Research On Optimization Decision Of Load Recovery After Power Outage

The ultimate goal of power system restoration after power outage is to restore power supply to users as soon as possible and reduce power outage loss.This paper studies the large-scale load recovery in power system restoration,considers the requirement of load recovery,and puts forward the optimization decision of system stability index.Finally,the combination optimization problem of single-time multi-load point restoration is considered.(1)In this paper,the system voltage is gradually changed from controllable to uncontrollable instability mechanism in the process of system recovery through theoretical analysis,and safety indexes affecting the direction of subsequent load recovery loading are extracted.The simulation results show that different load loading directions have different effects on system security.(2)In order to ensure that the system is in the fastest direction of load recovery under the premise of security and stability,the voltage changes and system stability levels of the system nodes are incorporated into the objective functions,and multiple target functions including load weighted recovery,node voltage changes,and system stability levels are proposed.The constraints such as unit output and trend are taken into account.A multi-objective load recovery model with security considerations was established,and the Pareto optimal solution set was solved by an improved NSGA-II fast non-dominant sorting genetic algorithm with an elite strategy(Non-dominated Sorting Generational Algorith-II);Then,the optimal solution sorting method based on fuzzy anti-entropy weight is used to determine the most satisfactory recovery scheme.(3)According to the problem of load recovery after power outage,a recovery strategy that considers the participation of wind power is proposed;At the same time,in order to deal with the uncertainty of wind power,the wind power output is expressed in interval form,and a robust optimization model with the goal of maximizing recovery benefits and load loss risk is proposed.It is applied to the combined problem of multi-load line recovery in a single step and optimized by genetic algorithm to obtain a quantitative load recovery scheme that combines recovery efficiency and operational safety.