径向配电系统中电容器组与光伏发电机组优化集成的多目标猎-猎物优化

Soundarya Lahari Pappu, Varaprasad Janamala
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引用次数: 0

摘要

本文提出了径向配电系统中电容器组和PV-DG(光伏配电发电)单元的最佳选址和尺寸的确定。采用基于种群的现代优化算法——猎人-猎物优化算法(HPO)来确定最佳电容器组和PV-DG的放置位置。这个算法,HPO,从像狮子和狼这样的食肉动物(捕食者/猎人)对鹿这样的目标动物的诱捕行为中得到了它的动机。典型的IEEE-33使用MATLAB软件R2021b版本对69个测试总线系统进行了仔细检查,以验证所建议算法的有效性。所得结果与现有的有功损耗准则的启发式算法进行了比较。为了与HPO的结果进行比较,考虑了系统损耗和电压分布的标称值或基本值。与其他技术相比,HPO应用在确定电容器组和光伏dg的最佳位置和容量方面具有有效的性能。
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A multi-objective hunter-prey optimization for optimal integration of capacitor banks and photovoltaic distribution generation units in radial distribution systems
This article put forward the determination of the optimal siting and sizing of capacitor banks and PV-DG (Photo-Voltaic Distribution Generation) units in a radial distribution system. A modern population-based optimization algorithm, Hunter-Prey Optimization (HPO), is applied to determine the optimal capacitor bank and PV-DG placement. This algorithm, HPO, got its motivation from the trapping behaviour of the carnivore (predator/hunter) like lions and wolves towards their target animal like deer. The typical IEEE-33 & 69 test bus systems are scrutinized for validating the effectiveness of the suggested algorithm using MATLAB software R2021b version. The acquired results are collated with the existing heuristic algorithms for the active power loss criterion. The nominal or base values for system losses and voltage profile were considered for the comparison, with the results from HPO. The HPO application has an efficient performance in figuring out the most favourable location and capacity of the capacitor banks and PV DGs compared with the other techniques.
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