy specifically include: sending a closing operation instruction to the tie switch in the tie switch list, and at the same time sending a partial interruptable load removal operation instruction to the adjacent feeder bus agents corresponding to the power outage area set.

[0073] As you can see, this module uses distributed control to ensure that each region's restoration strategy is executed according to real-time optimization results. During the restoration process, the distributed transmission of tie-breaker closures and load shedding commands enables coordinated restoration across the entire network. Furthermore, shedding some interruptible loads helps avoid excessive load pressure on the grid during power restoration. Especially in situations with limited capacity, appropriate load shedding can prevent grid overload and ensure stability during the restoration process.

[0074] It should be understood that the distributed execution nature of this module means that each area or each switching operation makes independent decisions locally, ensuring the system's flexibility and real-time performance. Once the recovery strategy is optimized, the system transmits recovery instructions to each relevant node via the distributed network, reducing the burden on the central control system and improving the system's response speed and processing capabilities. Furthermore, load shedding is selective; rather than simply shutting off power, it intelligently selects which areas to shed load based on load priority and the grid's actual recovery capabilities. In this way, the system not only maximizes the recovery of critical loads but also ensures that a new round of failures is not caused by overly rapid recovery or excessive load.

[0075] Embodiment 2: In addition, the present invention provides a power distribution operation and maintenance method based on smart power distribution, which adopts a power distribution operation and maintenance system based on smart power distribution in the above embodiment, and can solve a technical problem of power distribution operation and maintenance based on smart power distribution. Compared with the existing technology, the beneficial effects of the power distribution operation and maintenance method based on smart power distribution provided by the present invention are the same as the beneficial effects of the power distribution operation and maintenance system based on smart power distribution provided by the above embodiment, and the other technical features of the power distribution operation and maintenance method based on smart power distribution are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0076] Example 3: The present invention provides a power distribution operation and maintenance equipment based on smart power distribution, please refer to Figure 2A power distribution operation and maintenance device based on smart power distribution includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a power distribution operation and maintenance method based on smart power distribution in the above-mentioned embodiment 1. A power distribution operation and maintenance device based on smart power distribution in an embodiment of the present invention may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. A power distribution operation and maintenance device based on smart power distribution is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present invention. A power distribution operation and maintenance device based on smart power distribution may include a processing device 1001 (e.g., a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the power distribution operation and maintenance device based on smart power distribution. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, hard disk, etc.; and communication devices 1009. Communication devices 1009 can allow a power distribution operation and maintenance device based on smart power distribution to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a power distribution operation and maintenance device based on smart power distribution with various systems, it should be understood that implementation or presence of all the illustrated systems is not required. More or fewer systems may alternatively be implemented or present.

[0077] Example 4: The present invention also provides a computer program product, comprising a computer program. When executed by a processor, the computer program implements the steps of the above-described method for power distribution operation and maintenance based on smart power distribution. The computer program product provided by the present invention can solve the technical problem of power distribution operation and maintenance based on smart power distribution. Compared with the prior art, the beneficial effects of the computer program product provided by the present invention are the same as the beneficial effects of the power distribution operation and maintenance method based on smart power distribution provided in the above-mentioned embodiment, and are not further described here.

[0078] In particular, according to the embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present invention are performed.

[0079] It should be understood that the various parts disclosed in the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any appropriate manner in any one or more embodiments or examples.

[0080] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A power distribution operation and maintenance system based on smart power distribution, characterized in that: The system includes: The operation data acquisition module is used to collect the distribution network operation data in real time, including the node voltage set V, the branch current set E and the switch topology state set S, and build the electrical diagram model of the distribution network based on the grid operation data ; The fault area identification module is used to extract current change characteristics, voltage change characteristics and switch state characteristics from the electrical diagram model, identify the fault area based on the current change characteristics and voltage change characteristics, and automatically isolate the fault based on the switch state characteristics; The restoration benefit calculation module is used to automatically isolate the fault, detect the currently affected area, and obtain a set of power-off areas. Based on the set of power-off areas, it calculates a weighted load restoration benefit index. The restoration strategy setting module is used to obtain the available branch connection capacity and the corresponding tie switch list from the adjacent feeder bus agents corresponding to the power outage area set. Based on the available branch connection capacity and the corresponding tie switch list, the restoration strategy objective function and voltage and current constraints are constructed. The restoration strategy objective function is solved by combining the ant colony algorithm to obtain the optimized restoration strategy. The recovery strategy execution module is used to perform operation and maintenance recovery in a distributed manner according to the optimized recovery strategy.

