A long-term power grid outage strategy optimization method

Abstract

The present application relates to the field of long-term power outage strategy optimization of power grid, and particularly relates to a long-term power outage strategy optimization method of power grid, comprising: building a user-power grid interaction platform, the platform supports user access through a mobile terminal or a computer terminal, and the platform has a user terminal module, a power grid terminal module, a solution library module and a two-way feedback module; the method collects user basic information, power outage sensitive information, self-provided conditions and other key data by building the user-power grid interaction platform, realizes accurate capture of the needs of different types of users, such as fully non-power outage hospitals and short-time non-power outage shops, ensures that the power outage strategy fully considers the special power demand of users, reduces the production and life loss of users, accurately responds to the differentiated needs of users, and solves the problem of demand response loss.

Description

Technical Field

[0001] This invention relates to the field of long-term power outage strategy optimization in power grids, and specifically to a method for optimizing long-term power outage strategies in power grids. Background Technology

[0002] Current long-term power outage strategies for power grids mainly revolve around annual, quarterly, and monthly outage plans. Core technologies include integrated outage plan management, N-1 criterion-based optimization modeling, big data and forecasting technologies, GIS and SCADA system integration, and intelligent decision support systems. Integrated outage plan management follows the principle of "calculate before stopping, and use one outage for multiple purposes," merging outage needs from multiple disciplines to reduce redundant outages. N-1 criterion-based optimization modeling uses mathematical models such as mixed integer programming, combined with parameters such as power grid topology and power flow constraints, to optimize outage timing and scope. Big data and forecasting technologies utilize historical outage data, equipment status, and meteorological data to predict high-risk areas and time periods. GIS and SCADA system integration enables intuitive assessment of outage impact and formulation of power transfer schemes. Intelligent decision support systems integrate the above technologies to achieve automated generation and dynamic adjustment of outage plans.

[0003] However, existing long-term power outage strategies in the power grid have significant shortcomings: 1. Lack of response to differentiated user needs. The existing strategy focuses on the needs of power grid equipment maintenance and infrastructure renovation, without establishing an effective interaction mechanism with users. It is impossible to accurately obtain key information such as "whether power outage is allowed", "allowed power outage duration", and "sensitive periods" for users. This results in insufficient consideration of the needs of users such as hospitals, data centers, and special factories that cannot or will experience short-term power outages, which may easily lead to losses in users' production and life. 2. The disconnect between power grid data and user needs: the existing system only focuses on power grid-side data (such as line topology and load transfer capacity) and does not incorporate user-side information into the power outage strategy optimization process. Even if some user needs are obtained, the lack of a data linkage mechanism makes it impossible to achieve accurate matching between needs and power grid outage plans, which may lead to the contradiction of "users making demands but the power grid being unable to meet them". 3. The solutions lack personalization and standardization. Faced with the power outage sensitive needs of different users, the existing strategies mostly rely on manual temporary solutions without the support of a standardized solution library. This results in low implementation efficiency, poor adaptability, and a lack of post-event feedback and optimization mechanisms, making it difficult to continuously improve the rationality of power outage strategies. Summary of the Invention

[0004] In order to overcome the above-mentioned technical problems, the purpose of this invention is to provide a method for optimizing long-term power outage strategies in power grids, which solves the problem mentioned in the background art that the core defect of the existing technology is that it treats the affected users as a whole and does not build a differentiated evaluation mechanism for the differences in the electricity demand of different users.

[0005] The objective of this invention can be achieved through the following technical solutions: A method for optimizing long-term power outage strategies in a power grid includes the following steps: S1: Build a user-grid interaction platform. The platform supports users to access it via mobile phone or computer. The platform has a user terminal module, a grid terminal module, a solution library module, and a two-way feedback module. S2: Collect user information through the user terminal module. The user information includes at least basic information, power outage sensitive information, self-sufficient condition information, and emergency contact information. S3: The power grid module connects to the existing power outage planning system, GIS line topology system and load management system of the power grid, and synchronizes the long-term power outage planning data, line topology data, load transfer capacity data and backup power reserve data of the power grid. S4: The power grid module processes the user information collected in step S2 and the power grid data synchronized in step S3, and sequentially performs automatic verification, scheme matching and manual review to generate an optimized power outage scheme for the target area. S5: The power grid module pushes the optimized power outage plan to the user end, and at the same time collects the user's objections to the plan and the satisfaction evaluation after the power outage through the two-way feedback module. Based on the evaluation results, the platform algorithm and solution library are optimized.

