BigData techniques for Solar Power Forecasting - Nunes, Rui
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With the growth of social awareness for environmental issues, came a new and important problem to the discussion, related to renewable energies. Although this kind of energy production is already in an advanced state of development there are some issues that still need to be studied and perfected on the real production environment. The Photovoltaic production is gain some importance but the prediction of this kind of energy still need a boost in their performance. The SMART Grid projects brought this issues to another level where the importance of these predictions needs to be as accurate as…mehr

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Produktbeschreibung
With the growth of social awareness for environmental issues, came a new and important problem to the discussion, related to renewable energies. Although this kind of energy production is already in an advanced state of development there are some issues that still need to be studied and perfected on the real production environment. The Photovoltaic production is gain some importance but the prediction of this kind of energy still need a boost in their performance. The SMART Grid projects brought this issues to another level where the importance of these predictions needs to be as accurate as possible, butthey brought another problem, how to accurate this prediction with all data that this kindof problems is associated with. There are some accurate models for a single location prediction but we involving multiple locations in one problem we need to have some computational power. Big Data techniques such the Convex optimization are a field that is important to explore since these techniques applied with the parallel computer programming paradigm can bring that computational power, and more accurate models can be trained faster.
Autorenporträt
Rui Miguel da Cunha Nunes finished his Applied Mathematics and Computing degree. Post-graduation, he joined the Data Analytics Master's for further academic growth. He's now pursuing a Doctoral Program in Applied Mathematics.