Using high resolution climate data to help prepare future energy systems for weather-driven extremes.

Energy systems across the world are rapidly evolving to meet climate mitigation targets. This requires a rapid transition to electricity systems lower reliance on fossil fuels and greater weather-dependent renewable generation (such as wind power, solar power, and hydropower). This increased weather dependence adds a new set of challenges for balancing supply and demand due to the inherent variability of weather, increasing the need for investment in storage and flexible technologies. The impacts of climate variability and climate change on national energy systems is a topic of current academic interest. Both in terms of security of supply risks from system level challenges (e.g., energy shortfall events, where existing generation is insufficient to meet demand) or from smaller-scale infrastructure challenges (e.g., extreme weather impacting the operability of energy system components).

This talk will discuss a programme of work on energy sector impacts using the UK Climate projections data (UKCP18). This is a suite of state-of-the-art climate model projections available at 60km resolution globally, 12km spatial resolution over Europe, and 2.2km resolution over the UK. Electricity demand, wind power, and solar photovoltaic power timeseries are developed for the period 1980-2080 using the regional climate model outputs. Climate data of this high spatial and temporal resolution is critical for the accurate quantification of meteorological hazards of relevance to the energy sector. The UK energy sector will be used as a case study in this talk due to its large share of variable renewables and commitments to reach net-zero emissions by 2050 and decarbonising the electricity system by 2035.

This talk will highlight weather-driven risks to the energy sector in both a present and future climate, with a particular focus on compound events. At short timescales examples of these risks could be periods of high demand combined with low wind power generation, or weather patterns extending over a very large area of Europe (therefore creating a spatial compound event) or sequences of extreme weather (such as several storms happening in quick succession, which could damage energy infrastructure). At longer timescales these types of compound events could be years with low renewable energy production relative to demand, or as successive years with low production. Future work will use the years containing extreme events highlighted in this talk as inputs within high resolution power system modelling simulations.