Method for assisting coordinated recovery of multi-voltage-class power distribution network

Abstract

The invention discloses a method for assisting coordinated recovery of a multi-voltage-class power distribution network. The method comprises the following steps: step 1, constructing a multi-port SOP topology feasible set and initializing parameters; step 2, fault detection and power failure area division; step 3, switching a multi-port SOP control mode and formulating a collaborative strategy; 4, establishing a recovery optimization model considering the uncertainty of the source load; 5, solving a recovery strategy based on convex difference planning; step 6, executing a recovery strategy and monitoring a system state in real time; and step 7, evaluating a recovery effect and updating the emergency scheme set. According to the method for assisting the coordinated recovery of the multi-voltage-class power distribution network, by virtue of the multi-voltage-class adaptation capability and the flexible power regulation characteristic, the voltage support requirement after a fault is quickly responded, and the problems of multi-voltage-class regulation disjunction, line overload and the like in a traditional recovery scheme are effectively solved; and reliable guarantee is provided for safe, efficient and economic recovery of the multi-voltage-class power distribution network in a high-proportion new energy and novel load access scene.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, in particular to a method for assisting coordinated recovery of multi-voltage level distribution network. BACKGROUND

[0002] With the continuous increase of the penetration rate of new types of sources and loads such as distributed power sources (such as photovoltaic and wind power) and electric vehicles in distribution networks, distribution networks gradually transform from traditional passive networks to active distribution networks with multi-voltage level coordination. However, this transformation also brings significant operational challenges. On the one hand, the intermittency and volatility of distributed power output and the spatio-temporal uncertainty of electric vehicle charging load can easily lead to problems such as voltage out-of-limit and line overload in distribution networks. In particular, in the multi-voltage level (such as high voltage 110kV, medium voltage 10kV, and low voltage 0.4kV) hierarchical associated distribution network structure, single voltage level control measures cannot take into account the overall operational safety. The traditional recovery scheme relying on mechanical switches and conventional transformers has slow response speed and low control precision, and cannot meet the demand for rapid recovery after failure. On the other hand, the recovery process after the failure of the distribution network involves multi-device coordination (such as voltage regulation devices and reactive power compensation devices) and multi-objective balancing (such as load recovery rate, network loss control, and economy). Traditional recovery schemes often lack consideration of the associated characteristics of multi-voltage level distribution network topology and are difficult to effectively deal with the recovery risks brought by source and load uncertainty, resulting in low recovery efficiency, insufficient protection of important loads, and even secondary failure, which affects the overall resilience of the distribution network.

[0003] To improve the operational flexibility and fault recovery capability of distribution networks, flexible power electronic devices represented by soft switches (SOP) are gradually applied to the regulation and control of distribution networks. SOP has characteristics such as fast power regulation, multi-port interconnection, and precise voltage support, and can replace traditional tie switches to realize flexible interconnection of multi-voltage level distribution networks. In the process of fault recovery, SOP can quickly switch control modes, provide reactive power support and power transfer, and provide a technical basis for coordinated recovery of multi-voltage level distribution networks. However, existing SOP-based distribution network recovery technologies still have some deficiencies. Some schemes only focus on the application of SOP in a single voltage level and do not fully consider the hierarchical adaptability and coordinated control requirements of multi-voltage level distribution networks. Some schemes do not systematically integrate source and load uncertainty handling mechanisms, and the adaptability and reliability of the recovery strategy are limited. At the same time, the topology design, parameter configuration, and optimization solution of SOP lack deep integration with the operational constraints and economic objectives of multi-voltage level distribution networks, making it difficult to achieve cost optimization while ensuring recovery safety. These problems restrict the further improvement of the coordinated recovery level of multi-voltage level distribution networks. SUMMARY

[0004] The application aims to provide a method for assisting coordinated recovery of multi-voltage level distribution networks, to solve the problems of slow response, low control precision, and inability to meet the requirements of fast coordinated recovery of multi-voltage level distribution networks after failure, and difficulty in coping with source-load uncertainty caused by distributed power and electric vehicles in the prior art.

