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Determining the optimal setting of voltage regulators for day-ahead management of distribution smart systems

机译:确定用于配电智能系统的提前管理的稳压器的最佳设置

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Environmental pollution and greenhouse gas emissions, as well as oil depletion are prime motivators for the development and adoption of renewable power sources. However, the traditional operating philosophy of power systems and the random nature of these sources represent an important barrier for their massive deployment. Fluctuations of wind and solar power generation integrated as distributed sources can induce important variations on the voltage profile, leading to values out of the range typically suggested by power quality standards. To deal with this problem, in this paper the optimal setting of voltage regulators (VRs) at each hour has been optimally determined by implementing a genetic algorithm with integer codification, so that it can be effectively integrated with the load flow methodologies currently available in the literature without requiring any linearization process. Results obtained from the analysis of a case study reveal the behavior of the optimal VR settings and reactive power compensation on a daily basis, which are highly correlated with the daily load profile.
机译:环境污染和温室气体排放以及石油枯竭是开发和采用可再生能源的主要动力。但是,传统的电力系统运行原理和这些电源的随机性为大规模部署提供了重要的障碍。集成为分布式电源的风能和太阳能发电的波动会引起电压曲线的重要变化,从而导致其值超出电能质量标准通常建议的范围。为了解决这个问题,在本文中,通过实施带有整数编码的遗传算法,最优地确定了每个小时的电压调节器(VR)的最佳设置,以便可以将其有效地与当前可用的潮流方法集成在一起。不需要任何线性化过程的文献。通过案例分析获得的结果表明,每天最佳VR设置和无功功率补偿的行为与每日负荷曲线高度相关。

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