复杂网络的社团发现方法在电网分区识别中的应用研究

摘要

The traditional way of dividing the power grid is mainly based on geographical and administrative area, which often ignores the network’s structure and characteristics, however, power grid’s blackout always results from the partition lines. Community structure detection of complex network is used to identify the network’s topology partition by the connections between nodes and it has a familiar structure with power grid’s partition. This paper introduces the conceptions and evaluation indexs of community structure and the modularity Q function, comes up with a new power grid partition method based on community structure detecting. Four different kinds of weighted network models are built with grid tide and impedance data. The improved Louvain hierarchical algorithm is adopted to divide power grid and a practical improvement is made in partition process considering the real power grid’s characteristics. Through the community division results of IEEE 39, 118, 300 standard power grids and China southern power grid in different models, this method is proved to be effective and accurate.%　　电网传统分区方案主要依据地理和行政区域，这样的分区往往对网络结构没有太多关注，而引发大停电事故又多源自分区联络线。复杂网络理论中的社团发现利用节点之间的连接关系来识别网络拓扑分区，与电网的分区结构极为相似。简介了社团结构及其模块化Q函数的概念及其评价指标，提出了基于社团发现的电网分区方法。利用电网潮流和阻抗参数作为边的权重建立四种不同的加权复杂网络模型，引入Louvain改进层次算法，并结合实际电网的特点对分区流程进行了实用化改进。基于标准的IEEE39、118、300节点电网及南方电网，分析了不同模型下的电网分区结果，论证了其有效性和准确性。