Intelligent photovoltaic system to maximize the capture of solar energy

Christian Ovalle Paulino, Luis Rojas Nieves, Hugo Villaverde Medrano, Ernesto Paiva Peredo


The large consumption of electricity worldwide has an impact on the environment which can be said to alter climate change, the degradation of the ozone layer and acid rain. A house has an average daily consumption of 270kWh, this is why solar panels are very useful and can help to have a renewable energy at low costs. To create an intelligent photovoltaic system, different electronic sensors can be applied to follow the sunlight through a series of instructions in some programming software. The article proposes to prototype an intelligent photovoltaic system, based on artificial intelligence with a neural network library "propet" having a positive impact on the optimization of power generation by allowing a more accurate tracking of the sun and a greater collection of photovoltaic energy throughout the day. performing an integration between Arduino and machine learning algorithms such as artificial neural networks in prediction of time series. Different practical experiments were performed to illustrate the effectiveness of the proposed method.


Solar traker Arttificial intelligence; Neural network; Photovoltaic; Environment

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The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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