AbstractAn implementation of an intelligent photovoltaic module on reconfigurable Field Programmable Gate Array (FPGA) is described in this paper. An experimental database of meteorological data (irradiation and temperature) and output electrical generation data of a Photovoltaic (PV) module (current and voltage) under variable climate condition is used in this study. Initially, an Artificial Neural Network (ANN) is developed under Matlab/Similuk, environment for modeling the PV module. The inputs of the ANN–PV module are the global solar irradiation and temperature while the outputs are the current and voltage generated from the PV‐module. Subsequently, the optimal configuration of the ANN model (ANN–PV module) is written and simulated under the Very High Description Language (VHDL) and ModelSim. The synthesized architecture by ModelSim is then implemented on an FPGA device. The designed MLP‐photovoltaic module permits the evaluation of performance of the PV module using only environmental parameters and involves less computational effort. The device can also be used for predicting the output electrical energy from the PV module and for a real time simulation in specific climatic conditions. Copyright © 2010 John Wiley & Sons, Ltd.