[0006] As a further aspect of the present invention: In step S1, the user terminal module includes a registration and login unit, an information collection unit, and a demand query unit; the registration and login unit supports registration for enterprise users and individual users respectively. Enterprise users need to upload their business license and important user identification documents when registering, while individual users only need to complete real-name authentication when registering; the demand query unit allows users to query the demand review progress through a unique demand number, and the progress includes pending review, matched solution, and solution under adjustment.

[0007] As a further aspect of the present invention: In step S2, the basic information includes the user's location, electricity address, and user type. The location is accurate to the street / community / factory area, the electricity address is associated with the power grid line topology data, and the user type is divided into enterprises, individuals, and public institutions. The power outage sensitivity information includes whether a power outage is permissible, the maximum allowed power outage duration, and sensitive time periods. The maximum allowed power outage duration is divided into ≤1 hour, ≤4 hours, ≤8 hours, and completely uninterruptible. The self-sufficiency information includes whether a backup power supply is available and the sustainable power supply duration of the backup power supply. The backup power supply type includes diesel generators, energy storage devices, and photovoltaic devices.

[0008] As a further aspect of the present invention: In step S4, the automatic verification specifically involves: determining whether the user's area is within the scope of the long-term power outage plan in the power grid, and simultaneously determining whether the power outage-sensitive demand proposed by the user exceeds the power grid's carrying capacity. The power grid's carrying capacity includes the target area's line load transfer limit, the reserve of backup power, and the quantity of live-line working resources.

[0009] As a further aspect of the present invention: In step S4, the solution matching specifically involves: based on user power outage sensitivity information and grid carrying capacity data, retrieving the corresponding standardized solution from the solution library module. The solutions in the solution library module include: a "load transfer to backup line + mobile emergency power vehicle access + live-line work" solution for users who cannot experience power outages at all; a "peak-shifting power outage + rapid operation" solution for users who cannot experience power outages for short periods; a "segmented power outage + backup power supplementation" solution for users who can experience power outages but have limited duration; and a "extended load transfer duration + mobile energy storage device supplementation" solution for users who have their own power supply but insufficient endurance.

[0010] As a further aspect of the present invention: In step S4, the manual review specifically involves: performing a second confirmation on complex requirements that have passed automatic verification and whose solutions have been matched. The complex requirements include user requirements that cannot be interrupted and have no backup power supply, and conflicting requirements in areas with multiple users concentrated in one location. The grid operation and maintenance personnel confirm the feasibility of the solution based on the actual situation on site. If the solution is not feasible, it is re-matched and fed back to the user end.

[0011] As a further aspect of the present invention: In step S5, the optimized power outage scheme information pushed by the power grid module includes the scheme type, the adjusted power outage duration, the implementation time, and precautions. The precautions include the user's backup power supply startup preparation time and the emergency contact person's contact method.

[0012] As a further aspect of the present invention: in step S5, the two-way feedback module includes a user objection submission unit and a satisfaction evaluation unit; the user objection submission unit supports users to submit objections within 48 hours after receiving the solution, and the power grid end to reply with the negotiation results within 24 hours after receiving the objection; the satisfaction evaluation unit includes three evaluation dimensions: solution adaptability, accuracy of power outage duration, and communication efficiency, with each dimension scored on a 1-5 scale.

[0013] As a further aspect of the present invention: In step S5, the optimization of the platform algorithm based on the evaluation results specifically involves: statistically analyzing the distribution of user demand types in each region; if the proportion of users in a certain region who are completely unable to access power exceeds 30%, then optimizing the long-term power outage plan algorithm in the power grid and prioritizing the planning of backup lines for that region; at the same time, adjusting the matching priority of each solution in the solution library based on the user's rating of the solution, and increasing the priority of solutions with a rating higher than 4.

[0014] As a further aspect of the present invention, the platform also includes a permission management module, which sets different operation permissions for different user roles, including but not limited to enterprise administrators and individual users, and different roles on the power grid side, including but not limited to data entry personnel, operation and maintenance auditors, and solution decision-makers, to ensure data security and operational compliance.

