Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

IF 2 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI:10.32604/cmc.2022.023588
Waleed Rafique, Ayesha Khan, Ahmad S. Almogren, J. Arshad, Adnan Yousaf, Mujtaba Hussain Jaffery, Ateeq Ur Rehman, Muhammad Shafiq
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引用次数: 5

Abstract

: An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for an instantaneous reactive and active current (I d -I q ) and power theory (Pq0) in SIMULINK. To prevent the degradation effect of disturbances on the system’s
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基于粒子群优化的自适应模糊控制器谐波抑制
:工业中过多使用非线性器件会产生电流谐波,从而降低电能质量,对电力系统的性能产生不利影响。在本研究中,通过改善系统的功率因数(PF)和总激素失真(THD)以及系统性能,实现了一种基于混合有源功率滤波器(HAPF)的新型控制技术,用于平衡负载的无功补偿和谐波电流分量。本文提出了一种基于粒子群优化(PSO)和自适应模糊技术的软计算技术,以避免传统控制方法引起的相位延迟。此外,在SIMULINK中实现了瞬时无功和有功电流(I d -I q)和功率理论(Pq0)的控制算法。防止扰动对系统的退化效应
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来源期刊
Cmc-computers Materials & Continua
Cmc-computers Materials & Continua 工程技术-材料科学:综合
CiteScore
5.30
自引率
19.40%
发文量
345
审稿时长
1 months
期刊介绍: This journal publishes original research papers in the areas of computer networks, artificial intelligence, big data management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, data analysis, modeling, and engineering of designing and manufacturing of modern functional and multifunctional materials. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.
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