A robust controlling and management of load with minimum frequency and voltage deviation in network employing genetic algorithm

A. Saxena, Arun Sharma, Mohd Majid
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Abstract

Abstract In this work optimal autonomous controlling of frequency and voltage deviation of the power system network has been presented. The frequency deviations and the voltage fluctuations are assessed with conventional and genetic algorithm method. Initial model of power system network has been developed which is based on Tie line power flow. There were several unknown parameters observed in the objective functions of conventional tie line power method. These unknown parameters were trained with genetic algorithm. The genetic algorithm consist of three major steps: reproduction, crossover, and mutations. The suitable value of frequency and voltage deviations are obtained for various loading conditions. But due loading conditions, high value of transient or peak overshoot and settling time were attained for frequency and voltage variations. It is observed that optimal minimum value of peak overshoot and settling time for frequency and voltage deviations are attained with genetic algorithm in comparison to conventional methods.
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利用遗传算法对电网中频率和电压偏差最小的负荷进行鲁棒控制和管理
摘要本文研究了电网频率和电压偏差的最优自治控制问题。采用常规算法和遗传算法对频率偏差和电压波动进行了评估。建立了基于电网潮流的电力系统网络初始模型。传统的联机功率法在目标函数中观察到多个未知参数。利用遗传算法对这些未知参数进行训练。遗传算法包括三个主要步骤:繁殖、交叉和突变。在不同的负载条件下,得到了合适的频率和电压偏差值。但由于负载条件的限制,频率和电压变化的暂态超调量或峰值超调量和稳定时间都很高。结果表明,与传统方法相比,遗传算法能获得频率偏差和电压偏差的最优过峰值和稳定时间。
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