[0005] To achieve the above-mentioned purpose, the application provides the following technical scheme: a method for assisting coordinated recovery of multi-voltage level distribution networks, comprising the following steps: Step one: constructing a multi-port SOP topology feasible set and initializing parameters; Step two: fault detection and division of power failure areas; Step three: switching multi-port SOP control mode and formulating a coordinated strategy; Step four: establishing a recovery optimization model considering source-load uncertainty; Step five: solving the recovery strategy based on convex difference programming; Step six: executing the recovery strategy and real-time monitoring of system state; Step seven: evaluating the recovery effect and updating the emergency scheme set; In step one, based on the line parameters, transformer rated capacity, distributed power (DG) and electric vehicle (EV) access location and capacity information of multi-voltage level distribution networks (including high voltage such as 110kV, medium voltage such as 10kV, and low voltage such as 0.4kV), the candidate installation ports of each voltage level SOP are determined, such as the 10kV medium voltage feeder interconnection point and the 0.4kV low voltage transformer area contact point, to form a SOP topology feasible set, and the SOP technical parameters are initialized, the upper limit of AC-DC converter capacity, the loss coefficient of DC-DC converter, the safe range (such as 0.1-0.9) and the initial value (such as 0.5) of the state of charge (SOC) of the energy storage battery are determined, and the operating constraint thresholds such as the voltage safety interval (high voltage ±5%, medium and low voltage ±7%) and the line load rate upper limit (such as 80%) are set, to ensure that the SOP meets the interconnection requirements of different voltage level distribution networks.

[0006] Preferably, in step two, the fault location is completed with the help of distribution network automation system (such as pilot protection and circuit breaker state monitoring), after the fault line is isolated, the power failure node set of each voltage level is identified according to the node association matrix, for example, when the 10kV line has a permanent fault, the corresponding medium voltage and low voltage power failure node range is determined after isolation, the active and reactive load shortage of each power failure area is synchronously counted, and the power failure range of different voltage levels is accurately defined in combination with the topology association characteristics of multi-voltage level distribution networks, and the island area (such as industrial transformer area containing energy storage) formed by DG is excluded.

[0007] Preferably, in step three, based on the location relationship between the power outage area and the SOP port, if only one end of the SOP is located in the power outage area, the SOP control mode is switched from the normal operation mode "PQ-UdcQ" to the recovery mode "Uacθ-UdcQ". That is, one side of the converter maintains the DC bus voltage stability, while the other side provides voltage and frequency support for the power outage area. For overlapping power outage areas covered by multiple SOPs, a collaborative strategy is formulated, allowing only a single SOP terminal to provide voltage support, while the remaining SOPs are assisted in recovery through power flow transfer, avoiding multi-terminal voltage support conflicts and overload risks caused by power flow loops.

[0008] Preferably, in step four, typical source-load scenarios are generated based on K-means clustering (such as multiple scenarios covering extreme operating conditions such as DG output peak and EV charging peak). Box-type uncertainty sets are used to describe the probability fluctuation of the scenarios (such as ±15%). With the goal of "maximizing the recovery load rate (prioritizing the recovery of important loads such as medical and industrial loads, and setting corresponding weight coefficients) + minimizing network loss and over-limit penalties", a mixed integer second-order cone programming (MISOCP) model is constructed. The model constraints include SOP power transmission limit, transformer backfeed power limit (such as ≤80% rated capacity), node voltage and line current safety constraints.

[0009] Preferably, in step five, the non-convex power flow constraint is first transformed into a convex constraint through second-order cone relaxation. If the cone constraint deviation of the initial solution (e.g., the power flow equation deviation exceeds a preset accuracy threshold) does not meet the requirements, a quadratic convex function (e.g., the line power loss deviation function) and a penalty term (with a set penalty coefficient growth rate, such as 2) are introduced. Iterative optimization is performed until the deviation converges to an allowable range (e.g., <1×10⁻⁻⁶). 7 It outputs active and reactive power dispatching instructions and network reconfiguration schemes for each SOP (such as closing the low-voltage distribution area interconnection switch) to ensure the accuracy and efficiency of the solution.

[0010] Preferably, in step six, the SOP action is controlled based on the solution results, such as adjusting the converter output and controlling the charging and discharging of energy storage. The voltage, line current, and output data of DG and EV at each node are collected in real time through the phasor measurement unit (PMU), with a sampling frequency of not less than 1 second. If a voltage over-limit is detected (such as low-voltage node voltage < 0.95 pu) or line overload, a local adjustment is triggered (such as increasing the reactive power compensation of SOP). An incremental control strategy is adopted for voltage over-limit adjustment, and the adjustment amount does not exceed 5% of the reactive power capacity of SOP each time to avoid voltage oscillation. When the SOC of SOP energy storage is detected to be lower than 0.1 or higher than 0.9, the charging and discharging switch is triggered. If SOC < 0.1, the discharge is stopped and the excess active power of DG is absorbed first.

