Analysis of Variability and Uncertainty in Wind Power Forecasting

An International Comparison

Jie Zhang, Bri-Mathias Hodge, Jari J. Miettinen, Hannele Holttinen, Emilio Gómez-Lázaro, Nicolaos Cutululis, Marisciel Litong-Palima, Poul Sørensen, Anne Line Lovholm, Erik Berge, Jan Dobschinski

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

Abstract

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer
Original languageEnglish
Title of host publicationProceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013
Place of PublicationDarmstadt
PublisherEnergynautics GmbH
Number of pages7
ISBN (Print)978-3-9813870-7-0
Publication statusPublished - 2013
MoE publication typeB3 Non-refereed article in conference proceedings
Event12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW13 - London, United Kingdom
Duration: 22 Oct 201324 Oct 2013
Conference number: 12

Conference

Conference12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW13
Abbreviated titleWIW13
CountryUnited Kingdom
CityLondon
Period22/10/1324/10/13

Fingerprint

international comparison
wind power
forecast
analysis
winter
estimation method
power generation

Keywords

  • Wind forecasting
  • reliability
  • power systems
  • uncertainty
  • variability

Cite this

Zhang, J., Hodge, B-M., Miettinen, J. J., Holttinen, H., Gómez-Lázaro, E., Cutululis, N., ... Dobschinski, J. (2013). Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison. In Proceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013 Darmstadt: Energynautics GmbH.
Zhang, Jie ; Hodge, Bri-Mathias ; Miettinen, Jari J. ; Holttinen, Hannele ; Gómez-Lázaro, Emilio ; Cutululis, Nicolaos ; Litong-Palima, Marisciel ; Sørensen, Poul ; Lovholm, Anne Line ; Berge, Erik ; Dobschinski, Jan. / Analysis of Variability and Uncertainty in Wind Power Forecasting : An International Comparison. Proceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013. Darmstadt : Energynautics GmbH, 2013.
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title = "Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison",
abstract = "One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer",
keywords = "Wind forecasting, reliability, power systems, uncertainty, variability",
author = "Jie Zhang and Bri-Mathias Hodge and Miettinen, {Jari J.} and Hannele Holttinen and Emilio G{\'o}mez-L{\'a}zaro and Nicolaos Cutululis and Marisciel Litong-Palima and Poul S{\o}rensen and Lovholm, {Anne Line} and Erik Berge and Jan Dobschinski",
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Zhang, J, Hodge, B-M, Miettinen, JJ, Holttinen, H, Gómez-Lázaro, E, Cutululis, N, Litong-Palima, M, Sørensen, P, Lovholm, AL, Berge, E & Dobschinski, J 2013, Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison. in Proceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013. Energynautics GmbH, Darmstadt, 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW13, London, United Kingdom, 22/10/13.

Analysis of Variability and Uncertainty in Wind Power Forecasting : An International Comparison. / Zhang, Jie; Hodge, Bri-Mathias; Miettinen, Jari J.; Holttinen, Hannele; Gómez-Lázaro, Emilio; Cutululis, Nicolaos; Litong-Palima, Marisciel; Sørensen, Poul; Lovholm, Anne Line; Berge, Erik; Dobschinski, Jan.

Proceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013. Darmstadt : Energynautics GmbH, 2013.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientific

TY - GEN

T1 - Analysis of Variability and Uncertainty in Wind Power Forecasting

T2 - An International Comparison

AU - Zhang, Jie

AU - Hodge, Bri-Mathias

AU - Miettinen, Jari J.

AU - Holttinen, Hannele

AU - Gómez-Lázaro, Emilio

AU - Cutululis, Nicolaos

AU - Litong-Palima, Marisciel

AU - Sørensen, Poul

AU - Lovholm, Anne Line

AU - Berge, Erik

AU - Dobschinski, Jan

N1 - Project code: 78560 1.6

PY - 2013

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N2 - One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer

AB - One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer

KW - Wind forecasting

KW - reliability

KW - power systems

KW - uncertainty

KW - variability

M3 - Conference article in proceedings

SN - 978-3-9813870-7-0

BT - Proceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013

PB - Energynautics GmbH

CY - Darmstadt

ER -

Zhang J, Hodge B-M, Miettinen JJ, Holttinen H, Gómez-Lázaro E, Cutululis N et al. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison. In Proceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013. Darmstadt: Energynautics GmbH. 2013