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Genetic algorithm for weight assignment in optimum planning of multiple distributed generations to minimize energy losses

机译:遗传算法,用于在多个分布式发电的优化规划中分配权重,以最大程度地减少能量损失

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Renewable distributed generation (DG) is attracting special attention in order to meet the growing demand. Wind energy will drive rapid growth of distributed renewable energy systems in rural and remote areas worldwide. The one of the major potential benefits offered by DG concept is the reduction of total system losses. Because of the time-varying characteristics of both generation and load, energy loss minimization should be considered instead of power loss minimization. In this paper, a new and simple methodology is proposed to find optimal sizes and locations of DGs in order to minimize energy losses. This method is based on genetic algorithm and weighting factor. The effectiveness of proposed method is tested on the IEEE-30 bus mesh network. The results show that the proposed method is capable of finding the optimal sizing of DG to minimize energy losses for candidate DG buses.
机译:为了满足不断增长的需求,可再生分布式发电(DG)引起了人们的特别关注。风能将推动全球农村和偏远地区分布式可再生能源系统的快速增长。 DG概念所提供的主要潜在好处之一是减少系统总损耗。由于发电和负荷的时变特性,应考虑使能量损失最小化而不是使功率损失最小化。在本文中,提出了一种新的简单方法来寻找DG的最佳尺寸和位置,以最大程度地减少能量损失。该方法基于遗传算法和加权因子。该方法的有效性在IEEE-30总线网状网络上进行了测试。结果表明,所提出的方法能够找到最佳的DG尺寸,以最大程度地减少候选DG总线的能量损失。

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