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 At ECAI-2012/PAIS-2012: 20th European Conference on Artificial Intelligence, Prestigious Applications of Intelligent Systems Track, France. 27 - 31 Aug 2012. 6 pp.

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Description/Abstract

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)
Venue - Dates: ECAI-2012/PAIS-2012: 20th European Conference on Artificial Intelligence, Prestigious Applications of Intelligent Systems Track, France, 2012-08-27 - 2012-08-31
Subjects:
Organisations: Agents, Interactions & Complexity
ePrint ID: 341638
Date :
Date Event
27 August 2012e-pub ahead of print
Date Deposited: 02 Aug 2012 08:47
Last Modified: 17 Apr 2017 16:45
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/341638

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