电力系统恢复控制的网络重构智能优化策略

作为现代电力系统恢复控制的核心研究内容之一，该文对恢复控制中的网络重构问题进行探讨，提出最优送电路径的通用模型和相应的智能优化算法解算模式。以寻找最短的加权送电路径为优化目标，将网络重构建模为一个寻找图的局部最小树问题，并计及各种约束。利用遗传算法易于处理离散变量且具有全局收敛性的特点，对该优化问题进行求解。求解过程中，对算法寻优性能进行研究以提高求解速度、算法稳定性和寻优效率。所提方法能较好地解决解算精度与速度的矛盾。最后以IEEE 30节点系统作为算例，验证所提模型和算法的有效性。

Intelligent Optimization Strategy of the Power Grid Reconfiguration During Power System Restoration

As one of core subjects in the modern power system restoration research, the power grid reconfiguration is discussed, and a novel optimal strategy involving the corresponding model and approach for power grid reconfiguration is presented in this paper. The goal of the proposed model is to find the shortest weighted path for generation unit start-up or load recovery in restoration duration whilst considering all kinds of constraints. The proposed model is considered as a typical partial minimum spanning tree problem from the mathematical point of view. The genetic algorithm method with characteristics of global optimization and handling the discrete variables easily and effectively is employed to solve this problem. Furthermore, the performance of genetic algorithm is optimized in order to improve calculation speed, stability and search efficiency further. To some extent, the proposed method can make the trade off between the simulation precision and the computational efforts much better. Finally, the IEEE 30-bus test system is applied as benchmark to demonstrate the effectiveness and validity of the proposed model and method.