Study and analysis of partial shading effect on power production of a photovoltaic string controlled by three different MPPT techniques: P&O, PSO and ANN

2024;
: pp. 856–869
https://doi.org/10.23939/mmc2024.03.856
Received: January 05, 2024
Revised: September 04, 2024
Accepted: September 06, 2024

Atillah M. A., Stitou H., Boudaoud A., Aqil M., Hanafi A.  Study and analysis of partial shading effect on power production of a photovoltaic string controlled by three different MPPT techniques: P&O, PSO and ANN.  Mathematical Modeling and Computing. Vol. 11, No. 3, pp. 856–869 (2024)

1
Engineering and Applied Physics Team (EAPT), Superior School of Technology, Sultan Moulay Slimane University, Beni Mellal
2
Engineering and Applied Physics Team (EAPT), Superior School of Technology, Sultan Moulay Slimane University, Beni Mellal
3
Engineering and Applied Physics Team (EAPT), Superior School of Technology, Sultan Moulay Slimane University, Beni Mellal
4
Engineering and Applied Physics Team (EAPT), Superior School of Technology, Sultan Moulay Slimane University, Beni Mellal
5
Industrial Technologies and Services Laboratory, Higher School of Technology, Sidi Mohamed Ben Abdellah University, Fez

Partial shading occurs when some of the solar panels are exposed to reduced irradiation.  Partial shading can lead to creating peaks and troughs in power production.  The goal of this study is to compare the effect of partial shading on the capacity of maximum power point tracking (MPPT) methods, to find the global maximum power point.  To this end, the study focuses on performance simulation and discussion of Perturb and Observe (P&O), Particle Swarm Optimization (PSO), and Artificial Neural Network (ANN) controls.  Analysing the three MPPT controller's results, in terms of accuracy, the ANN and PSO controls showed high performance.  On the other hand, the P\&O control showed lower accuracy, particularly under partial shading.  For the speed of reaction, the P&O and ANN controls proved to be the fastest, while the PSO control showed a slightly longer response time.  However, it is important to note that ANN approach presents added complexity in terms of conception.

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