Diminution of factual power loss by enhanced bacterial foraging optimization algorithm

K. Lenin
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Abstract

This paper presents an enhanced bacterial foraging optimization (EBFO) algorithm for solving the optimal reactive power problem. Bacterial Foraging optimization is based on foraging behaviour of Escherichia coli bacteria which present in the human intestine. Bacteria have inclination to congregate the nutrient-rich areas by an action called as Chemo taxis. The bacterial foraging process consists of four chronological methods i.e. chemo taxis, swarming and reproduction and elimination-dispersal. In this work rotation angle adaptively and incessantly modernized, which augment the diversity of the population and progress the global search capability. The quantum rotation gate is utilized for chemo taxis to modernize the state of chromosome Projected enhanced bacterial foraging optimization (EBFO) algorithm has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss extensively.
增强细菌觅食优化算法降低实际功率损失
提出了一种求解最优无功问题的增强型细菌觅食优化算法。细菌觅食优化是基于觅食行为的大肠杆菌存在于人类肠道。细菌倾向于聚集在营养丰富的区域,这一行为被称为化学趋向性。细菌的觅食过程包括四种时间顺序,即趋化、成群繁殖和消除-扩散。在此工作中,旋转角度自适应地不断现代化,增加了种群的多样性,提高了全局搜索能力。利用量子旋转门对染色体的化学趋向性进行了改进,并在标准IEEE 14300总线测试系统上对投影增强细菌觅食优化(EBFO)算法进行了测试,仿真结果表明该算法大大降低了实际功率损耗。
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