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Gaussian bare-bones water cycle algorithm for optimal reactivepower dispatch in electrical power systems

机译:高斯裸骨水循环算法,用于电力系统的最优振动器调度

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摘要

Water cycle algorithm (WCA) is one of the efficient metaheuristic optimization algorithms inspired by hydrological cycle in nature. WCA can outperform several robust and efficient metaheuristics in solving optimization problems. Like other metaheuristics, premature convergence and stagnation in local optima can still occur in WCA. In order to mitigate this problem, in this paper, a Gaussian bare-bones WCA (NGBWCA) is proposed and utilized to tackle optimal reactive power dispatch (ORPD) problem in electric power systems. Resistive losses and voltage deviations are the objectives to be minimised. The efficiency of the proposed NGBWCA optimizer is investigated and compared to other well-established metaheuristic optimisation algorithms on IEEE 30, 57 and 118 bus power systems. The experimental results and statistical tests vividly demonstrate the efficiency of the NGBWCA algorithm in solving ORPD problem. (C) 2017 Elsevier B.V. All rights reserved.
机译:水循环算法(WCA)是自然水文循环启发的有效的成群质优化算法之一。 WCA可以在解决优化问题方面优于多种稳健和有效的常规法。 与其他美术学,在WCA中仍然可能发生在当地最佳的过早融合和停滞状态。 为了减轻该问题,本文提出了一种高斯裸骨WCA(NGBWCA)并利用在电力系统中解决最佳无功功率调度(ORPD)问题。 电阻损耗和电压偏差是最小化的目标。 研究了所提出的NGBWCA优化器的效率,并与IEEE 30,57和118总线电力系统上的其他良好的成熟优化算法进行了研究。 实验结果和统计测试生动地证明了NGBWCA算法在解决ORPD问题方面的效率。 (c)2017 Elsevier B.v.保留所有权利。

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