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Optimal deployment of renewable DG and battery storage system in distribution system considering techno-economic, environment and reliability aspects

机译:考虑技术经济,环境和可靠性方面的分配系统中可再生DG和电池存储系统的最佳部署

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In the present scenario of energy market restructuring and global warming incorporation of Renewable Distributed Generation (DG) in the distribution system is one of the efficient and viable strategies that can be adapted by the Distribution Companies (DISCO) for the overall benefit of the system. In this paper, a Non-Dominant Sorted Genetic Algorithm II (NSGA II) based multi-objective approach is developed for optimal deployment of DG to maximize voltage profile improvement, reliability, economic and environmental benefit. To address the issue of intermittence of renewable DG, Battery Storage System (BSS) is also used in the system. A new formula is proposed to evaluate the failure rate of the distribution line. Reliability indices such as Expected Energy not served (EENS) is used to assess the reliability of the network by the incorporation of DG. New and logical formulas such as Network voltage profile improvement index (NVPII), Benefit Cost Ratio (BCR), and Environmental Benefit Index (EBI) are formulated to assess the overall performance of the device The proposed method is tested on 33-bus radial system for time variant practical load models. The proposed technique when compared with other multi-objective algorithms shows good applicability and superior performance. This analysis facilitates the planning engineers to choose an optimal approach for the overall benefit of the system.
机译:在现有的能源市场的情况下,分配系统中可再生分布生成(DG)的全球变化融合(DG)是可由分销公司(迪斯科)为系统的整体利益而调整的有效和可行的策略之一。本文开发了一种非显着的分类遗传算法II(NSGA II)的多目标方法,以实现DG的最佳部署,以最大化电压型材改善,可靠性,经济和环境效益。为了解决可再生DG的间歇性问题,系统也使用电池存储系统(BSS)。提出了一种新的公式来评估分配线的故障率。不服务于预期能量(Eens)的可靠性指数用于通过掺入DG来评估网络的可靠性。新的和合乎逻辑的公式如网络电压分布的改善指数(NVPII),效益成本比(BCR),和环境效益指数(EBI)进行配制,以评估装置所提出的方法是在33客车子午线系统测试的整体性能用于时间变体实用负载模型。与其他多目标算法相比,所提出的技术显示出良好的适用性和优越的性能。该分析有助于规划工程师为系统的整体利益选择最佳方法。

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