Wind Power Forecasting Error Distributions over Multiple Timescales

Bri Mathias Hodge, Michael Milligan

Research output: Contribution to conferencePaperpeer-review

251 Scopus Citations

Abstract

Wind forecasting is an important consideration in integrating large amounts of wind power into the electricity grid. The wind power forecast error distribution assumed can have a large impact on the confidence intervals produced in wind power forecasting. In this work we examine the shape of the persistence model error distribution for ten different wind plants in the ERCOT system over multiple timescales. Comparisons are made between the experimental distribution shape and that of the normal distribution. The shape of the distribution is found to change significantly with the length of the forecasting timescale. The Cauchy distribution is proposed as a model distribution for the forecast errors and model parameters are fitted. Finally, the differences in confidence intervals obtained using the Cauchy distribution and the normal distribution are compared.

Original languageAmerican English
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future - Detroit, MI, United States
Duration: 24 Jul 201128 Jul 2011

Conference

Conference2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future
Country/TerritoryUnited States
CityDetroit, MI
Period24/07/1128/07/11

Bibliographical note

See NREL/CP-5500-50614 for preprint

NREL Publication Number

  • NREL/CP-5500-53784

Keywords

  • error probability
  • forecasting
  • stochastic systems
  • wind energy
  • Wind power generation

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