【摘要】 提出一种改进粒子群优化算法并将其应用于电网无功分区,以复杂网络社团结构理论为基础,建立以电气距离为权重的电力系统加权网络模型,以模块度为标准量化地评价无功分区的划分质量。改进粒子群优化算法采用了新的粒子编码方式与位置更新方式,提高了以模块度为目标函数的启发式算法的收敛速度并减少了存储空间。通过改进粒子群优化算法得到的无功网络具有较强的区域解耦特性,分区内部电气联系紧密,区域之间联系稀疏,无功分区结构合理。该算法在IEEE 39节点系统、IEEE 118节点系统及大型电网的应用结果表明了该算法的合理性及有效性。更多还原

【Abstract】 An improved particle swarm optimization( PSO) algorithm is presented and applied to reactive power partitioning of power grid. The method is based on complicated network theory and adopts modularity as the standard to quantitatively evaluate the quality of power network partitioning. Furthermore, a power system network model weighted by electrical distance and combined with improved PSO algorithm for reactive power network partitioning is proposed. A new particle coding method and location updating method are adopted by the improved PSO algorithm, which improves the convergence rate of heuristic algorithm aimed at the modularity and saves storage capacity. The reactive power network obtained by the improved PSO algorithm has strong regional decoupling characteristics of close electrical link internally but sparse externally. The rationality and effectiveness of the algorithm are verified by the application of IEEE 39-bus system, IEEE 118-bus system and large power network systems.更多还原