Improved Load Frequency Control in Power Systems Hosting Wind Turbines by an Augmented Fractional Order PID Controller Optimized by the Powerful Owl Search Algorithm

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Algorithms Pub Date : 2023-11-25 DOI:10.3390/a16120539
F. Amiri, Mohsen Eskandari, Mohammad Hassan Moradi
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引用次数: 0

Abstract

The penetration of intermittent wind turbines in power systems imposes challenges to frequency stability. In this light, a new control method is presented in this paper by proposing a modified fractional order proportional integral derivative (FOPID) controller. This method focuses on the coordinated control of the load-frequency control (LFC) and superconducting magnetic energy storage (SMES) using a cascaded FOPD–FOPID controller. To improve the performance of the FOPD–FOPID controller, the developed owl search algorithm (DOSA) is used to optimize its parameters. The proposed control method is compared with several other methods, including LFC and SMES based on the robust controller, LFC and SMES based on the Moth swarm algorithm (MSA)–PID controller, LFC based on the MSA–PID controller with SMES, and LFC based on the MSA–PID controller without SMES in four scenarios. The results demonstrate the superior performance of the proposed method compared to the other mentioned methods. The proposed method is robust against load disturbances, disturbances caused by wind turbines, and system parameter uncertainties. The method suggested is characterized by its resilience in addressing the challenges posed by load disturbances, disruptions arising from wind turbines, and uncertainties surrounding system parameters.
利用强大的猫头鹰搜索算法优化的增量分数阶 PID 控制器改进风力涡轮机所在电力系统的负载频率控制
间歇性风力涡轮机在电力系统中的普及给频率稳定性带来了挑战。有鉴于此,本文提出了一种新的控制方法,即改进型分数阶比例积分导数(FOPID)控制器。该方法侧重于使用级联 FOPD-FOPID 控制器对负载频率控制 (LFC) 和超导磁能存储 (SMES) 进行协调控制。为提高 FOPD-FOPID 控制器的性能,采用了开发的猫头鹰搜索算法 (DOSA) 来优化其参数。在四种情况下,将所提出的控制方法与其他几种方法进行了比较,包括基于鲁棒控制器的 LFC 和 SMES、基于飞蛾群算法 (MSA) -PID 控制器的 LFC 和 SMES、基于 MSA-PID 控制器的 LFC 和 SMES,以及基于 MSA-PID 控制器的 LFC(无 SMES)。结果表明,与上述其他方法相比,提议的方法性能更优。建议的方法对负载扰动、风力涡轮机引起的扰动和系统参数不确定性具有鲁棒性。所建议的方法在应对负载扰动、风力涡轮机造成的干扰和系统参数不确定性带来的挑战方面具有很强的适应性。
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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来源期刊
Algorithms
Algorithms Mathematics-Numerical Analysis
CiteScore
4.10
自引率
4.30%
发文量
394
审稿时长
11 weeks
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