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An Evolution Strategy With Stochastic Ranking For Solving Reactive Power Optimization

机译:具有随机排名的进化策略,用于解决无功优化

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This paper presents an algorithm for solving reactive power optimization problem through the application of Evolution Strategy (ES) with stochastic ranking. In order to better improve the optimization performance and practicality, the coding method for integer data of transformer tap position is designed deliberately and the self-adaptive optimization termination condition based on variance is also presented. Under simulated conditions, the proposed method has been tested on IEEE-14 and IEEE-118 bus systems. The optimal reactive power results obtained using improved ES are compared with initial power loss. It is shown that our strategy can decrease respectively nearly 4.43% and 4.3% of initial loss.
机译:本文通过应用随机排名,介绍了一种通过应用演化策略来解决无功功率优化问题的算法。为了更好地提高优化性能和实用性,设计了变压器抽头位置整数数据的编码方法,刻意设计了基于方差的自适应优化终止条件。在模拟条件下,所提出的方法已经在IEEE-14和IEEE-118总线系统上进行了测试。使用改进的ES获得的最佳无功功率结果与初始功率损耗进行比较。结果表明,我们的策略可分别降低初始损失的近4.43%和4.3%。

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