Evaluating the quality of scenarios of short-term wind power generation

► Presentation of the desirable properties of wind power generation scenarios. ► Description of various evaluation frameworks (univariate, multivariate, diagnostic). ► Highlighting of the properties of current approaches to scenario generation. ► Guidelines for future evaluation/benchmark exercises....

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Veröffentlicht in:Applied energy Jg. 96; S. 12 - 20
Hauptverfasser: Pinson, P., Girard, R.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.08.2012
Elsevier
Schlagworte:
Decision making
Diagnostic tools
Discrimination
domain_spi.energ
Engineering Sciences
Forecasting
Lead time
Multivariate verification
Optimization
power generation
Programming
Renewable energy
Stochasticity
Temporal logic
Time trajectories
wind power
Wind power generation
Diagnostic tools
Time trajectories
Renewable energy
Forecasting
Multivariate verification
ISSN:0306-2619, 1872-9118
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Zusammenfassung:► Presentation of the desirable properties of wind power generation scenarios. ► Description of various evaluation frameworks (univariate, multivariate, diagnostic). ► Highlighting of the properties of current approaches to scenario generation. ► Guidelines for future evaluation/benchmark exercises. Scenarios of short-term wind power generation are becoming increasingly popular as input to multistage decision-making problems e.g. multivariate stochastic optimization and stochastic programming. The quality of these scenarios is intuitively expected to substantially impact the benefits from their use in decision-making. So far however, their verification is almost always focused on their marginal distributions for each individual lead time only, thus overlooking their temporal interdependence structure. The shortcomings of such an approach are discussed. Multivariate verification tools, as well as diagnostic approaches based on event-based verification are then presented. Their application to the evaluation of various sets of scenarios of short-term wind power generation demonstrates them as valuable discrimination tools.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2011.11.004