2. A power distribution operation and maintenance system based on smart power distribution according to claim 1, characterized in that: In the operation data acquisition module, the step of collecting the distribution network operation data in real time specifically includes: setting voltage sensors, current transformers and intelligent switch sensors in the feeder lines, branch lines and section switch areas of the distribution network to collect the distribution network operation data in real time.

3. The power distribution operation and maintenance system based on smart power distribution according to claim 1, characterized in that: In the fault area identification module, the electrical diagram model The steps of extracting current change characteristics, voltage change characteristics, and switch state characteristics, identifying the fault area according to the current change characteristics and voltage change characteristics, and automatically isolating the fault based on the switch state characteristics specifically include: Preset time window T, first from the electrical diagram model The current of each branch i at time t is extracted by the time series feature extraction method ,Voltage and switch status , and then after the preset time window T, from the electrical diagram model Extract the current of each branch i at time t+T ,Voltage and switch status ; According to the current ,Voltage and switch status and current ,Voltage and switch status Calculate the current change characteristics , voltage change characteristics and switch state characteristics ; Based on the current change characteristics , voltage change characteristics and switch state characteristics Determine whether branch i has a fault within the preset time window T, and then obtain the fault area; Automatically isolate the fault area based on the switch status characteristics.

4. The power distribution operation and maintenance system based on smart power distribution according to claim 1, characterized in that: In the restoration benefit calculation module, the formula for the power outage area set is expressed as: ； in, is the set of power-off areas, is the branch j in the power-off region set, is the voltage of branch j, is the fault area; For each branch j in the power outage area set, obtain the corresponding current load demand , and introduce recovery priority weight , based on current load demand and recovery priority weights Defining weighted load restoration benefit indicators for in It is the adjustment coefficient of weighted load recovery benefit index.

5. The power distribution operation and maintenance system based on smart power distribution according to claim 1, characterized in that: In the recovery strategy setting module, the voltage and current constraints are constructed as follows: ,in, is a preset first voltage threshold, is a preset second voltage threshold, the first voltage threshold is less than the second voltage threshold; is the new voltage value after connecting to the healthy feeder, is the new current value after connecting to the healthy feeder, is a preset first current threshold.

6. The power distribution operation and maintenance system based on smart power distribution according to claim 1, characterized in that: In the recovery strategy setting module, the recovery strategy objective function is constructed as follows: ； in, is the objective function of the recovery strategy, is the weighted load restoration benefit index, is the number of tie switches obtained from the corresponding tie switch list, is the number of regions that could not be restored due to capacity limitations, and is the weight coefficient of the objective function of the recovery strategy.

7. The power distribution operation and maintenance system based on smart power distribution according to claim 1, characterized in that: In the recovery strategy execution module, the steps of distributed operation and maintenance recovery according to the optimized recovery strategy include: sending closing operation instructions to the tie switches in the tie switch list, and simultaneously sending partial interruption load removal operation instructions to the adjacent feeder bus agents corresponding to the power outage area set.

8. A power distribution operation and maintenance method based on smart power distribution, applied to a power distribution operation and maintenance system based on smart power distribution according to any one of claims 1 to 7, characterized in that: Methods include: Step S10: Real-time collection of distribution network operation data, including node voltage set V, branch current set E and switch topology state set S, and construction of the electrical diagram model of the distribution network based on the grid operation data ; Step S20: extracting current variation characteristics, voltage variation characteristics, and switch state characteristics from the electrical diagram model, identifying the fault area based on the current variation characteristics and voltage variation characteristics, and automatically isolating the fault based on the switch state characteristics; Step S30: After the fault is automatically isolated, the currently affected area is detected to obtain a set of power-off areas, and a weighted load restoration benefit index is calculated based on the set of power-off areas; Step S40: Obtain the available branch capacity and the corresponding tie switch list from the adjacent feeder bus agents corresponding to the power outage area set, construct a restoration strategy objective function and voltage and current constraints based on the available branch capacity and the corresponding tie switch list, and solve the restoration strategy objective function in combination with the ant colony algorithm to obtain an optimized restoration strategy; Step S50: Perform operation and maintenance recovery in a distributed manner according to the optimized recovery strategy.

9. A power distribution operation and maintenance device based on smart power distribution, characterized in that: The distribution operation and maintenance equipment based on smart distribution includes: a memory, a processor, and a distribution operation and maintenance program based on smart distribution stored on the memory and runnable on the processor. When the distribution operation and maintenance program based on smart distribution is executed by the processor, a distribution operation and maintenance system based on smart distribution according to any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that The computer program product includes a power distribution operation and maintenance program based on smart power distribution. When the power distribution operation and maintenance program based on smart power distribution is executed by a processor, it implements a power distribution operation and maintenance system based on smart power distribution according to any one of claims 1 to 7.

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