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Application of Hybrid PSOGSA to Reactive Power Optimization Problem

机译:混合PSOGSA在无功优化问题中的应用。

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With the increasing power demand, voltage fluctuations are to be controlled for a reliable and stable power system. On the same way voltage fluctuations create reactive power mismatch in the system. To overcome these conditions we have to perform reactive power optimisation that would balance the reactive power flow of the system. There are several methods and algorithms that serve best for this problem. Among which minimising the real power losses and voltage deviation yields balanced reactive power and for this purpose the most efficient soft computing techniques are used. This study deals with a new approach of hybridisation of two algorithms Particle Swarm Optimisation (PSO) and Gravitational Search Algorithm (GSA). The results are produced on standard IEEE30 bus system for the ORPD problem and prove the best from other algorithms.
机译:随着功率需求的增加,必须控制电压波动,以实现可靠且稳定的电源系统。以同样的方式,电压波动会在系统中造成无功功率失配。为了克服这些条件,我们必须执行无功功率优化,以平衡系统的无功功率。有几种方法和算法最能解决此问题。其中,最小化实际功率损耗和电压偏差可产生平衡的无功功率,为此,使用了最有效的软计算技术。这项研究提出了一种混合两种算法的新方法:粒子群优化(PSO)和引力搜索算法(GSA)。结果是针对ORPD问题在标准IEEE30总线系统上产生的,并通过其他算法证明是最好的。

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