[0011] Preferably, in step seven, the load recovery rate (e.g., 100% recovery of critical loads, total load recovery rate > 95%), network loss reduction, and voltage qualification rate after the recovery is completed are statistically analyzed. The recovery strategy for this fault is incorporated into the emergency plan set. The update cycle of the emergency plan set matches the frequency of system status changes. When the installed capacity of DG increases by more than 15% or the EV charging load penetration rate increases by more than 10%, steps one to six are re-executed. The recovery effect evaluation should also include economic indicators, such as the SOP investment cost recovery period (e.g., 14.29 years) and CO2 emission reduction (e.g., a reduction of 26.23% compared to traditional solutions), to ensure that the recovery strategy takes into account both safety and economy.

[0012] Preferably, in the entire coordinated restoration process, each step revolves around the hierarchical correlation characteristics of multi-voltage level distribution networks and the flexible control capability of SOPs. Among them, the construction of topology feasible sets of SOPs, the switching of control modes and the formulation of collaborative strategies, the design of multi-voltage level adaptability and economic evaluation, and finally form a coordinated restoration scheme that covers the entire process of "equipment-model-strategy-execution-evaluation" and is adapted to multi-voltage level distribution networks.

[0013] Compared with existing technologies, the beneficial effects of this invention are as follows: Using a multi-port SOP as the core control device, leveraging its multi-voltage level adaptability and flexible power regulation characteristics, it can achieve coordinated interconnection of high-voltage, medium-voltage, and low-voltage distribution networks, rapidly responding to voltage support needs after a fault. It effectively solves problems such as multi-voltage level control disconnection, voltage exceeding limits, and line overload in traditional restoration schemes, ensuring power supply stability during distribution network restoration. Through precise fault detection and outage area delineation, combined with source-load uncertainty modeling and optimization, it can accurately address distribution network fluctuations caused by distributed power sources and electric vehicle access, improving the adaptability of the restoration strategy to complex operating conditions and ensuring the stability of power supply during restoration. Prioritizing load restoration and minimizing the impact of power outages on people's livelihoods and industrial production, economic considerations should be integrated into the entire restoration process. By designing a reasonable Standard Operating Procedure (SOP) topology, initializing parameters, and evaluating restoration effectiveness, SOP investment costs can be reduced, the cost recovery cycle can be shortened, and distribution network operation losses and carbon emissions can be reduced, balancing environmental and economic benefits. Relying on real-time status monitoring and a dynamic update mechanism for emergency solutions, the risk of secondary faults during the restoration process can be avoided in a timely manner, improving the efficiency of distribution network fault restoration and further enhancing the overall operational resilience of the distribution network. This provides a reliable guarantee for the safe, efficient, and economical restoration of multi-voltage level distribution networks in scenarios with a high proportion of new energy and new load access. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the steps of the present invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Please see Figure 1 This invention provides a technical solution: a method for assisting in the coordinated restoration of multi-voltage level distribution networks, comprising the following steps: Step 1: Construct a multi-port SOP topology feasible set and initialize parameters; Step 2: Fault detection and delineation of power outage areas; Step 3: Switch to multi-port SOP control mode and formulate a coordination strategy; Step 4: Establish a recovery optimization model that considers the uncertainty of the source load; Step 5: Solve the recovery strategy based on convexity programming; Step Six: Execute the recovery strategy and monitor the system status in real time; Step 7: Assess the recovery effectiveness and update the contingency plan set; In step one, based on the line parameters, transformer rated capacity, and the access location and capacity information of distributed generation (DG) and electric vehicles (EV) in the multi-voltage distribution network (including high voltage such as 110kV, medium voltage such as 10kV, and low voltage such as 0.4kV), candidate installation ports for SOPs at each voltage level are determined, such as the interconnection point of the 10kV medium voltage feeder and the connection point of the 0.4kV low voltage transformer area, forming a feasible set of SOP topologies. At the same time, the SOP technical parameters are initialized, clarifying the upper limit of AC-DC converter capacity, the loss coefficient of DC-DC converter, the safe range (e.g., 0.1-0.9) and initial value (e.g., 0.5) of the state of charge (SOC) of the energy storage battery, and setting the voltage safety range (high voltage ±5%, medium and low voltage ±7%) and the upper limit of line load rate (e.g., 80%) for each voltage level, to ensure that the SOP is adapted to the interconnection needs of distribution networks at different voltage levels.

