{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T09:57:12Z","timestamp":1771235832414,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T00:00:00Z","timestamp":1722643200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hellenic Foundation for Research and Innovation (H.F.R.I.)","award":["03698"],"award-info":[{"award-number":["03698"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Given the recent increase in demand for electricity, it is necessary for renewable energy sources (RESs) to be widely integrated into power networks, with the two most commonly adopted alternatives being solar and wind power. Nonetheless, there is a significant amount of variation in wind speed and solar irradiance, on both a seasonal and a daily basis, an issue that, in turn, causes a large degree of variation in the amount of solar and wind energy produced. Therefore, RES technology integration into electricity networks is challenging. Accurate forecasting of solar irradiance and wind speed is crucial for the efficient operation of renewable energy power plants, guaranteeing the electricity supply at the most competitive price and preserving the dependability and security of electrical networks. In this research, a variety of different models were evaluated to predict medium-term (24 h ahead) wind speed and solar irradiance based on real-time measurement data relevant to the island of Crete, Greece. Illustrating several preprocessing steps and exploring a collection of \u201cclassical\u201d and deep learning algorithms, this analysis highlights their conceptual design and rationale as time series predictors. Concluding the analysis, it discusses the importance of the \u201cfeatures\u201d (intended as \u201ctime steps\u201d), showing how it is possible to pinpoint the specific time of the day that most influences the forecast. Aside from producing the most accurate model for the case under examination, the necessity of performing extensive model searches in similar studies is highlighted by the current work.<\/jats:p>","DOI":"10.3390\/s24155035","type":"journal-article","created":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T13:57:28Z","timestamp":1722866248000},"page":"5035","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Towards Automated Model Selection for Wind Speed and Solar Irradiance Forecasting"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8410-1818","authenticated-orcid":false,"given":"Konstantinos","family":"Blazakis","sequence":"first","affiliation":[{"name":"School of Electrical and Computer Engineering, Technical University of Crete, 73100 Chania, Greece"},{"name":"QUBITECH, Quantum Technologies, 15231 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8893-219X","authenticated-orcid":false,"given":"Nikolaos","family":"Schetakis","sequence":"additional","affiliation":[{"name":"Institute of Computational Mechanics and Optimization, School of Production Engineering and Management, Technical University of Crete, 73100 Chania, Greece"}]},{"given":"Paolo","family":"Bonfini","sequence":"additional","affiliation":[{"name":"Quantum Innovation Pc, 73100 Chania, Greece"},{"name":"Alma-Sistemi Srl, IT-00012 Guidonia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6355-8690","authenticated-orcid":false,"given":"Konstantinos","family":"Stavrakakis","sequence":"additional","affiliation":[{"name":"Department of Quantum and Computer Engineering, Delft University of Technology, 2628 Delft, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3589-0627","authenticated-orcid":false,"given":"Emmanuel","family":"Karapidakis","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410 Heraklion, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1994-4314","authenticated-orcid":false,"given":"Yiannis","family":"Katsigiannis","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410 Heraklion, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.renene.2017.05.058","article-title":"A novel method based on similarity for hourly solar irradiance forecasting","volume":"112","author":"Akarslan","year":"2017","journal-title":"Renew. 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