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

Panagopoulos, Athanasios Aris, Chalkiadakis, Georgios and Koutroulis, Eftichios (2012) Predicting the power output of distributed renewable energy resources within a broad geographical region. In, ECAI-2012/PAIS-2012: 20th European Conference on Artificial Intelligence, Prestigious Applications of Intelligent Systems Track , Montpellier, FR, 27 - 31 Aug 2012.


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In recent years, estimating the power output of inherently
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 interactive
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 incorporates
free-to-use, readily available meteorological data coming from
online weather stations. The model utilizes non-linear approximation
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 guarantees.
Crucially, our methods do not rely on complex and expensive
weather models and data, and our web-based tool can be of immediate
use to the community as a simulation data acquisition platform.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
ePrint ID: 341638
Date Deposited: 02 Aug 2012 08:47
Last Modified: 27 Mar 2014 20:24
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