基于网络流的含分布式电源配电网两阶段规划  

A Flow Based Two-stage Scheme on Distribution Network Planning with Distributed Generation

作　　者：张皓然[1] 顾洁[1] 方陈[2] 

机构地区：[1]上海交通大学电力传输与功率变换控制教育部重点实验室,上海200240 [2]国网上海市电力公司电力科学研究院,上海200437

出　　处：《中国电力》2015年第9期31-37,共7页Electric Power

基　　金：国家科技支撑计划-以大规模可再生能源利用为特征的智能电网综合示范工程资助项目(2013BAA01B04)~~

摘　　要：针对含分布式电源(DG)的配电网规划问题,利用图论的思想,建立以规划年费用最小为目标的含分布式电源配电网规划图模型,提出两阶段的启发式算法,实现优化分布式电源的接入位置、接入容量、实际接入量及变电站和配电线路的新建或者升级改造等综合优化。第一阶段,对所建的图模型应用多重局部搜索算法确定分布式电源的接入位置、接入容量及变电站和配电线路的新建或者升级改造决策;第二阶段,利用第一阶段优化得到的线路、电源参数,建立精确的数学模型,并运用遗传算法确定分布式电源的实际接入量。33节点典型系统算例证明了该算法在含分布式电源配电网规划中应用的可行性和有效性。Distribution network planning with distributed generation is discussed. A graph model is formulated to convert planning problem to a flow problem. A two-stage method is proposed to achieve multiple targets optimization including capacity and sizing of distributed generation, feeder and substation upgrade. In the first stage, a local search algorithm within the graph model is performed to get suboptimal solution by using minimum cost flow algorithm. In the second stage, genetic algorithm is applied to fine mathematic formulation for final result based on first stage result. The experimental result on a 33-node benchmark system shows that the proposed method can get better solution than traditional genetic algorithm in shorter time, which shows its feasibility and efficiency.

关 键 词：配电网规划 分布式电源 最小费用最大流 图模型 两阶段启发式算法 

分 类 号：TM715[电气工程—电力系统及自动化]