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Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module
The estimation of the photovoltaic (PV) cell/module model parameters could lead to accomplish a diagnostic tool and to estimate several factors which affect the health state of a PV generator. In this context, it is crucial to look for an extraction technique which performs this evaluation precisely and quickly. Due to the nonlinear and implicit nature of the PV cell/module, significant computational effort is required to obtain all the parameters; therefore, in this context different metaheuristic algorithms are proposed. For the identification of the meaningful parameters of PV cell/module models, illuminated current-voltage (I–V) curves, under real conditions of PV cells temperature and incident irradiance, are employed. Considering several PV cell/module models, the goodness of the proposed algorithms is analyzed by means of statistical errors, convergence speed, and unknown parameters precision. Then these algorithms are tested and validated using a daily set of measured I–V curves, specifically for each one both the whole set of measured data and a reduced set around the maximum power point are used.
Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module
The estimation of the photovoltaic (PV) cell/module model parameters could lead to accomplish a diagnostic tool and to estimate several factors which affect the health state of a PV generator. In this context, it is crucial to look for an extraction technique which performs this evaluation precisely and quickly. Due to the nonlinear and implicit nature of the PV cell/module, significant computational effort is required to obtain all the parameters; therefore, in this context different metaheuristic algorithms are proposed. For the identification of the meaningful parameters of PV cell/module models, illuminated current-voltage (I–V) curves, under real conditions of PV cells temperature and incident irradiance, are employed. Considering several PV cell/module models, the goodness of the proposed algorithms is analyzed by means of statistical errors, convergence speed, and unknown parameters precision. Then these algorithms are tested and validated using a daily set of measured I–V curves, specifically for each one both the whole set of measured data and a reduced set around the maximum power point are used.
Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module
Hachana, O. (author) / Hemsas, K. E. (author) / Tina, G. M. (author) / Ventura, C. (author)
Journal of Renewable and Sustainable Energy ; 5 ; 053122-
2013-09-01
18 pages
Article (Journal)
Electronic Resource
English
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