[0017] In step two, fault location is completed with the help of distribution network automation systems (such as test protection and circuit breaker status monitoring). After isolating the faulty line, the set of outage nodes at each voltage level is identified based on the node association matrix. For example, when a permanent fault occurs on a 10kV line, the corresponding medium-voltage and low-voltage outage node ranges are determined after isolation. The active and reactive load deficits of each outage area are statistically analyzed. Combined with the topological association characteristics of multi-voltage distribution networks, the outage ranges of different voltage levels are accurately defined, excluding isolated areas that have formed microgrids through DG (such as industrial distribution areas with energy storage).

[0018] In step three, based on the location relationship between the power outage area and the SOP port, if only one end of the SOP is located in the power outage area, the SOP control mode is switched from the normal operation mode "PQ-UdcQ" to the recovery mode "Uacθ-UdcQ". That is, one side of the converter maintains the DC bus voltage stability, while the other side provides voltage and frequency support for the power outage area. For overlapping power outage areas covered by multiple SOPs, a collaborative strategy is formulated, allowing only a single SOP terminal to provide voltage support, while the remaining SOPs assist in recovery through power flow transfer, avoiding multi-terminal voltage support conflicts and overload risks caused by power flow loops.

[0019] In step four, typical source-load scenarios are generated based on K-means clustering (such as multiple scenarios covering extreme operating conditions such as DG output peak and EV charging peak). Box-type uncertainty sets are used to describe the probability fluctuation of the scenarios (such as ±15%). With the goal of "maximizing the recovery load rate (prioritizing the recovery of important loads such as medical and industrial loads and setting corresponding weight coefficients) + minimizing network loss and over-limit penalties", a mixed integer second-order cone programming (MISOCP) model is constructed. The model constraints include SOP power transmission limit, transformer backfeed power limit (such as ≤80% rated capacity), node voltage and line current safety constraints.

[0020] In step five, the non-convex power flow constraint is first transformed into a convex constraint through second-order cone relaxation. If the cone constraint deviation of the initial solution (e.g., the power flow equation deviation exceeds the preset accuracy threshold) does not meet the requirements, a quadratic convex function (e.g., the line power loss deviation function) and a penalty term (with a set penalty coefficient growth rate, such as 2) are introduced. Iterative optimization is performed until the deviation converges to the allowable range (e.g., <1×10⁻). 7 It outputs active and reactive power dispatching instructions and network reconfiguration schemes for each SOP (such as closing the low-voltage distribution area interconnection switch) to ensure the accuracy and efficiency of the solution.

[0021] In step six, the SOP action is controlled based on the solution results, such as adjusting the converter output and controlling the charging and discharging of energy storage. The voltage, line current, and output data of DG and EV at each node are collected in real time through the phasor measurement unit (PMU), with a sampling frequency of not less than 1 second. If voltage over-limit is detected (e.g., low-voltage node voltage < 0.95 pu) or line overload, local adjustment is triggered (e.g., increasing the reactive power compensation of SOP). An incremental control strategy is adopted for voltage over-limit adjustment, and the adjustment amount does not exceed 5% of the reactive power capacity of SOP each time to avoid voltage oscillation. When the SOC of SOP energy storage is detected to be lower than 0.1 or higher than 0.9, the charging and discharging switch is triggered. If SOC < 0.1, the discharge is stopped and the excess active power of DG is absorbed first.

[0022] In step seven, the load recovery rate (e.g., 100% recovery of critical loads, total load recovery rate > 95%), network loss reduction, and voltage qualification rate are statistically analyzed after the recovery is completed. The recovery strategy for this fault is incorporated into the emergency plan set. The update cycle of the emergency plan set matches the frequency of system status changes. When the installed capacity of DG increases by more than 15% or the EV charging load penetration rate increases by more than 10%, steps one to six are repeated. The recovery effect evaluation should also include economic indicators, such as the SOP investment cost payback period (e.g., 14.29 years) and CO2 emission reduction (e.g., a reduction of 26.23% compared to traditional solutions), to ensure that the recovery strategy takes into account both safety and economy.

