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Nature Inspired Computing Techniques for Optimal Reactive Power Dispatch

机译:最佳无功分配的自然灵感计算技术

摘要

This paper presents the application of recent nature inspired computing techniques namely gray wolf optimizerud(GWO) and ant lion optimizer (ALO) in solving optimal reactive power dispatch (ORPD) problem. GWO and ALO areudutilized to minimize the transmission losses by finding the best combination of control variables such as generator voltages, transformer tap ratios as well as reactive compensation devices. In this paper, IEEE 30-bus system is utilized to show these techniques in solving ORPD. The comparison between the effectiveness of GWO and ALO are made and reported in this paper. The results show that GWO is able to gain a better result in solving ORPD than ALO.
机译:本文介绍了最新的自然启发计算技术,即灰狼优化器 ud(GWO)和蚁狮优化器(ALO)在解决最优无功分配(ORPD)问题中的应用。通过找到控制变量(例如发电机电压,变压器抽头比率和无功补偿装置)的最佳组合,可以充分利用GWO和ALO来最大程度地降低传输损耗。在本文中,IEEE 30总线系统被用来展示这些技术来解决ORPD。本文对GWO和ALO的有效性进行了比较和报告。结果表明,与ALO相比,GWO能够更好地解决ORPD。

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