Two fast metaheuristic-based MPPT techniques for partially shaded photovoltaic system. (May 2022)

• Record Type: Journal Article
• Authors: Moghassemi, Ali; Ebrahimi, Shayan; Padmanaban, Sanjeevikumar; Mitolo, Massimo; Holm-Nielsen, Jens Bo
• Is Part Of: International journal of electrical power & energy systems. Volume 137(2022)
• Publication Date: 2022-05
• Subjects: PV -- MPPT technique -- WOADE -- IWOADE -- Tracking speed -- Tracking efficiency; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.107567
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Two metaheuristic algorithms for improvement of the MPPT technique are presented. The first MPPT method is based on WOA and DE, called the WOADE-MPPT technique. The second MPPT method, IWOADE-MPPT, is an improvement of the WOADE. IWOADE-MPPT technique outperforms all traditional MPPT techniques. Five various shading patterns are studied to analyze the proposed MPPT technique. Abstract: The photovoltaic output power varies according to the solar radiation and ambient temperature because the operation of the photovoltaic arrays depends on them. Therefore, achieving the maximum photovoltaic power under different shading patterns is a key factor in the performance improvement of photovoltaic systems. An efficient Maximum Power Point Tracking technique is needed to distinguish the global maximum power point from the local ones, as the traditional techniques are prone to fail. This paper proposes two hybrid meta-heuristic algorithms to improve the maximum power point tracking technique of partially shaded photovoltaic systems. The first proposed maximum power point tracking technique is based on the Whale Optimization Algorithm and Differential Evolution algorithms. The second proposed maximum power point tracking technique is an improved version of the first proposed technique. Both proposed techniques are highly proficient in enhancing the photovoltaic system's efficiency in shaded and unshaded conditions. The maximum power point tracking technique is studied for evaluating the performance based on two traditional algorithms, Whale Optimization Algorithm and Differential Evolution, and two hybrid proposed algorithms. The simulation results show the second proposed maximum power point tracking technique finds the global power points faster and offers better performance than the first proposed technique, which itself outperforms two traditional maximum power point tracking techniques concerning a faster rate of convergence and higher efficiency.