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Optimal Battery Sizing in Photovoltaic Based Distributed Generation Using Enhanced Opposition-Based Firefly Algorithm for Voltage Rise Mitigation

机译:基于增强型基于对立的萤火虫算法的光伏分布式发电中的最佳电池尺寸调整

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摘要

This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem.
机译:本文介绍了基于增强对立的萤火虫算法在获得光伏发电集成径向配电网中最佳电池储能系统(BESS)规模以减轻电压上升问题方面的应用。最初,通过利用基于对立的学习并引​​入惯性权重来增强原始萤火虫算法的性能。在评估具有15个基准功能的增强型基于对立的萤火虫算法(EOFA)的性能后,可采用该算法来确定BESS的最佳大小。进行两个优化过程,其中第一个优化旨在获得每小时最佳的电池输出功率,第二个优化旨在通过考虑BESS的充电状态约束来获得最佳BESS容量。通过将该算法应用于69总线配电系统,并将EOFA与传统萤火虫算法和重力搜索算法的性能进行比较,验证了该方法的有效性。结果表明,就减轻电压上升问题而言,EOFA具有最佳的性能。

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