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Optimal operation of transmission power networks by using improved stochastic fractal search algorithm

机译:利用改进的随机分形搜索算法优化传输电网的优化操作

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This paper presents the application of an improved stochastic fractal search algorithm (ISFSA) for optimizing five single objectives of optimal power flow (OPF) problem and satisfying all constraints consisting of operating limits of electric components, power balance and load voltage magnitude limits. The proposed ISFSA is formed by implementing three improvements on the conventional stochastic fractal search algorithm (SFSA). The first improvement cancels one ineffective formula but keeps another one in diffusion process. The second improvement selects some worst solutions in the first update and some best solutions in the second update for producing new solutions. In the third improvement, a proposed technique is applied for carrying out the update processes. Comparisons of obtained results from three standard IEEE power systems indicate that the proposed method is superior to SFSA in terms of optimal solution quality, execution speed as well as success rate. The performance comparisons with other existing methods available in previous studies also lead to the conclusions that the proposed method can reach lower generation fuel cost, smaller total power losses, less amount of emission, better voltage profile and faster execution process. As a result, it can be recommended that the proposed ISFSA should be used for OPF problem in high-voltage power system field.
机译:本文介绍了改进的随机分数态搜索算法(ISFSA),以优化最佳功率流量(OPF)问题的五个单一目标,并满足由电气元件的操作限制,功率平衡和负载电压限制的所有约束。所提出的ISFSA是通过对传统随机分数态搜索算法(SFSA)的三种改进来形成。第一个改进取消一个无效的公式,但在扩散过程中保持另一个。第二种改进在第一次更新中选择了一些最糟糕的解决方案以及在第二次更新中选择了一些最佳解决方案,以产生新的解决方案。在第三种改进中,应用了一个提出的技术来执行更新过程。从最佳解决方案质量,执行速度以及成功率方面,三个标准IEEE电力系统的获得结果表明所提出的方法优于SFSA。与以前的研究中可用的其他现有方法的性能比较也导致所提出的方法可以达到较低的燃料成本,较小的总功率损耗,减少量,更好的电压曲线和更快的执行过程的结论。因此,可以建议建议的ISFSA用于高压电源系统领域的OPF问题。

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