多时间尺度恢复策略融合的电力系统弹性优化

电力系统在遭受灾害冲击后快速恢复供电的能力对社会稳定与国家安全起着举足轻重的作用。本文融合快速紧急调度和慢速装备修复两个不同时间尺度恢复措施，提出了新能源电力系统的弹性优化方案。首先，考虑新能源出力的波动性，建立了在给定拓扑上新能源电力系统的优化调度模型。其次，为了解决灾后连接所有未被损坏设备构成的拓扑不一定是最优拓扑的问题，使用遗传算法对灾后电力系统进行拓扑重构。最后，考虑受损设备的顺序修复过程，使用贪婪算法计算每个设备修复序列，即每次优先选择修复能使系统供电效益增量最大的电力设备。仿真结果表明所提出的综合优化方法能有效提升新能源电力系统受灾后整个恢复过程的总体供电效益。

Resilience Optimization of Power Grids Considering Integration of Multi-timescale Restoration Strategies

The ability of power grids to quickly recover from extreme environmental disturbances such as natural disasters plays a pivotal role in social stability and national security. In This paper, optimizing the resilience of new energy-penetrated power grids was investigated by integrating recovery methods of different timescales, such as emergency dispatching and gradual equipment repair. First, considering the fluctuation of new energy outputs, a short-term optimal scheduling model of new energy-penetrated power grids on a given topology was established. Second, in order to solve the problem that the topology formed by connecting all undamaged devices after the disaster was not necessarily the optimal topology, the genetic algorithm was used to reconstruct the topology of the power grid after the disaster. Finally, considering the sequential repair process of damaged equipment, the greedy algorithm was used to generate the repair sequence, that was, the power equipment whose repair leads to the largest benefit increment was preferentially selected each time. Simulation results show that the integrated recovery scheme can effectively improve the overall power supply benefit of the whole restoration process of new energy-penetrated power grids.