Classification and Evaluation Review of Maximum Power Point Tracking Methods

• Published in: Sustainable futures Vol. 2; p. 100020
• Main Authors: Baba, Ali Omar, Liu, Guangyu, Chen, Xiaohui
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2020; Elsevier
• Subjects: Advanced; Classification; Comparison; Conventional; Evaluation; Soft computing; Tracking, MPPT; Tracking, MPPT; Evaluation; Advanced; Comparison; Classification; Soft computing; Conventional
• ISSN: 2666-1888; 2666-1888
• DOI: 10.1016/j.sftr.2020.100020

Photovoltaic (PV) systems have witnessed a rapid increment, the yield mainly relies on the working condition. In most cases, it is hard to obtain the optimal yield. Therefore, Maximum Power Point Tracking (MPPT) controllers witness much attention as an important optimization field of PV systems. These controllers employ different algorithms and they vary in their efficiency, performance, modernity, complexity, and tracking speed. MPPT controllers have witnessed a rapid improvement, they can be generally classified as conventional and advanced methods. Conventional methods are relatively simple but they can't distinguish between the local and global peaks if partial shading occurs, therefore, their efficiency is relatively low. Advanced tracking methods are widely used due to their superior efficiency. Due to the limitation of the singular conventional and advanced methods, hybrid methods find their way to solve these limitations. Selecting the finest MPPT method is still an open issue, this issue can be solved by implementing a survey of the applied methods. This study gives a concise classification and evaluation review of all the applied MPPT methods. This study also provides an accessible reference to undertake mass research works in MPPT in the near future.