基于改进邻接矩阵的稀疏技术及其在电力系统计算中的应用

针对存储网络拓扑结构的邻接矩阵具有高度稀疏的特点，对其表现形式进行改进，并将改进后的邻接矩阵应用于节点优化编号、检索信息的提前确定以及节点导纳矩阵的形成。在因子分解过程中，为实现列方向的非零检索，增加了列向的存储信息，并制定相应的检索方式。根据优化编号过程中新增支路与因子分解非零注入元的关联性质，在优化编号的同时，记录新增元素的位置并形成存储框架。将所提稀疏技术应用于谐波阻抗扫描与等值程序的开发，对6个电力系统的测试结果表明，随着系统规模的增大，所提方法与传统方法及NIMSCAN程序相比，可显著提高节点方程的求解效率，适用于大规模电力系统的分析与计算。

Improved adjacent matrix based sparse technology and its application in power system calculation

According to the highly sparse characteristics of the adjacent matrix used for the networks topology storing, its manifestation is improved, and the improved adjacent matrix is applied to node ordering optimization, determination of retrieval information in advance and the formation of node admittance matrix. During the process of factorization, to achieve the nonzero retrieving in the column direction, the stored information of the column direction is added and the corresponding retrieval method is made. According to the relationships between new added branches in node ordering and the nonzero injections in factorization, in the meantime of ordering optimization, the position of the new added elements is recorded and the storage framework is formed. The proposed sparse technology is used in the network impedance scanning and equivalence program, and testing results for six power systems show that, with the increase of system scale, the calculation efficiency of node equations with the proposed method is greatly improved compared with the traditional methods and the NIMSCAN program, and it is applicable to the analysis and calculation for large scale power system.