Optimization Of Active Distribution Networks With Distributed Energy Resources

In response to the "dual-carbon" policy and to achieve efficient energy utilization,the scale of Distributed Generation(DG)in the power system is constantly expanding.At the same time,the large-scale integration of DG into the distribution network is both a challenge and an opportunity.To better accommodate DG,it is necessary to plan and construct it,strengthen the coordination and interaction between sources,networks and loads,and tap the potential for regulation from all aspects.On the grid side,the intelligent Soft Open Point(SOP)can control the feeder flow,and on the load side,Demand Response(DR)can change the load distribution,both of which are effective measures to optimize the performance of the distribution network.Therefore,this article proposes the use of SOP configuration and demand response to optimize active distribution networks with distributed energy sources.Specifically,it includes the following:Firstly,a mathematical model is constructed for the distribution network,DG,SOP,and demand response.Since the model is nonlinear,variable substitution and second-order cone transformation are performed for subsequent solution.Secondly,based on the model,the impact of adding SOP and DR to the distribution network on operating parameters is studied.The effects of different configurations of DG on the network are analyzed to plan for their location and capacity.The impact of SOP and DR on DG site selection and capacity is studied.Finally,simulation analysis is carried out on the IEEE 33 network to lay the foundation for subsequent joint planning.Thirdly,considering the above factors,a coordinated planning model for DG with DR and SOP is constructed.The model aims to minimize the comprehensive cost and rationally plan the access location and capacity of DG and SOP.The model uses a combination of simulated annealing and second-order cone programming algorithms,and is solved in two layers:internal and external.First,the simulated annealing algorithm is used in the external layer to solve the position of SOP,and then the result is passed to the internal layer for second-order cone programming solution.This paper uses the IEEE 33-node example to simulate the proposed method and verifies that the planned results can minimize the system operating costs while ensuring the balance and stable operation of the power system.