Distribution Generation Planning in Distribution Network using Ant Lion Optimizer

Z. M. Yasin, M. Rusdi, Z. Zakaria
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引用次数: 1

Abstract

This paper proposed a method to determine the optimal location and sizing of Distributed Generation (DG) for power loss minimization using Ant Lion optimizer (ALO). The analysis also covers the effect of DG installation to voltage improvement and maximum system loadability index. ALO is an optimization algorithm that based on the nature interaction between ants and antlions. The nature interaction consists of five steps of hunting prey such as random walk of ants, building traps, entrapment of ants in traps, catching preys, and rebuilding traps. The ALO algorithm is tested on IEEE 69-bus distribution test system. The system will find the optimal location and sizing with corresponding load increase until it reaches the maximum system loadability (MSL) of the network. DG are usually attached to the end terminal at the load side of the system that refers to a technology that generate electricity at or near where it will be used such as solar panels and combined heat and power. The result of test function shows that the proposed algorithm can provide accurate yet competitive result in terms of power loss minimization, maximum system loadability enhancement and consistency.
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基于蚁狮优化的配电网配电网发电规划
提出了一种利用蚂蚁狮子优化器(ALO)确定分布式发电(DG)的最优位置和最优规模的方法。分析了DG安装对电压改善和系统最大负荷指标的影响。蚁群优化算法是一种基于蚁群与蚁群之间自然相互作用的优化算法。自然互动包括蚂蚁的随机行走、设置陷阱、将蚂蚁困在陷阱中、捕捉猎物和重建陷阱五个步骤。在IEEE 69总线配电测试系统上对ALO算法进行了测试。随着负载的增加,系统将找到最优的位置和规模,直到达到网络的最大系统负载能力(MSL)。DG通常附着在系统负载侧的终端上,这是指在使用地点或附近发电的技术,如太阳能电池板和热电联产。测试函数的结果表明,该算法在最小化功耗、最大限度地提高系统负载性和一致性方面能够提供准确而有竞争力的结果。
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