摘要
高比例新能源并网使配电网涌现出潮流复杂、轻重载等问题。智能软开关(Soft open point,SOP)的出现逐渐改变了传统配电网的规划布局。新型配电网出现的SOP选址定容问题和配电网最优潮流问题亟需解决。提出了新型配电网的SOP定容选址方法和柔性互联配电网优化调控策略。首先分析了SOP接入后配电网运行特性,对基于损耗灵敏度的SOP选址方法进行了改进;然后使用粒子群算法确定SOP最佳容量配置,并以全天运行损耗成本最低为目标,通过MATLAB的GUROBI求解器得出各分布式电源和SOP的出力大小,实现最优潮流;最后以IEEE 33节点算例对所提方法进行仿真验证。结果表明,所提的配电网调控策略比传统方法更具有优势,可大幅度降低配电网网损,提高配电网新能源消纳。
High proportion of new energy grid makes the problems of complex power flow,light and heavy load appear in the distribution network.The appearance of intelligent soft open point(SOP)has gradually changed the planning and layout of traditional distribution network.The SOP location selection and capacity determination problem and optimal power flow problem in the new distribution network need to be solved urgently.This paper presents a SOP method for capacity determination and location selection of new distribution network and optimal control strategy of flexible interconnected distribution network.Firstly,the distribution network operation characteristics after SOP access are analysed,and the method of SOP location selection based on loss sensitivity is improved;then,the particle swarm optimization algorithm is used to determine the optimal capacity configuration of SOP,with the goal of minimizing the cost of operating losses throughout the day.The optimal power flow is achieved by calculating the output of each distributed power supply and SOP by the GUROBI slover of MATLAB.Finally,an IEEE 33 node example is used to simulate and validate the proposed method.The results show that the proposed control strategy has more advantages than the traditional method,which can greatly reduce the loss of distribution network and improve the new energy consumption of distribution network.
作者
李超
郝正航
LI Chao;HAO Zhenghang(College of Electrical Engineering,Guizhou University,Guiyang 550025,China)
出处
《电力科学与工程》
2023年第9期1-9,共9页
Electric Power Science and Engineering
基金
教育部第二批国家级新工科研究与实践项目(E-NYDQHGC 20202227)。
关键词
新型配电网
智能软开关
粒子群算法
最优潮流
定容选址
new distribution network
soft open point
particle swarm optimization
optimal power flow
capacity determination and location selection
