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Embedding quasi-static time series within a genetic algorithm for stochastic optimization: the case of reactive power compensation on distribution systems
Journal of Computational Design and Engineering ( IF 4.8 ) Pub Date : 2020-04-02 , DOI: 10.1093/jcde/qwaa016
Juan M Lujano-Rojas 1, 2 , Ghassan Zubi 3 , Rodolfo Dufo-López 4 , José L Bernal-Agustín 4 , José L Atencio-Guerra 5 , João P S Catalão 6
Affiliation  

This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required.

中文翻译:

在遗传算法中嵌入准静态时间序列以进行随机优化:配电系统无功补偿的情况

本文提出了一种在具有分布式发电的配电系统(DS)中无功功率补偿装置的最佳放置和尺寸确定方法。在基于遗传算法的优化方法中嵌入了准静态时间序列,以充分表示太阳能光伏发电和电力需求带来的不确定性及其对DS运行的影响。通过对典型DS的分析,与经典遗传算法模型相比,无功补偿额定功率增加了24.9%。但是,准静态时间序列分析的引入使所需的计算时间增加了26.8%。
更新日期:2020-04-02
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