Research On Distribution Network Service Restoration Method Considering Stochasticity Of Distributed Generators

In recent years,the frequent occurrence of major blackouts worldwide has caused huge economic losses to society.Improving the service restoration capability of the distribution network after a major power outage is an important measure to improve national risk prevention capabilities and emergency preparedness mechanisms,and is of great significance to national energy security.After a major power outage occurs,the transmission facilities may be damaged,often failing to deliver electrical energy to the distribution network in a timely manner.However,with the continuous access of distributed generators(DGs),the comprehensive utilization of DGs to restore loads in the distribution network provides an opportunity for emergency service restoration.However,while using intermittent energy sources such as wind power and photovoltaics to recover more loads,the impact of the stochasticity of intermittent energy sources power output on service restoration of the distribution network cannot be ignored.Therefore,this paper will focus on the load restoration strategy of distribution networks that consider the stochasticity of DGs' power output.The main research contents of this article are as follows:First,the distribution network load restoration strategy considering the stochasticity of DGs' power output is proposed.Based on multi-source coordinated distribution network load restoration,the distribution network restoration problem considering the stochasticity of distributed power output is explained.A Gaussian mixture model(GMM)considering the temporal and spatial correlation of intermittent energy sources power output is proposed to achieve unified modeling of intermittent energy sources power output.The results show that the GMM has a good approximate fitting effect on intermittent energy sources power output,and also reflects the spatio-temporal correlation of their power outputs.The influence of the intermittent energy sources on the load restoration of the distribution network is analyzed,which lays the foundation for the subsequent establishment of the load restoration model of the distribution network.Then,a stochastic optimization model for distribution network load restoration with chance constraints is proposed.Considering the impact of the stochasticity of intermittent energy sources power output,chance constraints are used to describe voltage amplitude constraints,and voltage to meet amplitude limit constraints at certain confidence levels is allowed.Chance constraints are processed using the sample average approximation method,and the stochastic optimization model is approximately transformed into a deterministic mixed-integer second-order cone programming model.The results of case studies show that the proposed model can effectively reflect the impact of the stochasticity of intermittent energy sources power output on the load restoration of the distribution network,and cooperate with DGs to achieve the goal of restoring as many critical loads as possible.Finally,a two-stage stochastic optimization model for multi-period distribution network load restoration is proposed.In the first stage,the scheduled output of dispatchable DGs,status of loads,and status of lines are determined based on the predicted power ouputs of intermittent energy sources in each period.In the second stage,the power output of dispatchable DGs is adjusted under the uncertainties in intermittent energy sources power generation.Based on the scenario analysis method,the stochastic programming problem is approximately transformed into a deterministic two-stage mixed integer programming problem.The Benders decomposition algorithm is used to solve the deterministic programming problem.The case studies show that the proposed model can not only restore as many critical loads as possible,but also effectively reduce the times of load shedding.