Adaptable Algorithm for Tracking Global Maximum Power Point of Photovoltaic Module Arrays

• Published in: Sensors and materials Vol. 35; no. 12; p. 4359
• Main Authors: Chao, Kuei-Hsiang, Kuo, Ying-Piao, Chen, Hong-Han
• Format: Journal Article
• Language: English
• Published: Tokyo MYU Scientific Publishing Division 01.01.2023
• Subjects: Algorithms; Arrays; Electric potential; Maximum power tracking; Peak values; Photovoltaic cells; Switching; Voltage
• ISSN: 0914-4935; 2435-0869; 2435-0869
• DOI: 10.18494/SAM4645

The main objective of this study was to develop a method for the maximum power point tracking (MPPT) of photovoltaic module arrays (PVMAs) implemented using two proposed improved grey wolf optimization algorithms (GWOAs). A high-step-up soft-switching converter combined with lost-cost voltage and current sensors was adopted to realize MPPT. This reduced the converter switching losses and cost. Furthermore, in the improved GWOAs, iteration parameters were automatically adjusted online on the basis of the slope of the power–voltage (P–V) curve of the PVMA. In addition, 0.8 times the maximum power point (MPP) voltage of the PVMAs under standard test conditions was set as the starting voltage for conducting global MPPT. Lastly, by verifying the proposed improved GWOAs with actual test results, where multiple peak values were generated in the P–V characteristic curve of the PVMA by shading, we demonstrated that all MPPs could be tracked successfully, and the two improved GWOAs reduced the tracking time by at least 18.6 and 33.3% compared with that of the conventional GWOA. Therefore, the improved GWOAs exhibit superior tracking speed and stability.