A Comprehensive Evaluation of Up-to-Date Optimization Algorithms on MPPT Application for Photovoltaic Systems

ABSTRACT

Maximum Power Point Tracking (MPPT) plays a significant role in obtaining maximum power at PV system outputs. Recent research has focused on minimizing the adverse effects of partial shading and dynamic environmental conditions on MPPT. Metaheuristic optimization algorithms have attracted attention with their success in these issues. The growing body of literature lacks a study that comprehensively evaluates current metaheuristic algorithms. In this study, the performances of 20 metaheuristic algorithms under five different shading conditions, nonuniform temperature distribution, and variable irradiance conditions have been investigated. The successes of the algorithms in the convergence of the global maximum value and their convergence rates have been calculated through various statistical metrics with different aspects. This study provides a novel approach to objectively evaluating the performances of the algorithms by using the three-dimensional Pareto Front method. As the result of this multicriteria evaluation, RKO, MPA and CGO algorithms are able to provide non-dominated results. These three algorithms are further tested using case analysis designed for dynamic operating conditions, and the RKO algorithm exhibited the most favorable results. Additionally, the RKO algorithm exhibits remarkable performance by reaching the LMPP/GMPP point within an average time of 3.2 milliseconds in all cases. Moreover, it demonstrates an average efficiency value exceeding 0.999.

KEYWORDS:

• MPPT
• PV systems
• Meta-heuristic algorithms
• Runge-kutta algorithm
• Optimization

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials.

Supplementary Material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15567036.2023.2245771

Additional information

Notes on contributors

Murat Cikan

Murat Cikan received a B.Sc. degree in Electrical Engineering from Yildiz Technical University, Turkey. He obtained his first MSc, second MSc, and PhD degrees in Electrical Engineering from the Polytechnic Institute of New York University, New York, USA, Drexel University, Philadelphia, USA, and the Department of Electrical Engineering, Yildiz Technical University, Istanbul, Turkey, respectively. Currently, Dr Cikan is an academician at Cukurova University Adana Organized Industrial Region Vocational School Technical Sciences. His research interests include power system analysis, power system optimization, reconfiguration, and dc-dc converters.

Kadir Dogansahin

Kadir Dogansahin is an assistant professor in Artvin Coruh University. He received BSc in Electrical Engineering Department in Yıldız Technical University. His MSc degree is from College of Engineering at University of Texas at San Antonio. He received PhD degree from Electrical Engineering Department in Yıldız Technical University. His research interests are power distribution systems, power quality and photovoltaic systems.