{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T07:20:43Z","timestamp":1774596043187,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T00:00:00Z","timestamp":1706659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Operational Program Portugal 2020 and Operational Program CRESC Algarve 2020","award":["72581\/2020"],"award-info":[{"award-number":["72581\/2020"]}]},{"name":"Operational Program Portugal 2020 and Operational Program CRESC Algarve 2020","award":["UID\/EMS\/50022\/2020"],"award-info":[{"award-number":["UID\/EMS\/50022\/2020"]}]},{"name":"Operational Program Portugal 2020 and Operational Program CRESC Algarve 2020","award":["UIDB\/00326\/2020"],"award-info":[{"award-number":["UIDB\/00326\/2020"]}]},{"name":"Operational Program Portugal 2020 and Operational Program CRESC Algarve 2020","award":["UIDP\/00326\/2020"],"award-info":[{"award-number":["UIDP\/00326\/2020"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","award":["72581\/2020"],"award-info":[{"award-number":["72581\/2020"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","award":["UID\/EMS\/50022\/2020"],"award-info":[{"award-number":["UID\/EMS\/50022\/2020"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","award":["UIDB\/00326\/2020"],"award-info":[{"award-number":["UIDB\/00326\/2020"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","award":["UIDP\/00326\/2020"],"award-info":[{"award-number":["UIDP\/00326\/2020"]}]},{"name":"Foundation for Science and Technology, I.P.\/MCTES through national funds (PIDDAC), within the scope of CISUC R&amp;D Unit","award":["72581\/2020"],"award-info":[{"award-number":["72581\/2020"]}]},{"name":"Foundation for Science and Technology, I.P.\/MCTES through national funds (PIDDAC), within the scope of CISUC R&amp;D Unit","award":["UID\/EMS\/50022\/2020"],"award-info":[{"award-number":["UID\/EMS\/50022\/2020"]}]},{"name":"Foundation for Science and Technology, I.P.\/MCTES through national funds (PIDDAC), within the scope of CISUC R&amp;D Unit","award":["UIDB\/00326\/2020"],"award-info":[{"award-number":["UIDB\/00326\/2020"]}]},{"name":"Foundation for Science and Technology, I.P.\/MCTES through national funds (PIDDAC), within the scope of CISUC R&amp;D Unit","award":["UIDP\/00326\/2020"],"award-info":[{"award-number":["UIDP\/00326\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Energies"],"abstract":"<jats:p>The incorporation of renewable energy systems in the world energy system has been steadily increasing during the last few years. In terms of the building sector, the usual consumers are becoming increasingly prosumers, and the trend is that communities of energy, whose households share produced electricity, will increase in number in the future. Another observed tendency is that the aggregator (the entity that manages the community) trades the net community energy in public energy markets. To accomplish economically good transactions, accurate and reliable forecasts of the day-ahead net energy community must be available. These can be obtained using an ensemble of multi-step shallow artificial neural networks, with prediction intervals obtained by the covariance algorithm. Using real data obtained from a small energy community of four houses located in the southern region of Portugal, one can verify that the deterministic and probabilistic performance of the proposed approach is at least similar, typically better than using complex, deep models.<\/jats:p>","DOI":"10.3390\/en17030696","type":"journal-article","created":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T09:43:22Z","timestamp":1706780602000},"page":"696","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Multi-Step Ensemble Approach for Energy Community Day-Ahead Net Load Point and Probabilistic Forecasting"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0014-9257","authenticated-orcid":false,"given":"Maria da Gra\u00e7a","family":"Ruano","sequence":"first","affiliation":[{"name":"Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal"},{"name":"CISUC, University of Coimbra, 3030-290 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6308-8666","authenticated-orcid":false,"given":"Antonio","family":"Ruano","sequence":"additional","affiliation":[{"name":"Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal"},{"name":"IDMEC, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"113588","DOI":"10.1016\/j.enbuild.2023.113588","article-title":"From home energy management systems to communities energy managers: The use of an intelligent aggregator in a community in Algarve, Portugal","volume":"298","author":"Gomes","year":"2023","journal-title":"Energy Build."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"10751","DOI":"10.1109\/TII.2023.3241682","article-title":"Hybrid Policy-Based Reinforcement Learning of Adaptive Energy Management for the Energy Transmission-Constrained Island Group","volume":"19","author":"Yang","year":"2023","journal-title":"IEEE Trans. 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