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Developing a multi-objective framework for planning studies of modern distribution networks

机译:为现代配电网络的规划研究开发多目标框架

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This paper presents a new framework for planning studies of modern distribution networks. Presence of electric vehicles (EVs) and various technologies of distributed generation (DG) technologies are considered in the studies as two upcoming events of the future systems. In this regard, place and capacity of DG units along with the reinforcement of distribution lines are determined running a multi-objective (MO) optimization algorithm. Total losses of the distribution network along with annualized cost of expansion plans including investment, operation and maintenance costs are introduced as the main criteria which should be optimized in the proposed framework. An effective Posteriori optimization tool, i. e. Non-Dominated Sorting Genetic Algorithm II (NSGAII) is borrowed to solve the attained optimization problem of the studies. The proposed planning procedure is implemented on a distribution test system (IEEE RBTS-BUS5) and the optimal solutions have been found which shows the applicability and effectiveness of proposed algorithm.
机译:本文为现代配电网络的规划研究提出了一个新的框架。在研究中,电动汽车(EV)和分布式发电(DG)的各种技术的存在被认为是未来系统的两个即将发生的事件。在这方面,运行多目标(MO)优化算法可确定DG单元的位置和容量以及配电线路的加固。引入分销网络的总损失以及包括投资,运营和维护成本在内的扩展计划的年度成本作为主要标准,应在建议的框架中对其进行优化。有效的后验优化工具,即e。借用非支配排序遗传算法II(NSGAII)来解决所研究的优化问题。所提出的计划程序是在分布式测试系统(IEEE RBTS-BUS5)上实现的,并且找到了表明所提出算法的适用性和有效性的最佳解决方案。

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