Extreme value analysis of wind droughts in Great Britain
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Abstract:
Due to the growing proportion of wind energy in Great Britain's energy mix, prolonged periods of low wind power generation have become a significant challenge for decarbonising the electricity system. As such, characterising drought severity and duration is important for ensuring the reliability of the electricity system. Employing concepts derived from hydrology, an extreme value analysis was carried out on wind drought events in Great Britain based on 72 years of ERA5 reanalysis data. The application of pooling procedures was found to be beneficial in robustly identifying wind droughts in cases where the capacity factor is not constantly below an arbitrary threshold. The sequent peak algorithm pooling was found to have particular relevance for electricity systems where energy storage technologies are used to compensate for low wind power generation. The Pearson-III distribution was identified as a suitable model to represent extreme wind droughts, while the Lognormal and Generalised Pareto distributions are also viable alternatives. Sustained periods of low wind power generation with a duration of 14 days were estimated to have a return period of five years and the longest event on record of approximately 26 days is expected to occur once every 100 years. The investigation of these wind droughts from a hydrological perspective has thus shown that they may not be particularly rare occurrences.Keywords:
Value (mathematics)
Today different methods are used to solve extreme-value problems, e.g. the presentation of extreme values by particular distribution functions or the limitation of extreme-value regions by the definition of a limit (quantile values etc.). With the latter method all values below or above the limit are defined as extreme events. The disadvantage of this method is that the definition of the limit is more or less arbitrary, as long as physical limits are not available. To remedy this disadvantage a new method is presented which allows a region in statistical terms of extreme values to be defined which is entirely separated from the remainder of the examined series. (orig./KW).
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