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Optimal reconfiguration/distributed generation integration in distribution system using adaptive weighted improved discrete particle swarm optimization

机译:使用自适应加权改进离散粒子群算法的配电系统最优重构/分布式发电集成

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Purpose - This paper aims to address not only technical and economic challenges in electrical distribution system but also environmental impact and the depletion of conventional energy resources due to rapidly growing economic development, results rising energy consumption.Design/methodology/approach - Generally, the network reconfiguration (NR) problem is designed for minimizing power loss. Particularly, it is devised for maximizing power loss reduction by simultaneous NR and distributed generation (DG) placement. A loss sensitivity factor procedure is incorporated in the problem formulation that has identified sensitivity nodes for DG optimally. An adaptive weighted improved discrete particle swarm optimization (AWIDPSO) is proposed for ascertaining a feasible solution.Findings - In AWIDPSO, the adaptively varying inertia weight increases the possible solution in the global search space and it has obtained the optimum solution within lesser iteration. Moreover, it has provided a solution for integrating more amount of DG optimally in the existing distribution network (DN).Practical implications - The AWIDPSO seems to be a promising optimization tool for optimal DG placement in the existing DN, DG placement after NR and simultaneous NR and DG sizing and placement. Thus, a strategic balance is derived among economic development, energy consumption, environmental impact and depletion of conventional energy resources.Originality/value - In this study, a standard 33-bus distribution system has been analyzed for optimal NR in the presence of DG using the developed framework. The power loss in the DN has reduced considerably by indulging a new and innovative approaches and technologies.
机译:目的-本文旨在不仅解决配电系统中的技术和经济挑战,而且解决由于快速发展的经济而导致的环境影响和常规能源的枯竭,从而导致能耗的增加。设计/方法/方法-通常,网络重新配置(NR)问题旨在将功耗降至最低。特别地,其被设计用于通过同时进行NR和分布式发电(DG)布置来最大化功率损耗降低。问题公式中包含了损失敏感度因子程序,该过程已为DG确定了最佳敏感度节点。为了确定可行的解决方案,提出了一种自适应加权改进的离散粒子群算法(AWIDPSO)。发现-在AWIDPSO中,自适应变化的惯性权重增加了全局搜索空间中的可能解,并且在较小的迭代中获得了最优解。此外,它还提供了一种解决方案,可以将更多数量的DG最佳地集成到现有的配电网络(DN)中。实际意义-AWIDPSO似乎是一个有前途的优化工具,可用于在现有DN中优化DG放置,在NR后同时放置DG NR和DG的大小和位置。因此,在经济发展,能源消耗,环境影响和常规能源消耗之间取得了战略平衡。原始数据/价值-在本研究中,分析了标准33总线配电系统在存在DG的情况下优化NR的能力开发的框架。通过使用新的创新方法和技术,DN中的功率损耗已大大降低。

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