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An improved generalized differential evolution algorithm for multi-objective reactive power dispatch

机译:多目标无功调度的改进广义差分进化算法

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An improved multi-objective generalized differential evolution (I-GDE3) approach to solve optimal reactive power dispatch (ORPD) with multiple and competing objectives is proposed in this article. The objective functions are minimization of real power loss and bus voltage profile improvement. For maintaining good diversity, the concepts of simulated binary crossover (SBX) based recombination and dynamic crowding distance (DCD), are implemented in the GDE3 algorithm. I-GDE3 obtains the Pareto-solution set for ORPD that is impervious to load drifts and perturbations. The performance of the proposed approach is tested in standard IEEE 118-bus and IEEE 300-bus test systems and the result demonstrates the capability of the I-GDE3 algorithm in generating diverse and well distributed Pareto-optimal solutions that are less sensitive to various loading conditions along with load perturbations. The performance of I-GDE3 is compared with respect to multi-objective performance measures namely span, hyper-volume and C-measure. The results show the effectiveness of I-GDE3 and confirm its potential to solve the multi-objective RPD problem.
机译:本文提出了一种改进的多目标广义差分进化(I-GDE3)方法,以解决具有多个目标和竞争目标的最优无功功率分配(ORPD)。目标功能是最小化实际功率损耗并改善总线电压曲线。为了保持良好的多样性,在GDE3算法中实现了基于模拟二进制交叉(SBX)的重组和动态拥挤距离(DCD)的概念。 I-GDE3获得ORPD的Pareto解集,该集不受负载漂移和扰动的影响。该方法的性能在标准IEEE 118总线和IEEE 300总线测试系统中进行了测试,结果证明了I-GDE3算法具有生成对各种负载较不敏感的多样且分布良好的帕累托最优解决方案的能力。条件以及负载扰动。将I-GDE3的性能与跨度,超容量和C度量等多目标性能度量进行了比较。结果表明I-GDE3的有效性,并证实了其解决多目标RPD问题的潜力。

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