Simulating wind power forecast error distributions for spatially aggregated wind power plants

Jari Miettinen (Corresponding Author), Hannele Holttinen, Bri Mathias Hodge

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Dispersion and aggregation of wind power plants lower the uncertainty of wind power by reducing wind power forecasting errors. Using quantitative methods, this paper studies the dispersion's impact on the uncertainty of the aggregated wind power production. A method to simulate day‐ahead forecast error distributions at different dispersion and forecasting skill scenarios is presented. The proposed method models the uncertainty of wind power forecasting on an annual basis and at different levels of production. As a result, the uncertainty in the forecasting of spatially dispersed wind power plants is modelled using two continuous distributions: Laplace and beta distribution. The analysis shows that even the production level uncertainty can be modelled in various dispersion and forecasting skill scenarios. The model for aggregated forecast error distributions requires only four variables: capacity‐weighted distance of the total wind power plant fleet, mean of the site‐specific mean absolute errors (MAEs), number of aggregated wind power plants, and the mean variability of the elevations from the proximities of the aggregated wind power plants. The results are especially promising when the number of aggregated wind power plants exceeds five, the terrain complexity is low or moderate, and the aggregation region is large. This is demonstrated through a case study for Texas, United States.
Original languageEnglish
JournalWind Energy
DOIs
Publication statusAccepted/In press - 11 Sep 2019
MoE publication typeA1 Journal article-refereed

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Wind power
Power plants
Agglomeration
Uncertainty

Keywords

  • aggregated wind power production
  • wind power
  • wind power forecasting

Cite this

Miettinen, Jari ; Holttinen, Hannele ; Hodge, Bri Mathias. / Simulating wind power forecast error distributions for spatially aggregated wind power plants. In: Wind Energy. 2019.
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Simulating wind power forecast error distributions for spatially aggregated wind power plants. / Miettinen, Jari (Corresponding Author); Holttinen, Hannele; Hodge, Bri Mathias.

In: Wind Energy, 11.09.2019.

Research output: Contribution to journalArticleScientificpeer-review

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