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 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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01.08.2012
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| ISSN: | 0306-2619, 1872-9118 |
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| Abstract | ► 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. |
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| AbstractList | 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. ► 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. 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 |
| Author | Pinson, P. Girard, R. |
| Author_xml | – sequence: 1 givenname: P. surname: Pinson fullname: Pinson, P. email: pp@imm.dtu.dk organization: Technical University of Denmark, Dept. of Informatics and Mathematical Modelling, Denmark – sequence: 2 givenname: R. surname: Girard fullname: Girard, R. organization: Mines ParisTech, Centre for Energy and Processes, Sophia-Antipolis, France |
| BackLink | https://minesparis-psl.hal.science/hal-00654836$$DView record in HAL |
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| Cites_doi | 10.1109/TPWRS.2007.901117 10.1002/jae.1166 10.1002/we.230 10.1002/qj.49712556006 10.1175/2009MWR2945.1 10.1016/j.energy.2008.04.003 10.1016/j.ijforecast.2009.12.015 10.1002/we.309 10.1109/TPWRS.2010.2045774 10.1175/1520-0493(2001)129<0550:IORHFV>2.0.CO;2 10.1109/TPWRS.2010.2065818 10.1016/S0169-2070(01)00126-1 10.1016/j.energy.2011.03.058 10.1175/1520-0450(1973)012<0595:ANVPOT>2.0.CO;2 10.1007/BF03178958 10.1016/j.apenergy.2011.04.011 10.1002/we.526 10.1175/1520-0493(2004)132<1329:TMSTHA>2.0.CO;2 10.1016/j.jcp.2007.02.014 10.1088/0034-4885/63/2/201 10.1016/j.rser.2007.01.015 10.1109/TPWRS.2010.2070848 10.2172/968212 10.1057/jors.1969.52 10.1002/we.284 10.1016/j.apenergy.2009.09.022 10.1007/s11749-008-0114-x 10.1002/we.235 10.1016/j.energy.2009.11.023 10.1111/j.1467-9868.2007.00587.x 10.1109/TPWRS.2009.2036810 10.1175/2007WAF2006116.1 10.1175/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2 10.2172/1216743 |
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| Keywords | Diagnostic tools Time trajectories Renewable energy Forecasting Multivariate verification |
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| References | D’Urso (b0120) 2000; 9 Pinson, Chevallier, Kariniotakis (b0065) 2007; 22 Juul, Meibom (b0015) 2011; 36 Stephenson, Coelho, Jolliffe (b0185) 2008; 23 Hamill (b0150) 2001; 129 Giebel G, Brownsword R, Kariniotakis G, Denhardt M, Draxl C. The state of the art in short-term prediction of wind power – a literature overview, 2nd ed. Technical report, EU project ANEMOS.plus; 2011. Leutbecher, Palmer (b0085) 2008; 227 Cutler, Kay, Jacka, Nielsen (b0175) 2007; 10 Morales, Conejo, Perez-Ruiz (b0070) 2010; 25 Jordà, Marcellino (b0115) 2010; 25 Buizza, Miller, Palmer (b0135) 1999; 131 Lund, Moller, Mathiesen, Dyrelund (b0010) 2010; 35 Granger (b0040) 1969; 20 Toth, Tallagrand, Candille, Zhu (b0195) 2006 Gneiting, Stanberry, Grimit, Held, Johnson (b0105) 2008; 17 Pinson, Madsen (b0140) 2009; 12 Wilks (b0155) 2004; 132 Brier (b0200) 1950; 78 Murphy (b0180) 1973; 12 Costa, Crespo, Navarro, Lizcano, Madsen, Feitosa (b0025) 2008; 12 Meibom, Barth, Hasche, Brand, weber, O’Malley (b0060) 2011; 26 Matos, Bessa (b0050) 2011; 26 Holmgren E. Risk indices for the estimation of uncertainty in wind power predictions based on ensembles of numerical weather predictions. M.Sc. thesis, Chalmers University of Technology, Göteborg, Sweden; 2009. Gneiting, Balabdaoui, Raftery (b0090) 2007; 69 Jolliffe, Stephenson (b0160) 2003 Wang, Botterud, Bessa, keko, Carvalho, Issicaba (b0055) 2011; 88 Lund, Mathiesen (b0005) 2009; 34 Palmer (b0130) 2000; 