Using the gray wolf optimizer for solving optimal reactive power dispatch problem
Using the gray wolf optimizer for solving optimal reactive power dispatch problem
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DOI：
10.1016/j.asoc.2015.03.041
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发表时间：
2015-07
期刊：
影响因子：
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通讯作者：
M. Sulaiman;Z. Mustaffa;M. R. Mohamed;O. Aliman
中科院分区：
文献类型：
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作者：
M. Sulaiman;Z. Mustaffa;M. R. Mohamed;O. Aliman
本文提出了一种新的元启发式技术，即灰狼优化器（GWO），这是从灰狼的领导和狩猎行为的启发，以解决无功优化调度（ORPD）问题。ORPD问题是电力系统中一个著名的非线性优化问题。GWO用于找到控制变量的最佳组合，如发电机电压，分接头变换变压器的比率以及无功补偿装置的数量，以便可以实现损耗和电压偏差最小化。在本文中，两个案例研究的IEEE 30节点系统和IEEE 118节点系统被用来显示GWO技术的有效性相比，其他技术在文献中。研究结果表明，GWO能够实现比其他技术所确定的更小的功率损耗和电压偏差。
This paper presents the use of a new meta-heuristic technique namely gray wolf optimizer (GWO) which is inspired from gray wolves’ leadership and hunting behaviors to solve optimal reactive power dispatch (ORPD) problem. ORPD problem is a well-known nonlinear optimization problem in power system. GWO is utilized to find the best combination of control variables such as generator voltages, tap changing transformers’ ratios as well as the amount of reactive compensation devices so that the loss and voltage deviation minimizations can be achieved. In this paper, two case studies of IEEE 30-bus system and IEEE 118-bus system are used to show the effectiveness of GWO technique compared to other techniques available in literature. The results of this research show that GWO is able to achieve less power loss and voltage deviation than those determined by other techniques.