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Optimal Corrective Actions For Power Systems Using Multi-objective Genetic Algorithms

机译：使用多目标遗传算法的电力系统最优纠正措施

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摘要

In this paper, optimal corrective control actions are presented to restore the secure operation of power system for different operating conditions. Genetic algorithm (GA) is one of the modern optimization techniques, which has been successfully applied in various areas in power systems. Most of the corrective control actions involve simultaneous optimization of several objective functions, which are competing and conflicting each other. The multi-objective genetic algorithm (MOGA) is used to optimize the corrective control actions. Three different procedures based on GA and MOGA are proposed to alleviate the violations of the overloaded lines and minimize the transmission line losses for different operation conditions. The first procedure is based on corrective switching of the transmission lines and generation re-dispatch. The second procedure is carried out to determine the optimal siting and sizing of distributed generation (DG). While, the third procedure is concerned into solving the generation-load imbalance problem using load shedding. Numerical simulations are carried out on two test systems in order to examine the validity of the proposed procedures.
机译：本文提出了最佳的纠正控制措施，以恢复电力系统在不同工况下的安全运行。遗传算法（GA）是现代优化技术之一，已成功应用于电力系统的各个领域。大多数纠正控制措施都涉及同时优化多个相互竞争和冲突的目标功能。多目标遗传算法（MOGA）用于优化纠正控制措施。提出了基于GA和MOGA的三种不同的程序，以减轻对过载线路的侵犯，并使不同工况下的传输线损耗最小。第一个过程基于传输线的正确切换和发电重新分配。执行第二个过程以确定分布式发电（DG）的最佳选址和规模。同时，第三步涉及使用减载来解决发电-负荷不平衡问题。为了检验所提出程序的有效性，在两个测试系统上进行了数值模拟。

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