63 Pinson, Nielsen, Møller, Madsen, Kariniotakis (b0095) 2007; 10 Benedetti (b0190) 2010; 138 Gneiting (b0045) 2011; 27 Monteiro C, Bessa R, Miranda V, Botterud A, Wang J, Conzelmann G. Wind power forecasting: state of the art 2009. Technical report, Argonne National Laboratory, ANL/DIS-10-1; 2009. Clements, Smith (b0100) 2002; 18 Pinson, Kariniotakis (b0145) 2010; 25 Flowers L, Miner-Nordstrom L. Wind energy applications for municipal water services: opportunities, situation analyses and case-studies. In: AWWA/WEF joint management conference, Salt Lake City, Utah; 2006 [ref. NREL/CP-500-39178]. Wilks (b0165) 1995 Bossavy A, Girard R, Kariniotakis G. Forecasting ramps of wind power production with numerical weather prediction ensembles. Wind Energy 2011; in press. Morales, Minguez, Conejo (b0080) 2010; 87 Kaut, Wallace (b0110) 2004; 3 Pinson, Papaefthymiou, Klockl, Nielsen, Madsen (b0075) 2009; 12 Morales (10.1016/j.apenergy.2011.11.004_b0080) 2010; 87 Brier (10.1016/j.apenergy.2011.11.004_b0200) 1950; 78 Costa (10.1016/j.apenergy.2011.11.004_b0025) 2008; 12 Kaut (10.1016/j.apenergy.2011.11.004_b0110) 2004; 3 Benedetti (10.1016/j.apenergy.2011.11.004_b0190) 2010; 138 Leutbecher (10.1016/j.apenergy.2011.11.004_b0085) 2008; 227 D’Urso (10.1016/j.apenergy.2011.11.004_b0120) 2000; 9 10.1016/j.apenergy.2011.11.004_b0170 10.1016/j.apenergy.2011.11.004_b0030 Juul (10.1016/j.apenergy.2011.11.004_b0015) 2011; 36 Toth (10.1016/j.apenergy.2011.11.004_b0195) 2006 Granger (10.1016/j.apenergy.2011.11.004_b0040) 1969; 20 Pinson (10.1016/j.apenergy.2011.11.004_b0140) 2009; 12 Murphy (10.1016/j.apenergy.2011.11.004_b0180) 1973; 12 10.1016/j.apenergy.2011.11.004_b0020 Clements (10.1016/j.apenergy.2011.11.004_b0100) 2002; 18 Buizza (10.1016/j.apenergy.2011.11.004_b0135) 1999; 131 Meibom (10.1016/j.apenergy.2011.11.004_b0060) 2011; 26 Stephenson (10.1016/j.apenergy.2011.11.004_b0185) 2008; 23 Wang (10.1016/j.apenergy.2011.11.004_b0055) 2011; 88 10.1016/j.apenergy.2011.11.004_b0125 Gneiting (10.1016/j.apenergy.2011.11.004_b0105) 2008; 17 Hamill (10.1016/j.apenergy.2011.11.004_b0150) 2001; 129 Jordà (10.1016/j.apenergy.2011.11.004_b0115) 2010; 25 Lund (10.1016/j.apenergy.2011.11.004_b0005) 2009; 34 Lund (10.1016/j.apenergy.2011.11.004_b0010) 2010; 35 Wilks (10.1016/j.apenergy.2011.11.004_b0155) 2004; 132 Gneiting (10.1016/j.apenergy.2011.11.004_b0045) 2011; 27 Pinson (10.1016/j.apenergy.2011.11.004_b0065) 2007; 22 Pinson (10.1016/j.apenergy.2011.11.004_b0075) 2009; 12 Wilks (10.1016/j.apenergy.2011.11.004_b0165) 1995 Palmer (10.1016/j.apenergy.2011.11.004_b0130) 2000; 63 Jolliffe (10.1016/j.apenergy.2011.11.004_b0160) 2003 Pinson (10.1016/j.apenergy.2011.11.004_b0095) 2007; 10 Matos (10.1016/j.apenergy.2011.11.004_b0050) 2011; 26 Pinson (10.1016/j.apenergy.2011.11.004_b0145) 2010; 25 Morales (10.1016/j.apenergy.2011.11.004_b0070) 2010; 25 Gneiting (10.1016/j.apenergy.2011.11.004_b0090) 2007; 69 10.1016/j.apenergy.2011.11.004_b0035 Cutler (10.1016/j.apenergy.2011.11.004_b0175) 2007; 10 |
| References_xml | – volume: 20 start-page: 199 year: 1969 end-page: 207 ident: b0040 article-title: Prediction with a generalized cost of error function publication-title: Oper Res Quar – volume: 12 start-page: 1725 year: 2008 end-page: 1744 ident: b0025 article-title: A review on the young history of the wind power short-term prediction publication-title: Renew Sust Energ Rev – volume: 129 start-page: 550 year: 2001 end-page: 560 ident: b0150 article-title: Interpretation of rank histograms for verifying ensemble forecasts publication-title: Mon Weather Rev – volume: 10 start-page: 453 year: 2007 end-page: 470 ident: b0175 article-title: Detecting, categorizing and forecasting large ramps in wind farm power output