The University of Southampton
University of Southampton Institutional Repository

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

Record type: Conference or Workshop Item (Paper)

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.

PDF pckPowerOutPredecai2012.pdf - Version of Record
Download (214kB)

Citation

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.

More information

e-pub ahead of print date: 27 August 2012
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
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 341638
URI: http://eprints.soton.ac.uk/id/eprint/341638
PURE UUID: f6cfe393-7f8f-4955-aa7c-74e68665e0f2

Catalogue record

Date deposited: 02 Aug 2012 08:47
Last modified: 18 Jul 2017 05:34

Export record

Contributors

Author: Athanasios Aris Panagopoulos
Author: Georgios Chalkiadakis
Author: Eftichios Koutroulis

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×