Cuckoo-search optimized fuzzy-logic control of stationary battery storage systems

C. Truong, Daniel May, Rodrigo Martins, P. Musílek, A. Jossen, H. Hesse
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引用次数: 3

Abstract

Energy storage systems are acknowledged as key components for transforming the power system towards low-carbon technology. The performance and resulting benefit of energy storage systems are determined by their operation strategies. We present a generic and adaptive control algorithm, based on fuzzy-logic and optimized by a meta heuristic search method. The performance of the algorithm is demonstrated in a solar home context, with the aim to alleviate the voltage rise in the low-voltage distribution grid caused by renewable energy generation. This is achieved by reducing the household's peak feed-in of each day. The obtained results show that the proposed algorithm performs similarly well as a rule-based reference algorithm, specifically designed to reduce the daily feed-in peak. At the same time, the generic structure of the proposed controller is by far more versatile, as it allows its application in a variety of scenarios just by modifying the objective function for the search algorithm.
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固定式电池储能系统的模糊逻辑控制
储能系统被认为是电力系统向低碳技术转型的关键组成部分。储能系统的运行策略决定了储能系统的性能和效益。提出了一种基于模糊逻辑的通用自适应控制算法,该算法采用元启发式搜索方法进行优化。以太阳能家庭为例,验证了该算法的性能,以缓解可再生能源发电引起的低压配电网电压升高。这是通过减少家庭每天的高峰喂食量来实现的。结果表明,该算法的性能与基于规则的参考算法相似,该算法专门设计用于降低日馈峰。同时,所提出的控制器的通用结构是更通用的,因为它允许其应用于各种场景,只需修改搜索算法的目标函数。
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