Comparative evaluation of photovoltaic MPP trackers: A simulated approach

• Main Authors: Barnam Jyoti Saharia, Munish Manas, Bani Kanta Talukdar
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2016-12-01
• Series: Cogent Engineering
• Subjects: pv; boost converter; perturb and observe; fuzzy logic; neural networks; tracking factor
• Online Access: http://dx.doi.org/10.1080/23311916.2015.1137206

This paper makes a comparative assessment of three popular maximum power point tracking (MPPT) algorithms used in photovoltaic power generation. A 120 Wp PV module is taken as reference for the study that is connected to a suitable resistive load by a boost converter. Two profiles of variation of solar insolation at fixed temperature and varying temperature at fixed solar insolation are taken to test the tracking efficiency of three MPPT algorithms based on the perturb and observe (P&O), Fuzzy logic, and Neural Network techniques. MATLAB/SIMULINK simulation software is used for assessment, and the results indicate that the fuzzy logic-based tracker presents better tracking effectiveness to variations in both solar insolation and temperature profiles when compared to P&O technique and Neural Network-based technique.