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

机译:开发一种多目标框架,用于现代分销网络规划研究

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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:本文为现代配送网络的规划研究提供了新的框架。在研究中考虑了作为未来系统的两个即将到来的事件,考虑了电动车辆(EVS)和分布式发电(DG)技术的各种技术。在这方面,确定DG单元的地点和容量随着多目标(MO)优化算法确定运行多目标(MO)优化算法的加强。分销网络的总损失以及包括投资,运营和维护成本在内的年化的扩展计划成本作为主要标准,应在拟议的框架中优化。一个有效的后验优化工具,i。 e。借用非主导的分类遗传算法II(NSGAII)来解决研究的达到研究的优化问题。建议的规划程序在分发测试系统(IEEE RBTS-BUS5)上实施,并发现了最佳解决方案,其显示了所提出的算法的适用性和有效性。

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