Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry

Ricardo J. Bessa, Corinna Möhrlen, Vanessa Fundel, Malte Siefert, Jethro Browell, Sebastian Haglund El Gaidi, Bri-Mathias Hodge, Umit Cali and George Kariniotakis
Additional contact information
Ricardo J. Bessa: INESC Technology and Science (INESC TEC), 4200-465 Porto, Portugal
Corinna Möhrlen: WEPROG, 5610 Assens, Denmark
Vanessa Fundel: Deutscher Wetterdienst, 63067 Offenbach, Germany
Malte Siefert: Fraunhofer Institute for Wind Energy and Energy System Technology (IWES), 34119 Kassel, Germany
Jethro Browell: University of Strathclyde, Department of Electronic and Electrical Engineering, Glasgow G1 1XQ, UK
Sebastian Haglund El Gaidi: Royal Institute of Technology, Department of Mechanics, SE-100 44 Stockholm, Sweden
Bri-Mathias Hodge: National Renewable Energy Laboratory, Golden, CO 80401, USA
Umit Cali: University of North Carolina Charlotte, Dept. of Engineering Technology and Construction Management, Charlotte, NC 28223, USA
George Kariniotakis: MINES ParisTech, PSL Research University, Centre for Processes, Renewable Energies and Energy Systems (PERSEE), 06904 Sophia Antipolis Cedex, France

Energies, 2017, vol. 10, issue 9, 1-48

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.

Keywords: wind energy; uncertainty; decision-making; quantiles; ensembles; forecast; statistics; weather (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

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