Optimum Design of a Photovoltaic Inverter System Based on Ga, Pso and Gwo Algorithms with a Mppt Sliding Mode Control

Alberto Coronado-Mendoza (), Mónica Camas-Náfate, Jesús Sergio Artal-Sevil and José Antonio Domínguez-Navarro
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Alberto Coronado-Mendoza: Studies on Water and Energy Department, University of Guadalajara, Tonala Campus, Nuevo Periferico Av. 555, Jalisco 45425, Mexico
Mónica Camas-Náfate: Studies on Water and Energy Department, University of Guadalajara, Tonala Campus, Nuevo Periferico Av. 555, Jalisco 45425, Mexico
Jesús Sergio Artal-Sevil: Department of Electrical Engineering EINA, University of Zaragoza, María de Luna 3, 50018 Zaragoza, Spain
José Antonio Domínguez-Navarro: Department of Electrical Engineering EINA, University of Zaragoza, María de Luna 3, 50018 Zaragoza, Spain

Energies, 2025, vol. 18, issue 8, 1-16

Abstract: The deployment of photovoltaic single-phase inverters has been rapidly increasing worldwide. However, the performance of these systems is highly influenced by atmospheric conditions and load variations, necessitating the development of performance indices to enhance their efficiency and energy quality. In this study, four performance indices are proposed to evaluate the efficiency and energy quality of photovoltaic systems quantitatively. The entire process is analyzed, encompassing solar energy capture, DC-DC and DC-AC conversion, and filtering, to deliver maximum energy and quality to the load. Furthermore, eight system parameters are optimized using advanced techniques such as genetic algorithms, particle swarm optimization, and gray wolf optimization. These optimizations enhance the global performance of two critical stages: (1) the maximum power point tracking algorithm based on sliding mode control, which minimizes switching losses in the boost stage, and (2) the effective transfer of captured solar power to the load by optimizing the gains of a PI controller. The PI controller computes the switching triggers for the inverter stage, significantly improving the total harmonic distortion of voltage and current waveforms. Simulation results validate the proposed approach, demonstrating a marked improvement in overall system efficiency (95.8%) when compared to the incremental conductance method (−11.8%) and a baseline sliding mode control configuration (−1.14%).

Keywords: single-phase photovoltaic inverter; sliding mode control; performance indexes; bioinspired optimization algorithms; global efficiency and energy quality (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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