[0015] The beneficial effects of this invention are: 1. This method establishes a user-grid interaction platform to collect key data such as user basic information, power outage sensitive information, and self-backup conditions. This enables the accurate capture of the needs of different types of users (such as hospitals that cannot be interrupted at all and shops that cannot be interrupted for short periods of time). It breaks through the limitations of the existing "one-size-fits-all" strategy, ensures that the power outage strategy fully considers the special electricity needs of users, reduces the loss of users' production and life, accurately responds to the differentiated needs of users, and solves the problem of missing demand response.

[0016] 2. The platform connects with the existing power grid outage planning system, GIS line topology system, load management system, etc., to synchronize user demand data with power grid data in real time. Through demand review and matching engine, it completes automatic verification, scheme matching and manual review, ensuring that user demand is deeply integrated with power grid outage plans, load transfer capacity, backup power reserves and other data, avoiding the contradiction of "user demand and power grid capacity being out of sync", improving the feasibility of outage strategies, realizing the linkage between power grid data and user demand, and solving the problem of data disconnection.

[0017] 3. This method pre-defines a standardized solution library covering all scenarios, matching corresponding load transfer, emergency power dispatch, and peak-shifting power outage solutions for different user needs, eliminating the need for manual ad-hoc decision-making and improving solution implementation efficiency. Simultaneously, a two-way feedback mechanism is established, continuously optimizing the matching algorithm and solution library through user satisfaction evaluations and grid-side data statistics, enabling dynamic iteration of power outage strategies, improving solution adaptability and rationality, and addressing the issues of low solution efficiency and poor adaptability by constructing a standardized solution library and feedback mechanism. Attached Figure Description

[0018] The invention will now be further described with reference to the accompanying drawings.

[0019] Figure 1 This is a flowchart of a method for optimizing long-term power outage strategies in a power grid, as described in this invention. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention. Example 1

[0021] Please see Figure 1 As shown, this embodiment is a method for optimizing long-term power outage strategies in a power grid, including the following steps: S1: Build a user-grid interaction platform. The platform supports users to access it via mobile phone or computer. The platform has a user terminal module, a grid terminal module, a solution library module, and a two-way feedback module. S2: Collect user information through the user terminal module. The user information includes at least basic information, power outage sensitive information, self-sufficient condition information, and emergency contact information. S3: The power grid module connects to the existing power outage planning system, GIS line topology system and load management system of the power grid, and synchronizes the long-term power outage planning data, line topology data, load transfer capacity data and backup power reserve data of the power grid. S4: The power grid module processes the user information collected in step S2 and the power grid data synchronized in step S3, and sequentially performs automatic verification, scheme matching and manual review to generate an optimized power outage scheme for the target area. S5: The power grid module pushes the optimized power outage plan to the user end, and at the same time collects the user's objections to the plan and the satisfaction evaluation after the power outage through the two-way feedback module. Based on the evaluation results, the platform algorithm and solution library are optimized.

[0022] In step S1, the user terminal module includes a registration and login unit, an information collection unit, and a demand query unit. The registration and login unit supports registration for enterprise users and individual users. Enterprise users need to upload their business license and important user identification documents when registering, while individual users only need to complete real-name authentication. The demand query unit allows users to query the progress of demand review by unique demand number. The progress includes pending review, matched solution, and solution adjustment.

[0023] In step S2, the basic information includes the user's location, electricity address, and user type. The location is accurate to the street / community / factory area, the electricity address is associated with the power grid line topology data, and the user type is divided into enterprises, individuals, and public institutions. The power outage sensitivity information includes whether a power outage is allowed, the maximum allowed power outage duration, and sensitive time periods. The maximum allowed power outage duration is divided into ≤1 hour, ≤4 hours, ≤8 hours, and completely uninterruptible. The self-sufficiency information includes whether a backup power source is available and the sustainable power supply duration of the backup power source. The backup power source type includes diesel generators, energy storage devices, and photovoltaic devices.

[0024] In step S4, the automatic verification specifically involves: determining whether the user's area is within the scope of the long-term power outage plan in the power grid, and at the same time determining whether the power outage sensitive demand proposed by the user exceeds the power grid's carrying capacity. The power grid's carrying capacity includes the target area's line load transfer limit, the reserve of backup power, and the number of live-line working resources.

