OPF Solution by the Hunger Games Search (HGS) Algorithm

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Abstract

Optimal power flow (OPF) is a significant problem in electrical engineering. The optimization method of the Hunger Games Search (HGS) algorithm was presented in this study, which finds the OPF under different case studies. These cases include reducing the total fuel cost, minimizing power losses in transmission lines, reducing the amount of pollutants generated by units, and minimizing voltage variation at load buses. MATLAB software was used to test the suggested algorithm using the IEEE 30-bus power system. The findings indicate that the suggested algorithm was effective in accomplishing the goals of obtaining a reduction of 11.30% in the use of fuel cost, a reduction of 46.90% in power loss, a reduction of 88.11% in voltage fluctuation, and a reduction of 3.38% in pollutants while simultaneously satisfying all of the restrictions. We compared the used and published optimization methods. Finally, the HGS presented good performance in terms of power loss and fuel cost compared with other techniques. Keywords: Hunger Games Search, power flow, fuel cost, emission, power system, MATLAB. https://doi.org/10.55463/issn.1674-2974.50.8.11
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基于饥饿游戏搜索算法的OPF求解
最优潮流(OPF)是电气工程中的一个重要问题。本文提出了饥饿游戏搜索(Hunger Games Search, HGS)算法的优化方法,在不同的案例下找到OPF。这些情况包括降低总燃料成本,最大限度地减少输电线路的功率损耗,减少机组产生的污染物数量,以及最大限度地减少负载母线的电压变化。利用MATLAB软件在IEEE 30总线电力系统上对所提出的算法进行了测试。结果表明,该算法在满足所有限制条件的同时,有效地实现了燃料成本降低11.30%、功率损耗降低46.90%、电压波动降低88.11%、污染物排放降低3.38%的目标。我们比较了使用的和发表的优化方法。最后,与其他技术相比,HGS在功率损失和燃料成本方面表现出良好的性能。关键词:饥饿游戏搜索,潮流,燃料成本,排放,电力系统,MATLAB。https://doi.org/10.55463/issn.1674-2974.50.8.11
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