Evaluation of Transfer Learning and Fine-Tuning to Nowcast Energy Generation of Photovoltaic Systems in Different Climates
| Autor: | Guillermo Almonacid-Olleros, Gabino Almonacid, David Gil, Javier Medina-Quero |
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| Přispěvatelé: | Universidad de Alicante. Departamento de Tecnología Informática y Computación, Lucentia |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Energy generation
photovoltaic systems deep learning transfer learning energy generation distributed generation smart-grids Smart-grids Renewable Energy Sustainability and the Environment Geography Planning and Development Deep learning Management Monitoring Policy and Law Distributed generation Photovoltaic systems Arquitectura y Tecnología de Computadores Transfer learning |
| Zdroj: | Sustainability; Volume 14; Issue 5; Pages: 3092 RUA. Repositorio Institucional de la Universidad de Alicante Universidad de Alicante (UA) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su14053092 |
| Popis: | New trends of Machine learning models are able to nowcast power generation overtaking the formulation-based standards. In this work, the capabilities of deep learning to predict energy generation over three different areas and deployments in the world are discussed. To this end, transfer learning from deep learning models to nowcast output power generation in photovoltaic systems is analyzed. First, data from three photovoltaic systems in different regions of Spain, Italy and India are unified under a common segmentation stage. Next, pretrained and non-pretrained models are evaluated in the same and different regions to analyze the transfer of knowledge between different deployments and areas. The use of pretrained models provides encouraging results which can be optimized with rearward learning of local data, providing more accurate models. This contribution has been supported by the Cátedra ELAND for Renewable Energies of the University of Jaén, by the Spanish government by means of the project RTI2018-098979-A-I00. This work has been partially funded by “La Conselleria de Innovacién, Universidades, Ciencia y Sociedad Digital”, under the project “Development of an architecture based on machine learning and data mining techniques for the prediction of indicators in the diagnosis and intervention of autism spectrum disorder. AICO/2020/117”. |
| Databáze: | OpenAIRE |
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