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Atmospheric circulation, seasonal predictability and Britain’s energy system

Thornton, H. E. (2020) Atmospheric circulation, seasonal predictability and Britain’s energy system. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00095832


This PhD explores the influence of winter weather on the British energy system. It investigates the effect of weather variability on electricity and gas demand and on wind power generation. Weather-driven extremes of energy demand have a significant impact on the wider energy system, and therefore their risk is quantified and the driving circulation patterns identified. In addition, to potentially improve the energy sector’s preparedness for winter, the skill of seasonal weather forecasts to predict winter energy demand is assessed. The analysis indicates that energy demand has a strong anti-correlation with temperature, once socio-economic influences are removed. A 1 ◦C reduction in temperature typically gives a 1% increase in daily electricity demand and a 3%-4% increase in gas demand. The risk of extreme demand is assessed using a long temperature record and the modern-day temperature-demand relationship. For example, the risk of a winter having at least as much energy demand as December 2010 is estimated to be one in ∼34 years (95% confidence interval of 20-60 years). To assess the ability of wind turbines to provide power during high electricity demand, the relationship between wind power and demand is characterised. In winter, average wind power availability reduces by a third between lower and higher demand. However, during highest demand there is a modest recovery in wind power. This relationship is driven by the large-scale weather patterns affecting Northern Europe. During high demand events, neighbouring countries may struggle to provide additional capacity due to concurrent low temperatures and reduced wind power. Skilful predictions of winter mean gas demand and the number of extreme demand days over the winter period are possible from seasonal forecasts initialised in November. Use of such forecasts could help improve the security of gas supplies and reduce the impacts associated with extreme demand events.

Item Type:Thesis (PhD)
Thesis Supervisor:Hoskins, B., Scaife, A. and Brayshaw, D.
Thesis/Report Department:Department of Meteorology
Identification Number/DOI:
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:95832
Date on Title Page:November 2018


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