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

机译:基于光伏基于光伏的分布式发电的最佳电池尺寸使用增强的基于反对派的萤火虫算法进行电压上升缓解

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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:本文介绍了增强型反对派的萤火虫算法在光伏发电集成径向分布网络中获得最佳电池储能系统(BESS)尺寸,以减轻电压上升问题。最初,通过利用基于对立的学习和引入惯性重量来提高原始萤火虫算法的性能。在使用十五个基准函数的基于增强的反对派的萤火虫算法(eofa)的性能之后,然后采用它来确定贝塞的最佳尺寸。进行两个优化过程,其中第一优化旨在每小时获得最佳电池输出功率,并且第二优化目的是通过考虑贝塞的充电状态来获得最佳的BESSS容量。通过将算法应用于69总线分配系统,并通过比较常规萤火虫算法和引力搜索算法的eofa的性能来验证所提出的方法的有效性。结果表明,在减轻电压上升问题方面,EOFA具有最佳性能。

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