Economic Analysis by Optimal Placing of DGs in Distribution Networks by Particle Swarm Optimisation and Gravitational Search Optimisation Algorithm

C. Prasad, K. Subbaramaiah, P. Sujatha
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Abstract

The particle swarm optimisation and gravitational search optimisation algorithm (PSOGSA) is a hybrid algorithm which is used to determine size of optimal Distributed Generation (DG) in this paper. The PSOGSA integrates the social thinking ability (gbest) in PSO to capability of local search in GSA. The algorithm combines the searching capability of PSO and with enhanced exploration ability of GSA. Distributed generations are connected in distribution systems to consumers to reduce losses, enhance the voltage profile, reliability and economic benefits. DG optimal positioning and loss minimisation have a significant role for economic operation and overall reduction of energy costs. For evaluation of proposed algorithm, the test bus sets IEEE15, 33 and 69 are chosen. For considered objectives i.e., optimal DG sizing and economic analysis, this PSOGSA algorithm gives better results as compared to other methods and better outcomes has been achieved when DG unit of type III operates at power factor of 0.9 lag
基于粒子群优化和引力搜索优化算法的配电网dg优化配置的经济分析
粒子群优化和引力搜索优化算法(PSOGSA)是一种用于确定最优分布式发电(DG)规模的混合算法。PSOGSA将PSO中的社会思维能力(gbest)与GSA中的局部搜索能力相结合。该算法结合了粒子群算法的搜索能力和增强的GSA算法的搜索能力。分布式电源在配电系统中连接到用户,以减少损耗,提高电压分布,可靠性和经济效益。DG优化定位和损失最小化对经济运行和整体降低能源成本具有重要作用。为了对所提出的算法进行评估,选择了IEEE15、33和69测试总线集。对于考虑的目标,即最优DG规模和经济分析,与其他方法相比,该PSOGSA算法具有更好的结果,并且当III型DG机组在功率因数为0.9滞后时取得了更好的结果
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