A prediction Model Based on Nelder-Mead Algorithm for the Energy Production of PV Module
Abstract
The use of an adequate model of photovoltaic module for the energy prediction is an important tool. To this end, PV modeling primarily involves the formulation of the non-linear current versus voltage (I-V) curve. This paper presents an application of the Nelder-Mead simplex search method for identifying the parameters of solar cell and photovoltaic module models. The proposed technique is used to identify the unknown model parameters, namely, the generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor that govern the current-voltage relationship of a solar cell. The extracted parameters have been tested against several static IV characteristics of the PV module collected at different operating condition. Comparative study among different parameter estimation techniques is presented to demonstrate the effectiveness of the proposed approach. A dynamic MPP model has also been derived and simulated using the extracted parameters against MPP real dynamic measurements of a grid connected system located in the Centre de Developpement des Energies Renouvelables (CDER) in Algiers.
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