[0025] In step S4, the solution matching specifically involves: based on user power outage sensitivity information and grid carrying capacity data, retrieving corresponding standardized solutions from the solution library module. The solutions in the solution library module include: a "load transfer to backup line + mobile emergency power vehicle access + live-line work" solution for users who cannot experience power outages at all; a "peak-shifting power outage + rapid operation" solution for users who cannot experience power outages for short periods; a "segmented power outage + backup power supplementation" solution for users who can experience power outages but have limited duration; and a "extended load transfer duration + mobile energy storage device supplementation" solution for users who have their own power supply but insufficient endurance.

[0026] In step S4, the manual review specifically involves: performing a second confirmation on complex requirements that have passed automatic verification and whose solutions have been matched. These complex requirements include user requirements that cannot be interrupted and have no backup power supply, as well as conflicting requirements in areas with multiple users. The grid maintenance personnel will confirm the feasibility of the solution based on the actual situation on site. If the solution is not feasible, it will be re-matched and fed back to the user.

[0027] In step S5, the optimized power outage plan information pushed by the power grid module includes the plan type, adjusted power outage duration, implementation time, and precautions. The precautions include the user's backup power supply startup preparation time and emergency contact person contact method.

[0028] In step S5, the two-way feedback module includes a user objection submission unit and a satisfaction evaluation unit; the user objection submission unit allows users to submit objections within 48 hours of receiving the solution, and the power grid side will reply with the negotiation results within 24 hours of receiving the objection; the satisfaction evaluation unit includes three evaluation dimensions: solution suitability, accuracy of power outage duration, and communication efficiency, with each dimension scored on a 1-5 scale.

[0029] In step S5, the optimization of the platform algorithm based on the evaluation results is specifically as follows: statistically analyze the distribution of user demand types in each region. If the proportion of users in a certain region who cannot afford to experience power outages exceeds 30%, then optimize the long-term power outage plan algorithm of the power grid and prioritize the planning of backup lines for that region. At the same time, based on the user's rating of the solution, adjust the matching priority of each solution in the solution library, and increase the priority of solutions with a rating higher than 4.

[0030] The platform also has a permission management module, which sets different operation permissions for different user roles, including but not limited to enterprise administrators and individual users, and different roles on the power grid side, including but not limited to data entry personnel, operation and maintenance auditors, and solution decision-makers, to ensure data security and operational compliance. Example 2

[0031] This example illustrates the optimization of the power grid maintenance outage plan for the second quarter of year X in region A of a certain city.

[0032] S1. Platform Setup and Initialization S11. First, establish a user-grid interaction platform, which includes a user terminal (mobile APP and web page) and a grid terminal (deployed on the grid dispatch center server). The user terminal completes the development of registration and login functions. When registering, enterprise users need to upload their business license and the "Important User Identification Document" issued by the Management Committee of Area A (if hospitals need to provide the medical institution practice license issued by the Health Commission), while individual users can be authenticated with their ID cards. The grid terminal completes the data connection with the existing power outage planning system, GIS line topology system, and load management system of the Area A power grid, and synchronizes the 10kV line maintenance plan of Area A in the second quarter of 2025 (involving 3 main lines, with the power outage period initially set for April 10-15), line topology map (marking the location of the backup tie switch of each line), load transfer capacity data (the maximum transferable load of each main line is 8000kW), and backup power reserve data (2 500kW mobile emergency power vehicles and 5 200kW mobile energy storage devices).