using meteorological observations and WPPT publication-title: Wind Energy – volume: 27 start-page: 197 year: 2011 end-page: 207 ident: b0045 article-title: Quantiles as optimal point predictors publication-title: Int J Forecast – volume: 138 start-page: 201 year: 2010 end-page: 211 ident: b0190 article-title: Scoring rules for forecast verification publication-title: Mon Weather Rev – reference: Monteiro C, Bessa R, Miranda V, Botterud A, Wang J, Conzelmann G. Wind power forecasting: state of the art 2009. Technical report, Argonne National Laboratory, ANL/DIS-10-1; 2009. – reference: Flowers L, Miner-Nordstrom L. Wind energy applications for municipal water services: opportunities, situation analyses and case-studies. In: AWWA/WEF joint management conference, Salt Lake City, Utah; 2006 [ref. NREL/CP-500-39178]. – reference: Bossavy A, Girard R, Kariniotakis G. Forecasting ramps of wind power production with numerical weather prediction ensembles. Wind Energy 2011; in press. – volume: 34 start-page: 524 year: 2009 end-page: 531 ident: b0005 article-title: Energy systems analysis of 100% renewable energy systems – the case of Denmark in years 2030 and 2050 publication-title: Energy – volume: 36 start-page: 323 year: 2011 end-page: 330 ident: b0015 article-title: Optimal configuration of an integrated power and transport system publication-title: Energy – volume: 17 start-page: 211 year: 2008 end-page: 235 ident: b0105 article-title: Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds publication-title: Test – volume: 12 start-page: 51 year: 2009 end-page: 62 ident: b0075 article-title: From probabilistic forecasts to statistical scenarios of short-term wind power production publication-title: Wind Energy – year: 2003 ident: b0160 article-title: Forecast verification – a practitioner’s guide in atmospheric science – volume: 25 start-page: 635 year: 2010 end-page: 662 ident: b0115 article-title: Path forecast evaluation publication-title: J Appl Econ – volume: 23 start-page: 752 year: 2008 end-page: 757 ident: b0185 article-title: Two extra components in the Brier score decomposition publication-title: Weather Forecast – start-page: 137 year: 2006 end-page: 164 ident: b0195 article-title: Probability and ensemble forecasts publication-title: Forecast verification – a practitioner’s guide in atmospheric science – volume: 227 start-page: 3515 year: 2008 end-page: 3539 ident: b0085 article-title: Ensemble forecasting publication-title: J Comput Phys – volume: 131 start-page: 2887 year: 1999 end-page: 2908 ident: b0135 article-title: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system publication-title: Q J Roy Meteor Soc – year: 1995 ident: b0165 article-title: Statistical methods in the atmospheric sciences – volume: 26 start-page: 594 year: 2011 end-page: 603 ident: b0050 article-title: Setting the operating reserve using probabilistic wind power forecasts publication-title: IEEE Trans Power Syst – volume: 35 start-page: 1381 year: 2010 end-page: 1390 ident: b0010 article-title: The role of district heating in future renewable energy systems publication-title: Energy – volume: 87 start-page: 843 year: 2010 end-page: 855 ident: b0080 article-title: A methodology to generate statistically dependent wind speed scenarios publication-title: Appl Energy – volume: 12 start-page: 137 year: 2009 end-page: 155 ident: b0140 article-title: Ensemble-based probabilistic forecasting at Horns Rev publication-title: Wind Energy – volume: 3 start-page: 257 year: 2004 end-page: 271 ident: b0110 article-title: Evaluation of scenario-generation methods for stochastic programming publication-title: Pacif J Optim – volume: 12 start-page: 595 year: 1973 end-page: 600 ident: b0180 article-title: A new