Data-driven upscaling methods for regional photovoltaic power estimation and forecast using satellite and numerical weather prediction data

Author:

Pierro Marco,De Felice MatteoORCID,Maggioni Enrico,Moser David,Perotto Alessandro,Spada Francesco,Cornaro CristinaORCID

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference46 articles.

1. Alet, P.-J., 2015. Photovoltaics merging with the active integrated grid: a white paper. European Photovoltaic Technology Platform.

2. Alet, P.-J., Efthymiou, V., Graditi, G., Henze, N., Juel, M., Moser, D., et al., 2016. Forecasting and observability: critical technologies for system operations with high PV penetration. In: Proceedings of the 32nd EuropeanPhotovoltaic Solar Energy Conference and Exhibition, Paris, pp. 1444–1448.

3. Review of photovoltaic power forecasting;Antonanzas;Sol. Energy,2016

4. A hybrid method based on a new clustering technique and multilayer perceptron neural networks for hourly solar radiation forecasting;Azimi;Energy Convers. Manage.,2016

5. Artificial neural networks: fundamentals, computing, design, and application;Basheer;J. Microbiol. Methods,2000

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