Bessa, R., Möhrlen, C., Fundel, V., Siefert, M., Browell, J. , Haglund El Gaidi, S., Hodge, B.-M., Cali, U. and Kariniotakis, G. (2017) Towards improved understanding of the applicability of uncertainty forecasts in the electric power industry. Energies, 10(9), 1402. (doi: 10.3390/en10091402)
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Abstract
Around the world wind energy is starting to become a major energy provider in electricity markets, as well as participating in ancillary services markets to help maintain grid stability. The reliability of system operations and smooth integration of wind energy into electricity markets has been strongly supported by years of improvement in weather and wind power forecasting systems. Deterministic forecasts are still predominant in utility practice although truly optimal decisions and risk hedging are only possible with the adoption of uncertainty forecasts. One of the main barriers for the industrial adoption of uncertainty forecasts is the lack of understanding of its information content (e.g., its physical and statistical modeling) and standardization of uncertainty forecast products, which frequently leads to mistrust towards uncertainty forecasts and their applicability in practice. This paper aims at improving this understanding by establishing a common terminology and reviewing the methods to determine, estimate, and communicate the uncertainty in weather and wind power forecasts. This conceptual analysis of the state of the art highlights that: (i) end-users should start to look at the forecast’s properties in order to map different uncertainty representations to specific wind energy-related user requirements; (ii) a multidisciplinary team is required to foster the integration of stochastic methods in the industry sector. A set of recommendations for standardization and improved training of operators are provided along with examples of best practices.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Browell, Dr Jethro |
Authors: | Bessa, R., Möhrlen, C., Fundel, V., Siefert, M., Browell, J., Haglund El Gaidi, S., Hodge, B.-M., Cali, U., and Kariniotakis, G. |
College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
Journal Name: | Energies |
Publisher: | MDPI |
ISSN: | 1996-1073 |
ISSN (Online): | 1996-1073 |
Published Online: | 14 September 2017 |
Copyright Holders: | Copyright © 2017 The Authors |
First Published: | First published in Energies 10(9): 1402 |
Publisher Policy: | Reproduced under a Creative Commons License |
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