Global Maximum Power Point Tracking of PV Arrays Under Partial Shading Conditions Using Improved PSO and PID Algorithm

• Published in: Chinese Automation Congress (Online) pp. 3003 - 3007
• Main Authors: Zhong, Ningfan, Zhang, Meng, Ma, Mingyuan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06.11.2020
• Subjects: Heuristic algorithms; Mathematical model; Maximum power point trackers; partial shadowing conditions(PSCs); particle swarm optimization(PSO) algorithm; Partitioning algorithms; Photovoltaic cells; Photovoltaic systems; PID algorithm; PV system; Shadow mapping
• ISSN: 2688-0938
• DOI: 10.1109/CAC51589.2020.9327619

Under the condition of partial shading, the output characteristic curve of the PV system will show a global maximum power peak(GMPP) and multiple local maximum power peaks(LMPP). Since the traditional method can only track GMPP, the traditional method will not be suitable for partial occlusion. Under the dynamic partial shadowing conditions (PSCs), using traditional methods to track dynamic GMPP will become more difficult. This paper proposes a compound control algorithm that combines improved particle swarm optimization (PSO) algorithm with PID algorithm. Based on the traditional PSO, this paper uses adaptive inertia weight to make the algorithm jump out of the LMPP and search for the GMPP quickly and accurately. Meanwhile, PID controller is used to reduce system overshoot and make the system more stable. Compared with the traditional PSO algorithm, the proposed method has better tracking effect under static and dynamic PSCs.