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ADVANCED TOPICS IN ELECTRICAL ENGINEERING – ATEE 2017

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Comparative Prediction of Single and Double Diode Solar Cell Models with firefly Algorithm

Due to the non-linearity of current-voltage of solar cell model, the conventional methods are incapable to extract the parameters of solar cell with high accuracy. The implicit nonlinear equation describing the single and double diodes solar cell in five and seven parameters is rewritten as optimization problems with constraint functions and it is solved by using a firefly algorithm optimization. The firefly algorithm is a natureinspired stochastic optimization algorithm, and able to solve modern global optimization for nonlinear and complex system, based on the flashing patterns and behavior of firefly’s swarm. Moreover, this paper develops a unique solar cell modelling approach that incorporates search and optimization techniques for the determination of equivalent circuit parameters of RTC France Company mono-crystalline silicon solar cell single and double diodes at 33°C and 1000W/m² from experimental current-voltage. The statistical errors are used to verify the accuracy of the results. Finally, accuracy of the extracted parameters is verified by comparing the current-voltage curve generated from simulation with those provided by determined experimentally and with different recent algorithms.

Author(s):

Mohamed LOUZAZNI    
Laboratory of Innovative Technologies, National School of Applied Sciences (ENSA), Abdelmalek Essaadi University, Tangier, Morocco
Morocco

Ahmed KHOUYA    
Laboratory of Innovative Technologies, National School of Applied Sciences (ENSA), Abdelmalek Essaadi University, Tangier, Morocco
Morocco

Khalid AMECHNOUE    
Laboratory of Innovative Technologies, National School of Applied Sciences (ENSA), Abdelmalek Essaadi University, Tangier, Morocco
Morocco

Aurelian CRACIUNESCU    
Faculty of Electrical Engineering, University “Politehnica” of Bucharest, Romania
Romania

Marco MUSSETTA    
Politecnico di Milano, Dipartimento di Energia, Via La Masa 34, 20156 Milano, Italy
Italy

 

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