Performance Assessment of Grey Wolf Technique for AGC of Multi-source Intertied System

Ahmed Nura Mohammed, Shamik Chatterjee
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Abstract

The ever growing demands, nonlinearity and intricacies associated with the power system together with strict requirement of system performing consistently well and numerous other changes that are occurring overtime in power system makes A GC study indispensable in order to discover and accommodates the changes for invention of futuristic ways of tackling emergent AGC problems. Hence, an important technique that demonstrates excellent performance in cracking complex engineering problems termed Grey wolf optimization (GWO) is deployed here for optimizing the parameters of the regulator (PID) used for AGC investigations of the power model (multi-source multi-area MSMA) considered. The transient response acquired with the technique was compared with other techniques that are known to be efficient and gives good result in the most recent literature of AGC study of the model considered. However, this comparison clearly indicate how GWO technique performance surpass the performance of these techniques. Also, the detailed sensitivity examination carry out to system manifest clearly the high robustness of the technique put forward here to randomness. Hence, the technique proved to be effective to the model applied in this study and can be recommended for modelling systems with same or similar specification as that given in this work.
灰狼技术在多源互联系统AGC中的性能评价
与电力系统相关的不断增长的需求、非线性和复杂性,以及对系统持续良好运行的严格要求,以及电力系统中不断发生的许多其他变化,使得GC研究必不可少,以便发现和适应这些变化,以发明解决紧急AGC问题的未来方法。因此,一项在解决复杂工程问题方面表现出色的重要技术——灰狼优化(GWO)被部署在这里,用于优化用于功率模型(多源多区域MSMA) AGC调查的调节器(PID)的参数。用该方法获得的瞬态响应与其他已知有效的方法进行了比较,并在最近的模型AGC研究文献中给出了良好的结果。然而,这种比较清楚地表明,GWO技术的性能如何超越这些技术的性能。同时,对系统进行了详细的灵敏度检验,表明本文提出的方法对随机性具有很高的鲁棒性。因此,该技术被证明对本研究中应用的模型是有效的,并且可以推荐用于与本工作中给出的规范相同或相似的系统建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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