vector partition of the probability score publication-title: J Appl Meteor – volume: 78 start-page: 1 year: 1950 end-page: 3 ident: b0200 article-title: Verification of forecasts expressed in terms of probability publication-title: Mon Weather Rev – volume: 9 start-page: 53 year: 2000 end-page: 83 ident: b0120 article-title: Dissimilarity measures for time trajectories publication-title: J Italian Stat Soc – volume: 63 start-page: 71 year: 2000 end-page: 116 ident: b0130 article-title: Predicting uncertainty in forecasts of weather and climate publication-title: Rep Prog Phys – volume: 26 start-page: 1367 year: 2011 end-page: 1379 ident: b0060 article-title: Stochastic optimization model to study the operational impact of high wind power penetrations in ireland publication-title: IEEE Trans Power Syst – reference: Holmgren E. Risk indices for the estimation of uncertainty in wind power predictions based on ensembles of numerical weather predictions. M.Sc. thesis, Chalmers University of Technology, Göteborg, Sweden; 2009. – volume: 132 start-page: 1329 year: 2004 end-page: 1340 ident: b0155 article-title: The minimum spanning tree histogram as a verification tool for multidimensional ensemble forecasts publication-title: Mon Weather Rev – reference: Giebel G, Brownsword R, Kariniotakis G, Denhardt M, Draxl C. The state of the art in short-term prediction of wind power – a literature overview, 2nd ed. Technical report, EU project ANEMOS.plus; 2011. – volume: 10 start-page: 497 year: 2007 end-page: 516 ident: b0095 article-title: Nonparametric probabilistic forecasts of wind power: required properties and evaluation publication-title: Wind Energy – volume: 88 start-page: 4014 year: 2011 end-page: 4023 ident: b0055 article-title: Wind power forecast uncertainty and unit commitment publication-title: Appl Energy – volume: 25 start-page: 1845 year: 2010 end-page: 1856 ident: b0145 article-title: Conditional prediction intervals of wind power generation publication-title: IEEE Trans Power Syst – volume: 22 start-page: 1148 year: 2007 end-page: 1156 ident: b0065 article-title: Trading wind energy from short-term probabilistic forecasts of wind power publication-title: IEEE Trans Power Syst – volume: 69 start-page: 243 year: 2007 end-page: 268 ident: b0090 article-title: Probabilistic forecasts, calibration and sharpness publication-title: J Roy Stat Soc B – volume: 25 start-page: 554 year: 2010 end-page: 564 ident: b0070 article-title: Short-term trading for a wind power producer publication-title: IEEE Trans Power Syst – volume: 18 start-page: 397 year: 2002 end-page: 407 ident: b0100 article-title: Evaluating multivariate forecast densities: a comparison of two approaches publication-title: Int J Forecast – volume: 22 start-page: 1148 year: 2007 ident: 10.1016/j.apenergy.2011.11.004_b0065 article-title: Trading wind energy from short-term probabilistic forecasts of wind power publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2007.901117 – volume: 25 start-page: 635 year: 2010 ident: 10.1016/j.apenergy.2011.11.004_b0115 article-title: Path forecast evaluation publication-title: J Appl Econ doi: 10.1002/jae.1166 – volume: 10 start-page: 497 year: 2007 ident: 10.1016/j.apenergy.2011.11.004_b0095 article-title: Nonparametric probabilistic forecasts of wind power: required properties and evaluation publication-title: Wind Energy doi: 10.1002/we.230 – volume: 131 start-page: 2887 year: 1999 ident: 10.1016/j.apenergy.2011.11.004_b0135 article-title: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system publication-title: Q J Roy Meteor Soc doi: 10.1002/qj.49712556006 – start-page: 137 year: 2006 ident: 10.1016/j.apenergy.2011.11.004_b0195 article-title: Probability and ensemble forecasts – volume: 138 start-page: 201 year: 2010 ident: 10.1016/j.apenergy.2011.11.004_b0190 article-title: Scoring rules for forecast verification publication-title: Mon Weather Rev doi: 10.1175/2009MWR2945.1 – volume: 34 start-page: 524 year: 2009 ident: 10.1016/j.apenergy.2011.11.004_b0005 article-title: Energy systems analysis of 100% renewable energy systems – the case of Denmark in years 2030 and 2050 publication-title: Energy doi: 10.1016/j.energy.2008.04.003 – volume: 27 start-page: 197 year: 2011 ident: 10.1016/j.apenergy.2011.11.004_b0045 article-title: Quantiles as optimal point predictors publication-title: Int J Forecast doi: 10.1016/j.ijforecast.2009.12.015 – volume: 3 start-page: 257 year: 2004 ident: 10.1016/j.apenergy.2011.11.004_b0110 article-title: Evaluation of scenario-generation methods for stochastic programming publication-title: Pacif J Optim – volume: 12 start-page: 137 year: 2009 ident: 10.1016/j.apenergy.2011.11.004_b0140 article-title: Ensemble-based probabilistic forecasting at Horns Rev publication-title: Wind Energy doi: 10.1002/we.309 – volume: 25 start-page: 1845 year: 2010 ident: 10.1016/j.apenergy.2011.11.004_b0145 article-title: Conditional prediction intervals of wind power generation publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2010.2045774 – volume: 129 start-page: 550 year: 2001 ident: 10.1016/j.apenergy.2011.11.004_b0150 article-title: Interpretation of rank histograms for verifying ensemble forecasts publication-title: Mon Weather Rev doi: 10.1175/1520-0493(2001)129<0550:IORHFV>2.0.CO;2 – volume: 26 start-page: 594 year: 2011 ident: 10.1016/j.apenergy.2011.11.004_b0050 article-title: Setting the operating reserve using probabilistic wind power forecasts publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2010.2065818 – volume: 18 start-page: 397 year: 2002 ident: 10.1016/j.apenergy.2011.11.004_b0100 article-title: Evaluating multivariate forecast densities: a comparison of two approaches publication-title: Int J Forecast doi: 10.1016/S0169-2070(01)00126-1 – volume: 36 start-page: 323 year: 2011 ident: 10.1016/j.apenergy.2011.11.004_b0015 article-title: Optimal configuration of an integrated power and transport system publication-title: Energy doi: 10.1016/j.energy.2011.03.058 – volume: 12 start-page: 595 year: 1973 ident: 10.1016/j.apenergy.2011.11.004_b0180 article-title: A new vector partition of the probability score publication-title: J Appl Meteor doi: 10.1175/1520-0450(1973)012<0595:ANVPOT>2.0.CO;2 – volume: 9 start-page: 53 year: 2000 ident: 10.1016/j.apenergy.2011.11.004_b0120 article-title: Dissimilarity measures for time trajectories publication-title: J Italian Stat Soc doi: 10.1007/BF03178958 – volume: 88 start-page: 4014 year: 2011 ident: 10.1016/j.apenergy.2011.11.004_b0055 article-title: Wind power forecast uncertainty and unit commitment publication-title: Appl Energy doi: 10.1016/j.apenergy.2011.04.011 – ident: 10.1016/j.apenergy.2011.11.004_b0170 doi: 10.1002/we.526 – volume: 132 start-page: 1329 year: 2004 ident: 10.1016/j.apenergy.2011.11.004_b0155 article-title: The minimum spanning tree histogram as a verification tool for multidimensional ensemble forecasts publication-title: Mon Weather Rev doi: 10.1175/1520-0493(2004)132<1329:TMSTHA>2.0.CO;2 – volume: 227 start-page: 3515 year: 2008 ident: 10.1016/j.apenergy.2011.11.004_b0085 article-title: Ensemble forecasting publication-title: J Comput Phys doi: 10.1016/j.jcp.2007.02.014 – volume: 63 start-page: 71 year: 2000 ident: 10.1016/j.apenergy.2011.11.004_b0130 article-title: Predicting uncertainty in forecasts of weather and climate publication-title: Rep Prog Phys doi: 10.1088/0034-4885/63/2/201 – volume: 12 start-page: 1725 year: 2008 ident: 