Abstract: The precise of solar cell model parameters being the prerequisite for realizing accurate photovoltaic models. Hence, the parameters identification techniques have attracted immense interest over the years among the researchers. This paper proposes a modelling and prediction of electrical intrinsic parameter extraction method of flexible hydrogenated amorphous silicon a-Si:H solar cell, based on the meta-heuristic firefly algorithm (FA). The characteristics of solar cells are non-linear, multivariable and multi-modal and difficult to identifies the electrical intrinsic parameters by conventional and analytical methods with high accuracy. Recently, the firefly algorithm has attracted the attention to optimize the non-linear and complex systems, based on the flashing patterns and behaviour of firefly’s swarm. Besides, the proposed constrained objective function is derived from the current–voltage curve. It is the absolute errors between the experimental and calculated current and voltage values. Furthermore, the obtained results of the proposed algorithm are compared with the results obtained by quasi-Newton method (Q-N) and self-organizing migrating algorithm (SOMA). Indeed, to validate the performance of the algorithm, the statistical analyses are carried out to measure the accuracy of the estimated parameters. In the end, the theoretical results of the firefly algorithm show an excellent agreement with experimental data and more accurate compared to other compared techniques.

Modelling and Parameters Extraction of Flexible Amorphous Silicon Solar Cell a-Si:H

Mussetta M.
2020-01-01

Abstract

Abstract: The precise of solar cell model parameters being the prerequisite for realizing accurate photovoltaic models. Hence, the parameters identification techniques have attracted immense interest over the years among the researchers. This paper proposes a modelling and prediction of electrical intrinsic parameter extraction method of flexible hydrogenated amorphous silicon a-Si:H solar cell, based on the meta-heuristic firefly algorithm (FA). The characteristics of solar cells are non-linear, multivariable and multi-modal and difficult to identifies the electrical intrinsic parameters by conventional and analytical methods with high accuracy. Recently, the firefly algorithm has attracted the attention to optimize the non-linear and complex systems, based on the flashing patterns and behaviour of firefly’s swarm. Besides, the proposed constrained objective function is derived from the current–voltage curve. It is the absolute errors between the experimental and calculated current and voltage values. Furthermore, the obtained results of the proposed algorithm are compared with the results obtained by quasi-Newton method (Q-N) and self-organizing migrating algorithm (SOMA). Indeed, to validate the performance of the algorithm, the statistical analyses are carried out to measure the accuracy of the estimated parameters. In the end, the theoretical results of the firefly algorithm show an excellent agreement with experimental data and more accurate compared to other compared techniques.
2020
bio-inspired algorithms
firefly algorithm
flexible amorphous silicon
self-organizing migrating algorithm
solar cell
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1171244
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