Photovoltaic MPPT Tracking under Partial Shading Based on ICS-IGSS-INC Hybrid Algorithm

• Published in: Engineering letters Vol. 33; no. 2; p. 215
• Main Authors: Liu, Tan, Yu, Hexu, Liu, Sisi, Tong, Jiaqi, Wu, Zhiyi, Yuan, Qingyun
• Format: Journal Article
• Language: English
• Published: Hong Kong International Association of Engineers 01.02.2025
• Subjects: Accuracy; Arrays; Control algorithms; Control methods; Control theory; Global optimization; Incremental conductance; Local optimization; Maximum power tracking; Optimization; Particle swarm optimization; Search algorithms
• ISSN: 1816-093X; 1816-0948

The P-V characteristic curve of a photovoltaic array exhibits several peaks in conditions of partial shade. Accurately tracking the Global Maximum Power Point (GMPP) of the complete photovoltaic system array is challenging since traditional Maximum Power Point Tracking (MPPT) methods frequently fall into the Local Maximum Power Points (LMPP). Although MPPT control methods based on intelligent optimization algorithms have been widely adopted to address this issue, balancing tracking accuracy and speed remains a challenging problem. A hybrid MPPT control strategy based on Improved Cuckoo Search-Golden Section Search in conjunction with the Incremental Conductance Method (ICS-IGSS-INC) is suggested in order to swiftly and precisely track the GMPP under partial shade conditions. The ICS algorithm is employed for global optimization, while IGSS and INC are used for local optimization, which enhances the accuracy and speed of the control algorithm. Simulation results indicate that compared with Particle Swarm Optimization (PSO), Cuckoo Search (CS), Improved Cuckoo Search (ICS), and Improved Cuckoo Search combined with Incremental Conductance (ICS-INC), the proposed ICS-IGSS-INC MPPT method significantly improves accuracy and speed, reduces power oscillations during tracking, and accurately tracks GMPP.