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Optimal placement of non-site specific DG for voltage profile improvement and energy savings in radial distribution networks

机译:优化非现场特定DG的位置,以改善径向分布网络中的电压曲线并节省能源

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摘要

This paper proposes a model based on Fuzzy Genetic Algorithm (FGA) to determine the optimal capacity and location of a DG unit in a radial distribution network. In the FGA, a fuzzy controller is integrated into GA to adjust the crossover and mutation rates dynamically to maintain the proper population diversity during GA's operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The main objective functions considered in this study are maximisation of cost savings arising from energy loss, minimisation of voltage drops across all lines, and maximisation of the transfer capability of the system. The model takes into account the peculiarities of radial distribution networks, such as high R/X ratio, voltage dependency and composite nature of loads. The proposed model is evaluated on three radial test distribution systems, and the results obtained are very impressive, with high computational efficiency, when compared with those of the existing approaches cited in the literature.
机译:本文提出了一种基于模糊遗传算法(FGA)的模型,用于确定径向分布网络中DG机组的最佳容量和位置。在FGA中,模糊控制器已集成到GA中,可以动态调整交叉和变异率,以在GA运作期间维持适当的种群多样性。这有效地克服了简单遗传算法(SGA)的过早收敛问题。本研究中考虑的主要目标功能是:最大程度地减少因能量损失而产生的成本节省,最小化所有线路上的电压降以及最大程度地提高系统的传输能力。该模型考虑了径向配电网的特殊性,例如高的R / X比,电压依赖性和负载的复合特性。所提出的模型是在三个径向测试分布系统上进行评估的,与文献中引用的现有方法相比,所获得的结果令人印象深刻,计算效率很高。

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