Open AccessExperimental evaluation of a partially shaded photovoltaic system with a fuzzy logic‐based peak power tracking control strategy
Author(s) -
Shah Nilesh,
Rajagopalan Chudamani
Publication year - 2016
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2015.0098
Subject(s) - duty cycle , photovoltaic system , maximum power point tracking , robustness (evolution) , computer science , fuzzy logic , maximum power principle , control theory (sociology) , voltage , power (physics) , tracking (education) , algorithm , engineering , electrical engineering , inverter , control (management) , artificial intelligence , psychology , pedagogy , physics , quantum mechanics , biochemistry , chemistry , gene
Partial shading on photovoltaic (PV) array makes the task of operating the PV system at its peak power more complex due to multiple peak points on power–voltage ( P–V ) characteristic. Amongst multiple peaks, it is challenging to find global peak as there is a possibility of the system getting stuck at a local peak otherwise considerable loss of power may occur. In this study, experimental evaluation of a novel algorithm which tracks global peak is presented. The algorithm is capable of tracking the peak power under all partial shadowing and uniformly varying insolation conditions. The algorithm scans the entire P–V curve in larger steps by varying the duty cycle of DC–DC converter without missing any peak to determine approximate location of peak power point and then uses fuzzy logic to track the real global peak. The algorithm is verified through simulation and the results are validated through hardware implementation using TMS320F28335 digital signal processor. The experimental results match with the simulation results that justify the performance and robustness of the proposed algorithm for tracking global peak power when the PV array is partially shaded. The comparative evaluation of the proposed algorithm with conventional perturb and observe‐based method is also carried out experimentally.