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Reactive power optimization and voltage control using an improved genetic algorithm

机译:使用改进的遗传算法进行无功优化和电压控制

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This paper presents an improved dynamic genetic algorithm (IDGA) for reactive power optimization and voltage control. The problem is formulated as a mixed integer, nonlinear optimization problems considering both continuous and discrete control variables. The objective of optimization is minimizing active power losses while maintaining the quality of voltages. During evolution process, the crucial parameters, including mutation and crossover rate, are adjusted dynamically in order to get the optimal global solution. The IEEE standards 14 and 30 bus systems were used as test systems to demonstrate the applicability and efficiency of the proposed method. The results, compared with classical genetic algorithm and previous approaches reported in the literature, show that IDGA could find high-quality solutions with more reliability and efficiency.
机译:本文提出了一种改进的动态遗传算法(IDGA),用于无功优化和电压控制。该问题被公式化为混合整数,同时考虑了连续和离散控制变量的非线性优化问题。优化的目的是在保持电压质量的同时最大程度地减少有功功率损耗。在进化过程中,动态调整关键参数,包括变异和交叉率,以获得最佳的整体解。 IEEE标准14和30总线系统被用作测试系统,以证明所提出方法的适用性和效率。与经典遗传算法和文献中报道的先前方法相比,该结果表明IDGA可以找到具有更高可靠性和效率的高质量解决方案。

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