基于多目标优化的电网弹性薄弱环节识别

加固电力系统中少数关键元件提升其抗外力冲击能力可以有效提升电力系统弹性。本文主要研究考虑弹性的电力系统薄弱环节识别。首先，基于弹性过程曲线提出了最大供电能力指标来定量刻画系统弹性，构建了最优潮流模型并通过单纯形法求解任意拓扑下电力系统能提供的最大供电能力。然后在此基础上构建多目标优化模型，以破坏元件数目和电网的最大供电能力两个指标作为目标函数，选取智能优化算法对建立的多目标优化模型进行求解计算。仿真结果表明与基于启发式算法相比，本文建立的的多目标优化模型能够有效识别电力系统中对弹性有重要影响的关键元件组合。

Research on identification of vulnerable sets of components considering power grid resilience based on multi-objective optimizations

To enhancing a small fraction of critical components in the face to extreme disturbances can effectively improve the power grid resilience. In this paper, identifying the set of vulnerable components in the power system that most affect its resilience is investigated. First, based on the resilience process curve, the largest amount of power supply of a given topology was proposed to quantify power grid resilience, which was calculated with the optimal power flow model and simplex method. Then, a multi-objective optimization model was built, and two indicators, the number of damaged components and the maximum power that the grid can provide, were used as objective functions. Second, three intelligent optimization algorithms were selected to solve the established multi-objective optimization model. Simulation results show that the proposed method can effectively identify the critical components that have a significant impact on power system resilience, compared with commonly used methods.