URI | http://purl.tuc.gr/dl/dias/601227DB-B204-4ABF-A891-8A000305ED28 | - |
Identifier | http://eprints.soton.ac.uk/341638/1/pckPowerOutPredecai2012.pdf | - |
Language | en | - |
Extent | 6 pages | en |
Title | Predicting the power output of distributed renewable energy resources within a broad geographical region | en |
Creator | Eftichios Koutroulis | en |
Creator | Georgios Chalkiadakis | en |
Creator | Athanasios Aris Panagopoulos | en |
Content Summary | In 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 Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
Type of Item | Conference Full Paper | en |
License | http://creativecommons.org/licenses/by/4.0/ | en |
Date of Item | 2015-09-26 | - |
Date of Publication | 2012 | - |
Subject | Balance of nature | en |
Subject | Biology--Ecology | en |
Subject | Bionomics | en |
Subject | Ecological processes | en |
Subject | Ecological science | en |
Subject | Ecological sciences | en |
Subject | Environment | en |
Subject | Environmental biology | en |
Subject | Oecology | en |
Subject | ecology | en |
Subject | balance of nature | en |
Subject | biology ecology | en |
Subject | bionomics | en |
Subject | ecological processes | en |
Subject | ecological science | en |
Subject | ecological sciences | en |
Subject | environment | en |
Subject | environmental biology | en |
Subject | oecology | en |
Bibliographic Citation | A. 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.pdf | en |