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Research on adaptive niche differential evolution algorithm for reactive power optimization

机译:无功优化的自适应小生境差分进化算法研究

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Reactive power optimization which is the foundation for optimal control of voltage and reactive power is a very complex non-linear mixed integer programming problem. To deal with this optimization problem, an Adaptive Niche Differential Evolution algorithm (ANDE) is presented to avoid the premature phenomenon in DE. To maintain the population diversity, niche-sharing mechanism is adopted. To improve the rate of convergence, penalty function is used by niche-eliminating mechanism to deal with some low fitness individuals. To improve searching capability of algorithm, niching radius can also be adjusted adaptively on the basis of the relative distance between individuals which reflect the aggregation of population. Using the above method, the global searching ability of this algorithm could be improved. The proposed algorithm has been tested on IEEE-6, IEEE-30 and IEEE-118 bus systems and the calculation proves the effectiveness and practicability of the above algorithm.
机译:无功优化是电压和无功优化控制的基础,是一个非常复杂的非线性混合整数规划问题。为了解决这一优化问题,提出了一种自适应生态位差分进化算法(ANDE),以避免DE中的过早现象。为了维持人口多样性,采用了利基分享机制。为了提高收敛速度,利基消除机制使用惩罚函数来处理一些低适应度个体。为了提高算法的搜索能力,还可以根据反映种群聚集的个体之间的相对距离来自适应地调整小生境半径。使用上述方法,可以提高该算法的全局搜索能力。该算法已经在IEEE-6,IEEE-30和IEEE-118总线系统上进行了测试,计算结果证明了该算法的有效性和实用性。

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