FPGA Implementation of Multilayer Perceptron for Modeling of Photovoltaic panel
- Department of Electronics, RASIC laboratory BLIDA UniversityBLIDA (Algeria)
- Department of Electronics, Control laboratory BLIDA UniversityBLIDA (Algeria)
The Number of electronic applications using artificial neural network-based solutions has increased considerably in the last few years. However, their applications in photovoltaic systems are very limited. This paper introduces the preliminary result of the modeling and simulation of photovoltaic panel based on neural network and VHDL-language. In fact, an experimental database of meteorological data (irradiation, temperature) and output electrical generation signals of the PV-panel (current and voltage) has been used in this study. The inputs of the ANN-PV-panel are the daily total irradiation and mean average temperature while the outputs are the current and voltage generated from the panel. Firstly, a dataset of 4x364 have been used for training the network. Subsequently, the neural network (MLP) corresponding to PV-panel is simulated using VHDL language based on the saved weights and bias of the network. Simulation results of the trained MLP-PV panel based on Matlab and VHDL are presented. The proposed PV-panel model based ANN and VHDL permit to evaluate the performance PV-panel using only the environmental factors and involves less computational efforts, and it can be used for predicting the output electrical energy from the PV-panel.
- OSTI ID:
- 21143555
- Journal Information:
- AIP Conference Proceedings, Vol. 1019, Issue 1; Conference: CISA 08: 1. Mediterranean conference on intelligent systems and automation, Annaba (Algeria), 30 Jun - 2 Jul 2008; Other Information: DOI: 10.1063/1.2952981; (c) 2008 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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