A comparative analysis of bio- inspired optimization algorithms for Optimal Reactive Power Dispatch

Kevin Steven Morgado Gómez, Néstor Germán Bolívar Pulgarín
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Abstract

In this paper, it is developed an analysis of the usage of meta-heuristic models inspired by nature to obtain the Optimal Reactive Power Dispatch of a 30 bus system. Firstly, the obj ective function is presented, considering its power flow parameters. Afterward, the main algorithms were introduced the Grey Wolf Optimization (GWO), its improved version (1-GWO), and the Whale Optimization Algorithm (WOA). Then, they were implemented on the IEEE 30 bus system to calculate the obj ective function with 13 decision variables and 7 restrictions. Finally, the main results were presented, where it is highlighted an improvement in the Objective Function of 0.45%, in comparison with the traditional Optimal Power Flow implemented in Matpower.
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无功最优调度的仿生优化算法比较分析
本文分析了利用自然启发的元启发式模型求解某30母线系统的最优无功调度问题。首先,考虑其潮流参数,给出了目标函数;随后介绍了主要算法灰狼优化算法(GWO)及其改进版本(1-GWO)和鲸鱼优化算法(WOA)。然后在IEEE 30总线系统上实现,计算出具有13个决策变量和7个约束条件的目标函数。最后,给出了主要结果,其中强调了与传统的Matpower实现的最优潮流相比,目标函数的改进为0.45%。
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