Research Article
A Hybrid MPPT Algorithm Based on DE-IC for Photovoltaic Systems Under Partial Shading Conditions
@INPROCEEDINGS{10.1007/978-3-031-33979-0_8, author={Rafaela D. Silveira and S\^{e}rgio A. O. da Silva and Leonardo P. Sampaio and Jose A. Afonso}, title={A Hybrid MPPT Algorithm Based on DE-IC for Photovoltaic Systems Under Partial Shading Conditions}, proceedings={Sustainable Energy for Smart Cities. 4th EAI International Conference, SESC 2022, Braga, Portugal, November 16-18, 2022, Proceedings}, proceedings_a={SESC}, year={2023}, month={5}, keywords={Photovoltaic System Maximum Power Point Tracking Differential Evolution Incremental Conductance}, doi={10.1007/978-3-031-33979-0_8} }- Rafaela D. Silveira
Sérgio A. O. da Silva
Leonardo P. Sampaio
Jose A. Afonso
Year: 2023
A Hybrid MPPT Algorithm Based on DE-IC for Photovoltaic Systems Under Partial Shading Conditions
SESC
Springer
DOI: 10.1007/978-3-031-33979-0_8
Abstract
This paper presents a hybrid maximum power point tracking (MPPT), which combines a metaheuristic algorithm and a traditional MPPT method applied in a photovoltaic system operating under partial shading conditions. The MPPTs based on traditional methods are not able to track the global maximum power point (GMPP) when partial shadings occur. Thus, MPPT algorithms based on metaheuristic algorithms, which are used for global optimization, have presented efficiency to extract the maximum power from photovoltaic arrays. However, these methods are random, resulting in large power oscillations in transients of small variations in solar irradiance. Therefore, this paper proposes the metaheuristic algorithm called Differential Evolution (DE) to seek and track the GMPP. After the DE convergence, the MPPT algorithm is switched to Incremental Conductance (IC) in order to refine the tracking. The effectiveness of the algorithm is proved through simulation results. Furthermore, comparative analyses are provided for each algorithm (DE and IC) to evaluate their performances in the PV system.
