Hunter–Prey Optimization Algorithm for Optimal Allocation of PV, DSTATCOM, and EVCS in Radial Distribution Systems

Soundarya Lahari Pappu, Varaprasad Janamala, A. S. Veerendra
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Abstract

This research article instigates a seminal approach for optimizing reactive power in renewable energy sources (RES) and electric vehicles (EVs) coalescing distribution systems, using the innovative Hunter–Prey Optimization (HPO) algorithm in conjunction with DSTATCOM as a reactive power compensator. The proposed methodology aims to minimize losses, enhance voltage stability, and improve overall system performance by simultaneously optimizing reactive power flows in photovoltaic RES (PV_DG), EV charging stations (EVCS), and DSTATCOMs within the distribution system. Simulations carried on IEEE-33, IEEE-69, and IEEE-118 test bus systems in MATLAB environment demonstrate that the HPO-based approach achieves a 91.47% and 96.61% reduction in real power losses and an improvement in voltage profile with a minimum voltage value of 0.991 and 0.994 p.u. (respectively for IEEE-33 and 69 bus systems), compared to traditional algorithms. These results highlight the lofty performance of the HPO method, effectively addressing the challenges posed by the integration of RES and EVs along with DSTATCOM.

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径向配电系统中光伏、DSTATCOM 和 EVCS 优化配置的猎人-猎物优化算法
本文提出了一种开创性的方法来优化可再生能源(RES)和电动汽车(ev)合并配电系统中的无功功率,使用创新的猎人-猎物优化(HPO)算法与DSTATCOM作为无功功率补偿器。所提出的方法旨在通过同时优化配电系统中光伏储能系统(PV_DG)、电动汽车充电站(EVCS)和DSTATCOMs的无功功率流,最大限度地减少损耗,提高电压稳定性,并提高整体系统性能。在MATLAB环境下对IEEE-33、IEEE-69和IEEE-118测试总线系统进行了仿真,结果表明,基于hpo的方法分别降低了91.47%和96.61%的实际功率损耗,并改善了电压分布,最小电压值分别为0.991和0.994 p.u。(分别针对IEEE-33和69总线系统),与传统算法相比。这些结果凸显了HPO方法的卓越性能,有效地解决了RES和ev以及DSTATCOM集成带来的挑战。
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