[0023] Throughout the coordinated restoration process, each step revolves around the hierarchical interconnectivity of multi-voltage level distribution networks and the flexible control capabilities of Standard Operating Procedures (SOPs). This includes the construction of feasible topology sets for SOPs, control mode switching, and the formulation of collaborative strategies; multi-voltage level adaptability design; and economic evaluation. Ultimately, this results in a coordinated restoration solution covering the entire process from "equipment-model-strategy-execution-evaluation," adapting to multi-voltage level distribution networks. Using multi-port SOPs as the core control equipment, their multi-voltage level adaptability and flexible power regulation characteristics enable coordinated interconnection of high-voltage, medium-voltage, and low-voltage distribution networks. This allows for rapid response to voltage support needs after a fault, effectively solving problems such as multi-voltage level control disconnection, voltage exceeding limits, and line overload in traditional restoration solutions. It ensures power supply stability during distribution network restoration through precise fault detection and outage area delineation, combined with uncertain source-load conditions. The system employs robust modeling and optimization to accurately address distribution network fluctuations caused by distributed power sources and electric vehicle integration. This enhances the adaptability of recovery strategies to complex operating conditions, ensures priority restoration of critical loads during the recovery process, reduces the impact of power outages on people's livelihoods and industrial production, and incorporates economic considerations throughout the entire recovery process. Through reasonable SOP topology design, parameter initialization, and recovery effect evaluation, it can reduce SOP investment costs, shorten the cost recovery cycle, and simultaneously reduce distribution network operating losses and carbon emissions, balancing environmental and economic benefits. Relying on real-time status monitoring and a dynamic update mechanism for emergency solution sets, it can promptly avoid secondary fault risks during the recovery process, improve distribution network fault recovery efficiency, and further enhance the overall operational resilience of the distribution network. This provides a reliable guarantee for the safe, efficient, and economical recovery of multi-voltage level distribution networks in scenarios with a high proportion of new energy sources and new load integration.

[0024] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for assisted coordinated restoration of multi-voltage level distribution networks, characterized in that: Includes the following steps: Step 1: Construct a multi-port SOP topology feasible set and initialize parameters; Step 2: Fault detection and delineation of power outage areas; Step 3: Switch to multi-port SOP control mode and formulate a coordination strategy; Step 4: Establish a recovery optimization model that considers the uncertainty of the source load; Step 5: Solve the recovery strategy based on convexity programming; Step Six: Execute the recovery strategy and monitor the system status in real time; Step 7: Assess the recovery effectiveness and update the contingency plan set; In step one, based on the line parameters, transformer rated capacity, and the access location and capacity information of distributed generation (DG) and electric vehicles (EV) in the multi-voltage distribution network (including high voltage such as 110kV, medium voltage such as 10kV, and low voltage such as 0.4kV), candidate installation ports for SOPs at each voltage level are determined, such as the interconnection point of the 10kV medium voltage feeder and the connection point of the 0.4kV low voltage transformer area, forming a feasible set of SOP topologies. At the same time, the SOP technical parameters are initialized, clarifying the upper limit of AC-DC converter capacity, the loss coefficient of DC-DC converter, the safe range (e.g., 0.1-0.9) and initial value (e.g., 0.5) of the state of charge (SOC) of the energy storage battery, and setting the voltage safety range (high voltage ±5%, medium and low voltage ±7%) and the upper limit of line load rate (e.g., 80%) for each voltage level, to ensure that the SOP is adapted to the interconnection needs of distribution networks at different voltage levels.

2. The method for assisted coordinated restoration of multi-voltage level distribution networks according to claim 1, characterized in that: In step two, fault location is completed with the help of distribution network automation systems (such as test protection and circuit breaker status monitoring). After isolating the faulty line, the set of outage nodes at each voltage level is identified based on the node association matrix. For example, when a permanent fault occurs on a 10kV line, the corresponding medium-voltage and low-voltage outage node ranges are determined after isolation. The active and reactive load deficits of each outage area are statistically analyzed. Combined with the topological association characteristics of multi-voltage distribution networks, the outage ranges of different voltage levels are accurately defined, excluding isolated areas that have formed microgrids through DG (such as industrial distribution areas with energy storage).

