Jellyfish Search Optimization Algorithm for MPP Tracking of PV System

Afroz Alam, Preeti Verma, Mohd Tariq, Adil Sarwar, Basem Alamri, Noore Zahra and Shabana Urooj
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Afroz Alam: Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India
Preeti Verma: Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India
Mohd Tariq: Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India
Adil Sarwar: Department of Electrical Engineering ZHCET, Aligarh Muslim University, Aligarh 202002, India
Basem Alamri: Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia
Noore Zahra: Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia
Shabana Urooj: Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh 84428, Saudi Arabia

Sustainability, 2021, vol. 13, issue 21, 1-20

Abstract: Because of the rapid increase in the depletion rate of conventional energy sources, the energy crisis has become a central problem in the contemporary world. This issue opens the gateway for exploring and developing renewable energy sources to fulfill the exigent energy demand. Solar energy is an abundant source of sustainable energy and hence, nowadays, solar photovoltaic (PV) systems are employed to extract energy from solar irradiation. However, the PV systems need to work at the maximum power point (MPP) to exploit the highest accessible power during varying operating conditions. For this reason, maximum power point tracking (MPPT) algorithms are used to track the optimum power point. Furthermore, the efficient utilization of PV systems is hindered by renowned partial shading conditions (PSC), which generate multiple peaks in the power-voltage characteristic of the PV array. Thus, this article addresses the performance of the newly developed jellyfish search optimization (JSO) strategy in the PV frameworks to follow the global maximum power point (GMPP) under PSC.

Keywords: jellyfish search optimization; maximum power point tracking; partial shading condition; particle swarm optimization; photovoltaic systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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