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Optimal planning of RDGs in electrical distribution networks using hybrid SAPSO algorithm

机译:混合SAPSO算法的电气配电网络RDG的最佳规划

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The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA & PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA & PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.
机译:可再生分布代(RDG)(RDG)的影响,例如光伏(PV)和风力涡轮机(WT)系统可以基于DG的位置和大小对系统产生正面或负面。因此,分销网络中DG的正确位置和大小仍然是实现完全可能效益的障碍。因此,必须计划和操作具有高渗透功率的未来分销网络以提高其效率。因此,本文提出了一种新的具有电气配电网络可再生能源的DG单元的新方法。由于所提出的方法的主要目的是降低功率损耗并改善径向分布系统(RDS)的电压曲线。在这方面,使用损耗灵敏度因子(LSF),模拟退火(SA),粒子群优化(PSO)和SA&PSO(LSISA,LSIPSO)的损耗敏感性指数(LSI)的组合配制了优化问题。本文有助于一种新的方法SAPSO,这可以防止SA&PSO的缺陷。 33总线系统测试基于可再生能源的DG的最佳放置和尺寸。结果证明了所提出的SAPSO算法的可靠性和鲁棒性,以找到DG单元的近最优位置和大小,以减轻功率损耗并改善径向分布系统的电压曲线。

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