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Predicting the power output of distributed renewable energy resources within a broad geographical region

Eftichios Koutroulis

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URIhttp://purl.tuc.gr/dl/dias/601227DB-B204-4ABF-A891-8A000305ED28-
Identifierhttp://eprints.soton.ac.uk/341638/1/pckPowerOutPredecai2012.pdf-
Languageen-
Extent6 pagesen
TitlePredicting the power output of distributed renewable energy resources within a broad geographical regionen
CreatorEftichios Koutroulisen
CreatorGeorgios Chalkiadakisen
CreatorAthanasios Aris Panagopoulosen
Content SummaryIn recent years, estimating the power output of in- herently intermittent and potentially distributed renewable energy sources has become a major scientific and societal concern. In this paper, we provide an algorithmic framework, along with an inter- active web-based tool, to enable short-to-middle term forecasts of photovoltaic (PV) systems and wind generators output. Importantly, we propose a generic PV output estimation method, the backbone of which is a solar irradiance approximation model that incorpo- rates free-to-use, readily available meteorological data coming from online weather stations. The model utilizes non-linear approxima- tion components for turning cloud-coverage into radiation forecasts, such as an MLP neural network with one hidden layer. We present a thorough evaluation of the proposed techniques, and show that they can be successfully employed within a broad geographical region (the Mediterranean belt) and come with specific performance guar- antees. Crucially, our methods do not rely on complex and expensive weather models and data, and our web-based tool can be of immedi- ate use to the community as a simulation data acquisition platform.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-09-26-
Date of Publication2012-
SubjectBalance of natureen
SubjectBiology--Ecologyen
SubjectBionomicsen
SubjectEcological processesen
SubjectEcological scienceen
SubjectEcological sciencesen
SubjectEnvironmenten
SubjectEnvironmental biologyen
SubjectOecologyen
Subjectecologyen
Subjectbalance of natureen
Subjectbiology ecologyen
Subjectbionomicsen
Subjectecological processesen
Subjectecological scienceen
Subjectecological sciencesen
Subjectenvironmenten
Subjectenvironmental biologyen
Subjectoecologyen
Bibliographic CitationA. A.Panagopoulos, G. Chalkiadakis, E. Koutroulis . ( 2012,Aug.) .Predicting the power output of distributed renewable energy resources within a broad geographical Region.Presented at 20th European Conference on Artificial Intelligence, Prestigious Applications of Intelligent Systems Track , Montpellier, FR.[online].Available :http://eprints.soton.ac.uk/341638/1/pckPowerOutPredecai2012.pdfen

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