基于遗传算法的最优减载规划

Chao-Rong Chen, Wenta Tsai, Huayran Chen, Ching-Ying Lee, Chun-Ju Chen, H. Lan
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引用次数: 18

摘要

提出了一种利用遗传算法实现减载最小化的规划方法。当发电机停运时,电力系统的频率迅速下降。一般的解决方案是安装足够的低频继电器将频率拉回正常范围。本研究利用单机无限总线(SMIB)模拟系统负荷,采用遗传算法估计各阶段的最优减载和减载比。仿真结果表明,基于遗传算法的方法是可行的、有效的,可以实现最优减载规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal load shedding planning with genetic algorithm
This paper proposes a novel planning method using genetic algorithm (GA) to achieve minimization of load shedding. The frequency of a power system declines rapidly when generator outage occurs. The general solution is to install sufficient under-frequency relays to pull frequency back to normal range. In this study, a single machine infinite bus (SMIB) is utilized to simulate system load with genetic algorithm for estimating the optimal load shedding and shedding ratio in each stage. Simulated results indicate that the proposed GA-based method is both feasible and effective to facilitate optimal load shedding planning.
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