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Parallel Optimal Reactive Power Flow Based on Cooperative Co-Evolutionary Differential Evolution and Power System Decomposition

机译:基于协同进化微分进化和电力系统分解的并行最优无功潮流

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摘要

Differential evolution (DE) is a promising evolutionary algorithm for solving optimal reactive power flow problems, but it requires relatively large population to avoid premature convergence. In order to overcome this disadvantage, a novel decomposition and coordination method based on the cooperative co-evolutionary architecture and the voltage-var sensitivity-based power system decomposition technique is proposed and incorporated with DE in this paper. It is implemented with a three-level parallel computing topology on a PC-cluster. Based on the IEEE 118-bus system test case, the effectiveness of the proposed method has been verified by comparison with the parallel basic DE not using the decomposition and coordination technique
机译:差分进化(DE)是解决最佳无功潮流问题的一种有前途的进化算法,但它需要相对大量的资源来避免过早收敛。为了克服这一缺点,提出了一种基于协同协同进化架构和基于电压-电压灵敏度的电力系统分解技术的分解协调方法,并将其与DE结合起来。它通过PC群集上的三级并行计算拓扑实现。基于IEEE 118总线系统测试案例,通过与不使用分解和协调技术的并行基本DE进行比较,验证了该方法的有效性

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