3. The method for assisted coordinated restoration of multi-voltage level distribution networks according to claim 1, characterized in that: In step three, based on the location relationship between the power outage area and the SOP port, if only one end of the SOP is located in the power outage area, the SOP control mode is switched from the normal operation mode "PQ-UdcQ" to the recovery mode "Uacθ-UdcQ". That is, one side of the converter maintains the DC bus voltage stability, while the other side provides voltage and frequency support for the power outage area. For overlapping power outage areas covered by multiple SOPs, a coordination strategy is formulated, allowing only a single SOP terminal to provide voltage support, while the remaining SOPs assist in recovery through power flow transfer, avoiding multi-terminal voltage support conflicts and overload risks caused by power flow loops.

4. The method for assisted coordinated restoration of multi-voltage level distribution networks according to claim 1, characterized in that: In step four, typical source-load scenarios are generated based on K-means clustering (such as multiple scenarios covering extreme operating conditions such as DG output peak and EV charging peak). Box-type uncertainty sets are used to describe the probability fluctuation of the scenarios (such as ±15%). With the goal of "maximizing the recovery load rate (prioritizing the recovery of important loads such as medical and industrial loads and setting corresponding weight coefficients) + minimizing network loss and over-limit penalties", a mixed integer second-order cone programming (MISOCP) model is constructed. The model constraints include SOP power transmission limit, transformer backfeed power limit (such as ≤80% rated capacity), node voltage and line current safety constraints.

5. The method for assisted coordinated restoration of multi-voltage level distribution networks according to claim 1, characterized in that: In step five, the non-convex power flow constraint is first transformed into a convex constraint through second-order cone relaxation. If the cone constraint deviation of the initial solution (e.g., the power flow equation deviation exceeds the preset accuracy threshold) does not meet the requirements, a quadratic convex function (e.g., the line power loss deviation function) and a penalty term (with a set penalty coefficient growth rate, such as 2) are introduced. Iterative optimization is performed until the deviation converges to the allowable range (e.g., <1×10⁻). 7 It outputs active and reactive power dispatching instructions and network reconfiguration schemes for each SOP (such as closing the low-voltage distribution area interconnection switch) to ensure the accuracy and efficiency of the solution.

6. The method for assisted coordinated restoration of multi-voltage level distribution networks according to claim 1, characterized in that: In step six, the SOP action is controlled based on the solution results, such as adjusting the converter output and controlling the charging and discharging of energy storage. The voltage, line current, and output data of DG and EV at each node are collected in real time through the phasor measurement unit (PMU), with a sampling frequency of not less than 1 second. If voltage over-limit is detected (e.g., low-voltage node voltage < 0.95 pu) or line overload, local adjustment is triggered (e.g., increasing the reactive power compensation of SOP). An incremental control strategy is adopted for voltage over-limit adjustment, and the adjustment amount does not exceed 5% of the reactive power capacity of SOP each time to avoid voltage oscillation. When the SOC of SOP energy storage is detected to be lower than 0.1 or higher than 0.9, the charging and discharging switch is triggered. If SOC < 0.1, the discharge is stopped and the excess active power of DG is absorbed first.

7. The method for assisted coordinated restoration of multi-voltage level distribution networks according to claim 1, characterized in that: In step seven, the load recovery rate (e.g., 100% recovery of critical loads, total load recovery rate > 95%), network loss reduction, and voltage qualification rate are statistically analyzed after the recovery is completed. The recovery strategy for this fault is incorporated into the emergency plan set. The update cycle of the emergency plan set matches the frequency of system status changes. When the installed capacity of DG increases by more than 15% or the EV charging load penetration rate increases by more than 10%, steps one to six are repeated. The recovery effect evaluation should also include economic indicators, such as the SOP investment cost payback period (e.g., 14.29 years) and CO2 emission reduction (e.g., a reduction of 26.23% compared to traditional solutions), to ensure that the recovery strategy takes into account both safety and economy.

8. The method for assisted coordinated restoration of multi-voltage level distribution networks according to claim 1, characterized in that: Throughout the entire coordinated restoration process, each step revolves around the hierarchical correlation characteristics of multi-voltage level distribution networks and the flexible control capabilities of Standard Operating Procedures (SOPs). This includes the construction of topology feasible sets for SOPs, the switching of control modes and the formulation of collaborative strategies, the design of multi-voltage level adaptability and economic evaluation, ultimately forming a coordinated restoration solution that covers the entire process of "equipment-model-strategy-execution-evaluation" and is adaptable to multi-voltage level distribution networks.

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