A conceptual framework and a Review of AI-Based MPPT Techniques for Photovoltaic Systems

Abstract Several Maximum Power Point Tracking (MPPT) techniques based on various Artificial Intelligence (AI) algorithms were recently developed due to the current availability of powerful computation controllers and adaptability of AI algorithms and their characteristic in handling non-linear problems. AI algorithms are perfectly suited to handle the problem of adverse conditions of rapid irradiance change and partial shading that the PV systems suffer. This paper presents a conceptual framework of the MPPT for photovoltaic systems and a comprehensive review of the current AI-based MPPT techniques. The paper also covers MPPT components, modeling, characteristics, affecting factors, and categories. The performance of different AI algorithms is evaluated and categorized based on many criteria including system complexity, tracking speed, cost, efficiency, accuracy, hardware implantation, sensory parameters, response to Partial Shading Conditions (PSC), etc. Finally, a summarizing comparison of performance of the main MPPT techniques is presented.