Assessing the Shortfall Risk of GB Electricity Grid using Shifts in Winter Weather Conditions
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866908986775699456 |
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| author | Bhattacharya, Aninda Dent, Chris J. Wilson, Amy L. Hegerl, Gabriele C. |
| author_facet | Bhattacharya, Aninda Dent, Chris J. Wilson, Amy L. Hegerl, Gabriele C. |
| contents | Extreme weather events during peak winter periods drive resource adequacy risk in Great Britain (GB), with weather sensitivity of the supply-demand balance increasing through additional electric heating and wind generation. This work develops an approach of time-shifting weather within the peak season, through adjustment of the relevant terms in a statistical model for demand. This allows more complete consideration of the security of supply consequences of a weather series, as there will be relevant conditions where demand is suppressed due to weather occurring at a weekend or during the Christmas holiday. Results on a GB example show that consideration of this counterfactual is indeed important, and specifically that winter 2010-11 can either be the most severe in the dataset, or insignificant within the resource adequacy model, depending on the alignment of day-of-week with the weather series. Statistical interpretation of the shift model is discussed, which is straightforward for alignment of day-of-week with weather assuming that all seven alignments are equiprobable; but is more subtle for shifting weather in and out of Christmas, as there is no natural maximum on the realistic length of shift, but too large a shift may be physically unrealistic. It is likely that in all systems, assessment of a weather year's severity is incomplete without such consideration of the day-of-week effect; however, whether longer shifts of weather with respect to date need to be considered will depend on the presence of a major holiday (such as Christmas in GB) in the peak season. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_20445 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Assessing the Shortfall Risk of GB Electricity Grid using Shifts in Winter Weather Conditions Bhattacharya, Aninda Dent, Chris J. Wilson, Amy L. Hegerl, Gabriele C. Applications Extreme weather events during peak winter periods drive resource adequacy risk in Great Britain (GB), with weather sensitivity of the supply-demand balance increasing through additional electric heating and wind generation. This work develops an approach of time-shifting weather within the peak season, through adjustment of the relevant terms in a statistical model for demand. This allows more complete consideration of the security of supply consequences of a weather series, as there will be relevant conditions where demand is suppressed due to weather occurring at a weekend or during the Christmas holiday. Results on a GB example show that consideration of this counterfactual is indeed important, and specifically that winter 2010-11 can either be the most severe in the dataset, or insignificant within the resource adequacy model, depending on the alignment of day-of-week with the weather series. Statistical interpretation of the shift model is discussed, which is straightforward for alignment of day-of-week with weather assuming that all seven alignments are equiprobable; but is more subtle for shifting weather in and out of Christmas, as there is no natural maximum on the realistic length of shift, but too large a shift may be physically unrealistic. It is likely that in all systems, assessment of a weather year's severity is incomplete without such consideration of the day-of-week effect; however, whether longer shifts of weather with respect to date need to be considered will depend on the presence of a major holiday (such as Christmas in GB) in the peak season. |
| title | Assessing the Shortfall Risk of GB Electricity Grid using Shifts in Winter Weather Conditions |
| topic | Applications |
| url | https://arxiv.org/abs/2604.20445 |