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Application of Constriction Factor Particle Swarm Optimization to Optimum Load Shedding in Power System

机译:收缩因子粒子群算法在电力系统最优减载中的应用

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Load shedding is an important action during contingency situations in electrical power systems. This paper presents a new application of constriction factor particle swarm optimization (CPSO) technique for solving the steady state load shedding (SSLS) problem, due to capacity deficiency conditions caused by unscheduled outages in the bulk generation and transmission system. The problem is formulated to minimize the sum of curtailed load in contingency situations and restore the power system to its normal security and operation conditions. The feasibility of the proposed approach is demonstrated and compared with genetic algorithm (GA) in terms of solution quality and convergence properties over realistic test systems.
机译:在电力系统的紧急情况下,减载是一项重要的动作。本文提出了一种收缩因子粒子群优化(CPSO)技术在解决稳态发电负荷(SSLS)问题方面的新应用,该问题是由于大容量发电和输电系统中计划外停机造成的容量不足情况。该问题的制定旨在最大程度地减少紧急情况下减少的负荷总和,并使电源系统恢复到其正常的安全性和运行状态。在解决方案质量和在实际测试系统上的收敛性方面,证明了该方法的可行性并与遗传算法(GA)进行了比较。

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