Policy goals to transition national energy systems to meet decarbonisation and security goals must contend with multiple overlapping uncertainties. These uncertainties are pervasive through the complex nature of the system, and exist in a strategic policy area where the impact of investment decisions have long term consequences. Uncertainty also lies in the tools and approaches used, increasing the challenges of informing robust decision making. Energy system studies in the UK have tended not to address uncertainty in a systematic manner, relying on simple scenario or sensitivity analysis. This paper utilises an innovative energy system model, ESME, which characterises multiple uncertainties via probability distributions and propagates these uncertainties to explore trade-offs in cost effective energy transition scenarios. A global sensitivity analysis is then undertaken to explore the uncertainties that have most impact in the long term mitigation pathways.
The analysis highlights the strong impact of uncertainty on delivering the required emission reductions under a given carbon price. In the mid-term (2030), the likelihood of meeting legislated reduction targets is extremely sensitive to the carbon price level, with a modest reduction or increase in carbon pricing leading to the target being or not being met. The uncertainty in the carbon price level for achieving emissions mitigation increases further in the longer term (2050). The cost and availability of a range of technologies is key in delivering required reductions; in the mid-term, decarbonisation of the power sector is critical, with cost-effective nuclear and CCS technologies playing a vital role. In the longer term, the availability of biomass for use in CCS technologies (power and biofuel production) along with the cost of nuclear technologies and gas prices play a critical role in delivering emission reductions.
Further iteration of this energy systems uncertainty analysis is needed with policy makers and stakeholders around the role of uncertainties. Key questions include whether these uncertainty impacts are likely to play out in reality or are a function of the modelling, and the scope of the uncertainty analysis i.e. what is missing and what else is needed. Such iteration allows us to determine the robustness and relevance of the insights emerging from this analysis for informing future UK low carbon transitions.