Abstract In this paper, a novel hybrid population-based meta-heuristic algorithm, called the hybrid Phasor Particle Swarm Optimization and Gravitational Search Algorithm (PPSOGSA), is proposed to solve the problem of optimal placement and sizing of inverter-based distributed generation (DG) units and shunt capacitors in radial distribution systems with linear and non-linear loads. The objective of the problem is reduction of active power losses considering constraints of the fundamental frequency active and reactive power balance, RMS voltage, and total harmonic distortion of voltage (THDV) at each bus of the network, as well as the branch flow constraints. The performance of the PPSOGSA-based approach is evaluated on the standard IEEE 33- and 69-bus test systems under sinusoidal and non-sinusoidal operating conditions. Compared to the original PPSO and GSA and other algorithms commonly used in the optimal sitting and sizing problem of DG units and shunt capacitors, it is found that the proposed algorithm has yielded better results.

中文翻译：

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使用混合相量粒子群优化和引力搜索算法在扭曲配电系统中优化基于逆变器的分布式发电机组和并联电容器的布局和尺寸

摘要 本文提出了一种新的混合基于种群的元启发式算法，称为混合相量粒子群优化和引力搜索算法（PPSOGSA），用于解决基于逆变器的分布式发电（DG ) 具有线性和非线性负载的径向配电系统中的单元和并联电容器。该问题的目标是考虑到基频有功和无功功率平衡、RMS 电压和网络每条总线上的电压总谐波失真 (THDV) 以及支流约束的约束，减少有功功率损耗。在正弦和非正弦操作条件下，在标准 IEEE 33 和 69 总线测试系统上评估基于 PPSOGSA 的方法的性能。