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A novel multi-objective hybrid WIPSO-GSA algorithm-based optimal DG and capacitor planning for techno-economic benefits in radial distribution system

机译:基于新型多目标混合WIPSO-GSA算法的最优DG和电容器规划,可为径向配电系统带来技术经济效益

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Purpose - This paper aims to optimally plan distributed generation (DG) and capacitor in distribution network by optimizing multiple conflicting operational objectives simultaneously so as to achieve enhanced operation of distribution system. The multi-objective optimization problem comprises three important objective functions such as minimization of total active power loss (p~(loss) total), reduction of voltage deviation and balancing of current through feeder sections. Design/methodology/approach - In this study, a hybrid configuration of weight improved particle swarm optimization (WIPSO) and gravitational search algorithm (GSA) called hybrid WIPSO-GSA algorithm is proposed in multi-objective problem domain. To solve multi-objective optimization problem, the proposed hybrid WIPSO-GSA algorithm is integrated with two components. The first component is fixed-sized archive that is responsible for storing a set of non-dominated pareto optimal solutions and the second component is a leader selection strategy that helps to update and identify the best compromised solution from the archive. Findings - The proposed methodology is tested on standard 33-bus and Indian 85-bus distribution systems. The results attained using proposed multi-objective hybrid WIPSO-GSA algorithm provides potential technical and economic benefits and its best compromised solution outperforms other commonly used multi-objective techniques, thereby making it highly suitable for solving multi-objective problems. Originality/value - A novel multi-objective hybrid WIPSO-GSA algorithm is proposed for optimal DG and capacitor planning in radial distribution network. The results demonstrate the usefulness of the proposed technique in improved distribution system planning and operation and also in achieving better optimized results than other existing multi-objective optimization techniques.
机译:目的-本文旨在通过同时优化多个相互冲突的运营目标来优化配电网中的分布式发电(DG)和电容器,从而实现配电系统的增强运行。多目标优化问题包括三个重要的目标函数,例如最小化总有功功率损耗(p〜(loss)total),减小电压偏差和平衡通过馈线部分的电流。设计/方法/方法-在本研究中,在多目标问题域中提出了一种加权改进的粒子群优化(WIPSO)和重力搜索算法(GSA)的混合配置,称为混合WIPSO-GSA算法。为了解决多目标优化问题,将提出的混合WIPSO-GSA算法与两个组件集成在一起。第一个组件是固定大小的存档,它负责存储一组非支配的pareto最佳解决方案,第二个组件是领导者选择策略,可帮助从存档中更新和识别最佳的妥协解决方案。调查结果-所建议的方法在标准的33总线和印度85总线配电系统上进行了测试。使用提出的多目标混合WIPSO-GSA算法获得的结果提供了潜在的技术和经济利益,其最佳折衷的解决方案优于其他常用的多目标技术,从而使其非常适合解决多目标问题。原创性/价值-提出了一种新颖的多目标混合WIPSO-GSA算法,用于径向配电网中的最佳DG和电容器规划。结果表明,与其他现有的多目标优化技术相比,所提出的技术在改进配电系统的规划和运营以及获得更好的优化结果方面是有用的。

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