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Reactive Power Optimization of Power System Based on Improved Differential Evolution Algorithm

机译:基于改进差分演化算法的电力系统无功优化

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This paper presents a novel differential evolution (DE) algorithm, with its improved version (IDE) for the benchmark functions and the optimal reactive power dispatch (ORPD) problem. Minimization of the total active power loss is usually considered as the objective function of the ORPD problem. The constraints involved are generators, transformers tapings, shunt reactors, and other reactive power sources. The aim of this study is to discover the best vector of control variables to minimize power loss, under the premise of considering the constraints system. In the proposed IDE, a new initialization strategy is developed to construct the initial population for guaranteeing its quality and simultaneously maintaining its diversity. In addition, to enhance the convergence characteristic of the original DE, two kinds of self-adaptive adjustment strategies are employed to update the scaling factor and the crossover factor, respectively, in which the detailed information about the two factors can be exchanged for each generation dynamically. Numerical applications of different cases are carried out on several benchmark functions and two standard IEEE systems, i.e., 14-bus and 30-bus test systems. The results achieved by using the proposed IDE, compared with other optimization algorithms, are discussed and analyzed in detail. The obtained results demonstrated that the proposed IDE can successfully be used to deal with the ORPD problem.
机译:本文提出了一种新颖的差分演进(DE)算法,其改进的版本(IDE)用于基准函数和最佳无功功率调度(ORPD)问题。最小化总有效功率损耗通常被认为是ORPD问题的目标函数。所涉及的约束是发电机,变压器胶带,并联电抗器和其他无功电源。本研究的目的是发现控制变量的最佳载体,以最小化电力损耗,在考虑约束系统的前提下。在拟议的IDE中,开发了一种新的初始化策略,以构建初始群体,以保证其质量并同时保持其多样性。此外,为了提高原始DE的收敛特性,采用两种自适应调整策略来分别更新缩放因子和交叉因子,其中可以为每代交换有关两个因素的详细信息动态地。不同案例的数值应用在几个基准函数和两个标准IEEE系统,即14公交车和30柱测试系统上进行。与其他优化算法相比,通过使用所提出的IDE实现的结果,并详细讨论和分析。所获得的结果表明,建议的IDE可以成功地用于处理ORPD问题。

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