[0033] S2, User Information Collection S21. Users in Area A submit information through the platform's user terminal: A tertiary hospital (enterprise user) submits basic information (Location: Area A, Keyuan Road; Electricity address: No. 88 Keyuan Road; User type: Public institution), power outage sensitive information (Whether power outage is permissible: No; Maximum allowed power outage duration: Absolutely not permissible; Sensitive period: 24 hours), self-supplied conditions information (Available to have one 1000kW diesel generator, capable of providing continuous power for 4 hours), and emergency contact information (Equipment Department, Engineer Wang, Tel: 138XXXX1234); An electronics factory (enterprise user) submits information (Location: Area A, Industrial Park; Electricity address: No. 88 Keyuan Road; User type: Public institution), power outage sensitive information (Whether power outage is permissible: No; Maximum allowed power outage duration: Absolutely not permissible; Sensitive period: 24 hours), self-supplied conditions information (Available to have one 1000kW diesel generator, capable of providing continuous power for 4 hours), and emergency contact information (Equipment Department, Engineer Wang, Tel: 138XXXX1234); Address: Building 15, Industrial Park; User Type: Enterprise; Power Outage Allowed: Yes; Maximum Allowed Power Outage Duration: ≤4 hours; Sensitive Period: 8:00-18:00 (Production Period); No Backup Power Supply; Emergency Contact: Manager Li, Tel: 139XXXX4567. A resident (individual user) submitted information (Location: Yiju Community, Area A; Electricity Address: Unit 2, Building 3; User Type: Individual; Power Outage Allowed: Yes; Maximum Allowed Power Outage Duration: ≤8 hours; Sensitive Period: 18:00-22:00; No Backup Power Supply; Emergency Contact: Ms. Zhang, Tel: 137XXXX7890).

[0034] S3. Requirements Review and Solution Matching S31. The platform's power grid side determined that the hospital, electronics factory, and residential area were all within the maintenance outage range from April 10th to April 15th. The hospital's "completely uninterruptible" demand, combined with power grid data (the corresponding line's backup tie switch can transfer 9000kW of load, the hospital's average load is 6000kW, and there is one 500kW mobile emergency power vehicle available for dispatch), was determined to be within the power grid's carrying capacity. The electronics factory's demand for "≤4 hours of power outage, avoiding 8:00-18:00" could be adjusted by the power grid to 18:00-22:00, and the line load was low during this period, thus deemed feasible. The residential area's demand for "≤8 hours of power outage, avoiding 18:00-22:00" could be arranged for 9:00-17:00 on April 12th, also deemed feasible.

[0035] S32. For hospitals, retrieve the "load transfer to backup line + mobile emergency power vehicle access" solution from the solution library (before the maintenance on April 10, close the backup connection switch to transfer the hospital's load to the backup line, and dispatch a 500kW mobile emergency power vehicle to the hospital for backup to ensure no power outage during the maintenance period); for electronics factories, retrieve the "staggered power outage + rapid operation" solution (adjust the power outage period to 18:00-22:00 on April 11, arrange two work teams to coordinate, prepare maintenance materials in advance, and compress the operation time to within 4 hours); for residential areas, retrieve the "regular power outage + real-time information push" solution (the power outage period is set to 9:00-17:00 on April 12, push notification 3 days in advance, and update the operation progress every 2 hours during the power outage).

[0036] S33. The power grid maintenance personnel conducted a second review of the hospital's plan, checked the status of the backup contact switch and the dispatch route of the mobile emergency power vehicle on-site, and confirmed the plan's feasibility. The plans for the electronics factory and the residential area passed the review directly due to their simple requirements and sufficient power grid capacity.

[0037] S4. Solution Push and Feedback Optimization The power grid pushed the above solutions to the corresponding user terminals, and the hospital, electronics factory, and residential community all had no objections. From April 10th to April 12th, the maintenance of the three lines was completed sequentially. After the power outage, users submitted satisfaction evaluations through the platform: the hospital rated the solution's adaptability, the accuracy of the power outage duration, and communication efficiency as 5 points each; the electronics factory rated it 4 points (feedback that "power restoration was slightly delayed after the work was completed, and the power restoration process needs optimization"); and the residential community rated it 5 points. Based on the evaluation results, the platform optimized its solutions: "Power restoration process time control" was added to the "rapid operation" solution in the solution library; statistics showed that 25% of users in Area A were completely unable to experience power outages, and it was recommended that backup lines for the industrial park area be prioritized in the third quarter of 2025 to further improve the power grid's carrying capacity.

[0038] The above description is merely an example and illustration of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A method for optimizing long-term power outage strategies in a power grid, characterized in that, Includes the following steps: S1: Build a user-grid interaction platform. The platform supports users to access it via mobile phone or computer. The platform has a user terminal module, a grid terminal module, a solution library module, and a two-way feedback module. S2: Collect user information through the user terminal module. The user information includes at least basic information, power outage sensitive information, self-sufficient condition information, and emergency contact information. S3: The power grid module connects to the existing power outage planning system, GIS line topology system and load management system of the power grid, and synchronizes the long-term power outage planning data, line topology data, load transfer capacity data and backup power reserve data of the power grid. S4: The power grid module processes the user information collected in step S2 and the power grid data synchronized in step S3, and sequentially performs automatic verification, scheme matching and manual review to generate an optimized power outage scheme for the target area. S5: The power grid module pushes the optimized power outage plan to the user end, and at the same time collects the user's objections to the plan and the satisfaction evaluation after the power outage through the two-way feedback module. Based on the evaluation results, the platform algorithm and solution library are optimized.

2. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S1, the user terminal module includes a registration and login unit, an information collection unit, and a demand query unit. The registration and login unit supports registration for enterprise users and individual users. Enterprise users need to upload their business license and important user identification documents when registering, while individual users only need to complete real-name authentication. The demand query unit allows users to query the progress of demand review by unique demand number. The progress includes pending review, matched solution, and solution adjustment.

3. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S2, the basic information includes the user's location, electricity address, and user type. The location is accurate to the street / community / factory area, the electricity address is associated with the power grid line topology data, and the user type is divided into enterprises, individuals, and public institutions. The power outage sensitivity information includes whether a power outage is allowed, the maximum allowed power outage duration, and sensitive time periods. The maximum allowed power outage duration is divided into ≤1 hour, ≤4 hours, ≤8 hours, and completely uninterruptible. The self-sufficiency information includes whether a backup power source is available and the sustainable power supply duration of the backup power source. The backup power source type includes diesel generators, energy storage devices, and photovoltaic devices.

4. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S4, the automatic verification specifically involves: determining whether the user's area is within the scope of the long-term power outage plan in the power grid, and at the same time determining whether the power outage sensitive demand proposed by the user exceeds the power grid's carrying capacity. The power grid's carrying capacity includes the target area's line load transfer limit, the reserve of backup power, and the number of live-line working resources.

5. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S4, the solution matching specifically involves: based on user power outage sensitivity information and grid carrying capacity data, retrieving corresponding standardized solutions from the solution library module. The solutions in the solution library module include: a "load transfer to backup line + mobile emergency power vehicle access + live-line work" solution for users who cannot experience power outages at all; a "peak-shifting power outage + rapid work" solution for users who cannot experience power outages for short periods; a "segmented power outage + backup power supplementation" solution for users who can experience power outages but have limited duration; and a "extended load transfer duration + mobile energy storage device supplementation" solution for users who have their own power supply but insufficient endurance.

6. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S4, the manual review specifically involves: performing a second confirmation on complex requirements that have passed automatic verification and whose solutions have been matched. These complex requirements include user requirements that cannot be interrupted and have no backup power supply, as well as conflicting requirements in areas with multiple users. The grid maintenance personnel will confirm the feasibility of the solution based on the actual situation on site. If the solution is not feasible, it will be re-matched and fed back to the user.

7. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S5, the optimized power outage plan information pushed by the power grid module includes the plan type, adjusted power outage duration, implementation time, and precautions. The precautions include the user's backup power supply startup preparation time and emergency contact person contact method.

8. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S5, the two-way feedback module includes a user objection submission unit and a satisfaction evaluation unit; the user objection submission unit allows users to submit objections within 48 hours of receiving the solution, and the power grid side replies with the negotiation results within 24 hours of receiving the objection. The satisfaction evaluation unit includes three evaluation dimensions: solution adaptability, accuracy of power outage duration, and communication efficiency. Each dimension is scored on a scale of 1 to 5.

9. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, In step S5, the optimization of the platform algorithm based on the evaluation results is specifically as follows: statistically analyze the distribution of user demand types in each region. If the proportion of users in a certain region who cannot afford to experience power outages exceeds 30%, then optimize the long-term power outage plan algorithm of the power grid and prioritize the planning of backup lines for that region. At the same time, based on the user's rating of the solution, adjust the matching priority of each solution in the solution library, and increase the priority of solutions with a rating higher than 4.

10. The method for optimizing long-term power outage strategies in a power grid according to claim 1, characterized in that, The platform also has a permission management module, which sets different operation permissions for different user roles, including but not limited to enterprise administrators and individual users, and different roles on the power grid side, including but not limited to data entry personnel, operation and maintenance auditors, and solution decision-makers, to ensure data security and operational compliance.

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