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

被引:80
作者
Bessa, Ricardo J. [1 ]
Mohlen, Corinna [2 ]
Fundel, Vanessa [3 ]
Siefert, Malte [4 ]
Browell, Jethro [5 ]
El Gaidi, Sebastian Haglund [6 ]
Hodge, Bri-Mathias [7 ]
Cali, Umit [8 ]
Kariniotakis, George [9 ]
机构
[1] INESC Technol & Sci INESC TEC, P-4200465 Oporto, Portugal
[2] WEPROG, DK-5610 Assens, Denmark
[3] Deutsch Wetterdienst, D-63067 Offenbach, Germany
[4] Fraunhofer Inst Wind Energy & Energy Syst Technol, D-34119 Kassel, Germany
[5] Univ Strathclyde, Dept Elect & Elect Engn, Glasgow G1 1XQ, Lanark, Scotland
[6] Royal Inst Technol, Dept Mech, SE-10044 Stockholm, Sweden
[7] Natl Renewable Energy Lab, Golden, CO 80401 USA
[8] Univ North Carolina Charlotte, Dept Engn Technol & Construct Management, Charlotte, NC 28223 USA
[9] PSL Res Univ, MINES ParisTech, Ctr Proc Renewable Energies & Energy Syst PERSEE, F-06904 Sophia Antipolis, France
关键词
wind energy; uncertainty; decision-making; quantiles; ensembles; forecast; statistics; weather; ENSEMBLE KALMAN FILTER; MODEL OUTPUT STATISTICS; WIND POWER; PROBABILISTIC FORECASTS; PREDICTION INTERVALS; LOGISTIC-REGRESSION; SINGULAR VECTORS; DECISION-MAKING; GENERATION; WEATHER;
D O I
10.3390/en10091402
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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.
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页数:48
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