Abstract
The equivalent electric circuit models reflect the electrical characteristics of the photovoltaic (PV) modules. Estimation of PV module parameters is considered as one of the challenging tasks while evaluating the performance. This article presents a new and useful approach to estimate the five-parameter PV module electrical circuit model. It translates the PV module parameter estimation process into an optimization problem using the information provided by the manufacturer on the rear side of the PV modules. It then employs an efficient metaheuristic technique, namely the backtracking search algorithm, to solve the developed optimization problem. The efficacy of the proposed approach is investigated by predicting the parameters of three PV module technologies: monocrystalline, poly-crystalline, and thin film. Finally, to check the feasibility of the proposed technique, this paper compares the approximate parameters of modeled I-V curves with experimental curves. The findings confirm the reliability of the estimated model parameters in simulating the near realistic characteristics of the PV modules.
Original language | English |
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Title of host publication | 2021 1st International Conference on Artificial Intelligence and Data Analytics, CAIDA 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 188-193 |
Number of pages | 6 |
ISBN (Electronic) | 9780738131771 |
DOIs | |
State | Published - 6 Apr 2021 |
Publication series
Name | 2021 1st International Conference on Artificial Intelligence and Data Analytics, CAIDA 2021 |
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Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- Backtracking search algorithm
- Electrical parameters
- PV module
- Parameter estimation
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Information Systems and Management