English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper investigates the use of extreme value theory for modelling thedistribution of demand-net-of-wind for capacity adequacy assessment. Extremevalue theory approaches are well-established and mathematically justifiedmethods for estimating the tails of a distribution and so are ideally suitedfor problems in capacity adequacy, where normally only the tails of therelevant distributions are significant. The extreme value theory peaks overthreshold approach is applied directly to observations of demand-net-of-wind,meaning that no assumption is needed about the nature of any dependence betweendemand and wind.  The methodology is tested on data from Great Britain and compared to twoalternative approaches: use of the empirical distribution of demand-net-of-windand use of a model which assumes independence between demand and wind. Extremevalue theory is shown to produce broadly similar estimates of risk metrics tothe use of the above empirical distribution but with smaller samplinguncertainty. Estimates of risk metrics differ when the approach assumingindependence is used, especially when data across different historical yearsare pooled, suggesting that assuming independence might result in the over- orunder-estimation of risk metrics.

Using extreme value theory for the estimation of risk metrics for capacity adequacy assessment