10.1016/j.apenergy.2011.11.004_b0025 article-title: A review on the young history of the wind power short-term prediction publication-title: Renew Sust Energ Rev doi: 10.1016/j.rser.2007.01.015 – volume: 26 start-page: 1367 year: 2011 ident: 10.1016/j.apenergy.2011.11.004_b0060 article-title: Stochastic optimization model to study the operational impact of high wind power penetrations in ireland publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2010.2070848 – ident: 10.1016/j.apenergy.2011.11.004_b0030 doi: 10.2172/968212 – year: 2003 ident: 10.1016/j.apenergy.2011.11.004_b0160 – volume: 20 start-page: 199 year: 1969 ident: 10.1016/j.apenergy.2011.11.004_b0040 article-title: Prediction with a generalized cost of error function publication-title: Oper Res Quar doi: 10.1057/jors.1969.52 – volume: 12 start-page: 51 year: 2009 ident: 10.1016/j.apenergy.2011.11.004_b0075 article-title: From probabilistic forecasts to statistical scenarios of short-term wind power production publication-title: Wind Energy doi: 10.1002/we.284 – volume: 87 start-page: 843 year: 2010 ident: 10.1016/j.apenergy.2011.11.004_b0080 article-title: A methodology to generate statistically dependent wind speed scenarios publication-title: Appl Energy doi: 10.1016/j.apenergy.2009.09.022 – volume: 17 start-page: 211 year: 2008 ident: 10.1016/j.apenergy.2011.11.004_b0105 article-title: Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds publication-title: Test doi: 10.1007/s11749-008-0114-x – volume: 10 start-page: 453 year: 2007 ident: 10.1016/j.apenergy.2011.11.004_b0175 article-title: Detecting, categorizing and forecasting large ramps in wind farm power output using meteorological observations and WPPT publication-title: Wind Energy doi: 10.1002/we.235 – volume: 35 start-page: 1381 year: 2010 ident: 10.1016/j.apenergy.2011.11.004_b0010 article-title: The role of district heating in future renewable energy systems publication-title: Energy doi: 10.1016/j.energy.2009.11.023 – volume: 69 start-page: 243 year: 2007 ident: 10.1016/j.apenergy.2011.11.004_b0090 article-title: Probabilistic forecasts, calibration and sharpness publication-title: J Roy Stat Soc B doi: 10.1111/j.1467-9868.2007.00587.x – volume: 25 start-page: 554 year: 2010 ident: 10.1016/j.apenergy.2011.11.004_b0070 article-title: Short-term trading for a wind power producer publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2009.2036810 – volume: 23 start-page: 752 year: 2008 ident: 10.1016/j.apenergy.2011.11.004_b0185 article-title: Two extra components in the Brier score decomposition publication-title: Weather Forecast doi: 10.1175/2007WAF2006116.1 – ident: 10.1016/j.apenergy.2011.11.004_b0035 – volume: 78 start-page: 1 year: 1950 ident: 10.1016/j.apenergy.2011.11.004_b0200 article-title: Verification of forecasts expressed in terms of probability publication-title: Mon Weather Rev doi: 10.1175/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2 – ident: 10.1016/j.apenergy.2011.11.004_b0020 doi: 10.2172/1216743 – ident: 10.1016/j.apenergy.2011.11.004_b0125 – year: 1995 ident: 10.1016/j.apenergy.2011.11.004_b0165 |
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| Snippet | ► Presentation of the desirable properties of wind power generation scenarios. ► Description of various evaluation frameworks (univariate, multivariate,... Scenarios of short-term wind power generation are becoming increasingly popular as input to multistage decision-making problems e.g. multivariate stochastic... |
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| SubjectTerms | 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 |
| Title | Evaluating the quality of scenarios of short-term wind power generation |
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