A Lipschitz Optimization-Based MPPT Algorithm for Photovoltaic System Under Partial Shading Condition

• Published in: IEEE access Vol. 7; pp. 126323 - 126333
• Main Authors: Li, Wenfan, Zhang, Guogang, Pan, Tingzhe, Zhang, Zeyu, Geng, Yingsan, Wang, Jianhua
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Arrays; Convergence; Global maximum power point (GMPP); Integrated circuit modeling; Lipschitz optimization (LIPO); Maximum power point trackers; maximum power point tracking (MPPT); Maximum power tracking; Optimization; partially shaded condition (PSC); Particle swarm optimization; Photovoltaic cells; Photovoltaic systems; Shading
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2939095

The power-voltage curve of a photovoltaic (PV) array shows multiple power peaks under partially shading conditions (PSCs). Hence, conventional maximum power point tracking (MPPT) algorithms can not guarantee the maximum power output of the PV array. In this study, a novel Lipschitz optimization (LIPO) MPPT algorithm, which is effective under PSCs, is proposed and analyzed. Its tracking speed is very fast and tracking efficiency is above 98%. The characteristics of a PV array under PSCs are first analyzed and then the working principle of the proposed LIPO MPPT algorithm is explained. In order to validate the performance of the proposed algorithm, two popular MPPT algorithms, i.e., the modified particle swarm optimization (M-PSO) algorithm and the modified firefly optimization (M-firefly) algorithm, are chosen to compare with it. All three algorithms are fulfilled and compared with each other through both simulations and experiments and the results show that the proposed MPPT algorithm has good performance.