Skip to main navigation Skip to search Skip to main content

Variability in large-scale wind power generation

  • Juha Kiviluoma*
  • , Hannele Holttinen
  • , David Weir
  • , Richard Scharff
  • , Lennart Soder
  • *Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The paper demonstrates the characteristics of wind power variability and net load variability in multiple power systems based on real data from multiple years. Demonstrated characteristics include probability distribution for different ramp durations, seasonal and diurnal variability and low net load events. The comparison shows regions with low variability (Sweden, Spain and Germany), medium variability (Portugal, Ireland, Finland and Denmark) and regions with higher variability (Quebec, Bonneville Power Administration and Electric Reliability Council of Texas in North America; Gansu, Jilin and Liaoning in China; and Norway and offshore wind power in Denmark). For regions with low variability, the maximum 1?h wind ramps are below 10% of nominal capacity, and for regions with high variability, they may be close to 30%. Wind power variability is mainly explained by the extent of geographical spread, but also higher capacity factor causes higher variability. It was also shown how wind power ramps are autocorrelated and dependent on the operating output level. When wind power was concentrated in smaller area, there were outliers with high changes in wind output, which were not present in large areas with well-dispersed wind power.
Original languageEnglish
Pages (from-to)1649-1665
JournalWind Energy
Volume19
Issue number9
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • wind power
  • variability
  • net load
  • variable generation
  • power systems

Fingerprint

Dive into the research topics of 'Variability in large-scale wind power generation'. Together they form a unique fingerprint.

Cite this