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A simple and fast load flow algorithm for sizing and placement of DG in radial distribution system

机译:一种用于径向分配系统中DG的大小和位置的简单快速潮流算法

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摘要

Rapid depletion of fossil based oil, coal and gas reserves and its greater demand day by day necessitates the search for other alternatives. Severe environmental impacts caused by the fossil fuel based power plants and the escalating fuel costs are the major challenges faced by the electricity supply industry. Integration of Distributed Generators (DG) especially, wind and solar systems to the grid can offer viable solutions to address these challenges. This paper focuses on a new simple and fast load flow algorithm for finding the voltage profile and power losses in a radial distribution system (RDS). Backward Forward Sweep Algorithm (BFSA) has been practiced to find the voltage profile and power losses with the integration of various size of DG at different locations. Genetic Algorithm (GA) based BFSA is adopted in finding the optimal location and sizing of DG to attain an improved voltage profile and considerable reduced power loss. Simulation results show that the proposed algorithm is more efficient in finding the optimal location and sizing of DG in 15-bus radial distribution system. The obtained results are compared with the system modeled in Simulink.
机译:基于化石的石油,煤炭和天然气储量的迅速枯竭及其日益增长的需求使得有必要寻找其他替代品。基于化石燃料的发电厂造成的严重环境影响以及不断上涨的燃料成本是电力供应行业面临的主要挑战。尤其是将分布式发电机(DG)集成到风能和太阳能系统中,可以提供可行的解决方案来应对这些挑战。本文关注于一种新的简单快速的潮流算法,该算法可找到径向分布系统(RDS)中的电压曲线和功率损耗。已经实践了向后正向扫描算法(BFSA)来查找电压分布和功率损耗,并在不同位置集成了各种大小的DG。采用基于遗传算法(GA)的BFSA来确定DG的最佳位置和大小,以实现改进的电压曲线并显着降低功率损耗。仿真结果表明,所提出的算法在15总线径向配电系统中寻找DG的最佳位置和大小更有效。将获得的结果与Simulink中建模的系统进行比较。

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