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Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems
Journal of Electrical Systems and Information Technology Pub Date : 2018-12-01 , DOI: 10.1016/j.jesit.2017.06.001
Dinakara Prasasd Reddy P. , Veera Reddy V.C. , Gowri Manohar T.

Abstract This paper mainly focused on the impact of distributed generation (DG) placement on distribution system. The integration of DG is transforming the traditional radial distribution system into a multi-source system. Distributed generation is a term that refers to the production of electricity near the consumption place. The effects of distributed generation are short circuit levels are increased, load losses change, reliability change and voltage profiles change along the network. The above advantages can be accomplished by ideal position and sizing of DG units. The ideal positions are obtained from index vector method. Ant Lion Optimization (ALO), a novel meta heuristic algorithm is used to determine the optimal DG size. ALO is modeled based on the unique hunting behavior of ant lions. The ALO algorithm is evaluated on IEEE 15, 33, 69 and 85-bus test systems. ALO algorithm was compared with different types of DG units and other evolutionary algorithms. When compared with other algorithms the ALO algorithm gives better results. From the analysis best results have been achieved from type III DG operating at 0.9 pf.

中文翻译:

用于优化可再生能源规模以减少配电系统损耗的 Ant Lion 优化算法

摘要 本文主要研究分布式电源(DG)布局对配电系统的影响。DG 的整合正在将传统的放射状配电系统转变为多源系统。分布式发电是指在消费地附近生产电力的术语。分布式发电的影响是短路水平增加、负载损耗变化、可靠性变化和电压分布沿网络变化。上述优点可以通过理想的 DG 单元位置和尺寸来实现。理想位置是通过索引向量方法获得的。Ant Lion Optimization (ALO) 是一种新颖的元启发式算法,用于确定最佳 DG 大小。ALO 是根据蚂蚁狮子独特的狩猎行为建模的。ALO 算法在 IEEE 15、33、69 和 85 总线测试系统。ALO 算法与不同类型的 DG 单元和其他进化算法进行了比较。与其他算法相比,ALO 算法给出了更好的结果。根据分析,在 0.9 pf 下运行的 III 型 DG 获得了最佳结果。
更新日期:2018-12-01
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