4.7 Article

Hybrid Gravitational-Firefly Algorithm-Based Load Frequency Control for Hydrothermal Two-Area System

期刊

MATHEMATICS
卷 9, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/math9070712

关键词

load frequency control; automatic generation control; controllers; optimization techniques; multisource power system; interconnected power system; hybrid gravitational with fire fly algorithm; gravitational search algorithm; firefly algorithm

资金

  1. King Mongkut's University of Technology North Bangkok [KMUTNB-BasicR-64-17]
  2. University of Lorraine [KMUTNB-BasicR-64-17]

向作者/读者索取更多资源

The performance analysis of a two-area power system is conducted based on LFC and tie-line power metrics, with a focus on the relationship between load frequency, tie-line power, generation capacity, and load. A PI controller is designed for evaluation, with hGFA used for parameter tuning. Deviations in generation and load capacity can impact load frequency and tie-line power, affecting the operation of the power system.
The load frequency control (LFC) and tie-line power are the key deciding factors to evaluate the performance of a multiarea power system. In this paper, the performance analysis of a two-area power system is presented. This analysis is based on two performance metrics: LFC and tie-line power. The power system consists of a thermal plant generation system and a hydro plant generation system. The performance is evaluated by designing a proportional plus integral (PI) controller. The hybrid gravitational search with firefly algorithm (hGFA) has been devised to achieve proper tuning of the controller parameter. The designed algorithm involves integral time absolute error (ITAE) as an objective function. For two-area hydrothermal power systems, the load frequency and tie-line power are correlated with the system generation capacity and the load. Any deviation in the generation and in the load capacity causes variations in the load frequencies, as well as in the tie-line power. Variations from the nominal value may hamper the operation of the power system with adverse consequences. Hence, performance of the hydrothermal power system is analyzed using the simulations based on the step load change. To elucidate the efficacy of the hGFA, the performance is compared with some of the well-known optimization techniques, namely, particle swarm optimization (PSO), genetic algorithm (GA), gravitational search algorithm (GSA) and the firefly algorithm (FA).

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据