Comparative evaluation of photovoltaic MPP trackers: A simulated approach. Issue 1 (31st December 2016)

• Record Type: Journal Article
• Authors: Saharia, Barnam Jyoti; Manas, Munish; Talukdar, Bani Kanta
• Editors: Chen, Kun
• Is Part Of: Cogent engineering. Volume 3:Issue 1(2016)
• Publication Date: 2016-12-31
• Subjects: PV -- boost converter -- perturb and observe -- fuzzy logic -- neural networks -- tracking factor; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2015.1137206
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: 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.