Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2024.2388445
An innovative maximum power point tracking for photovoltaic systems operating under partially shaded conditions using Grey Wolf Optimization algorithm
Muhannad J. Alshareef
; Department of Electrical Engineering, College of Engineering and Computing in Al-Qunfudhah, Umm Al-Qura University, Mecca, Saudi Arabia
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* Dopisni autor.
Sažetak
Partial shading conditions (PSCs) may be unpredictable and difficult to forecast in large-scale
solar photovoltaic (PV) systems. Potentially degrading the PV system’s performance results from
numerous peaks in the P–V curve caused by PSC. On the other hand, the PV system must be
run at its maximum power point (GMPP) to maximize its efficiency. Swarm optimization strategies have been employed to detect the GMPP; however, these methods are associated with an
unacceptable amount of time to reach convergence. In this research, an innovative grey wolf
optimization, abbreviated as NGWO, is presented as a solution to overcome the shortcomings
of the standard GWO method, which includes long conversion times, a rate of failure, and large
oscillations in a steady-state condition. This paper seeks to address these issues and fill a gap
in research by enhancing the GWO’s performance in tracking GMPP. The original GWO is modified to incorporate the Cuckoo Search (CS) abandoned process to shorten the time it takes for
effective adoption. Based on the simulation finding, the proposed IGWO method beats other
algorithms in most circumstances, particularly regarding tracking time and efficiency, where the
average tracking time is 0.19s, and the average efficiency is 99.86%.
Ključne riječi
Grey wolf optimization (GWO); global maximum power point tracking (GMPPT); partial shading conditions (PSCs); photovoltaic (PV) system
Hrčak ID:
326341
URI
Datum izdavanja:
8.9.2024.
Posjeta: 0 *