Geopolitical and socio-economic uncertainties are putting the European and Global energy transitions at stake. These deep uncertainties affect the analytical assessments underpinning energy and climate policies. For example, the models used to inform energy planning rely on uncertain forecasts and assumptions for future energy demands, macroeconomic indicators, social acceptance, fuel prices, technology costs, and climate scenarios. Due to fundamental methodological, computational, and data challenges, this uncertainty is at best rarely considered in energy planning, which increases the risk of failing to meet our urgent climate targets. This makes accounting for uncertainty one of the major unsolved problems in energy planning.

UNITES addresses these limitations to enable a new paradigm for long-term energy planning. In contrast to current approaches, which try to accurately predict the future, UNITES’ ambition is a systematic integration of uncertainty in energy-climate models.

Expected Results

The project will result in three fundamental contributions: (i) theoretical developments to consider different types of uncertainty in energy planning models; (ii) data to quantify and characterize input uncertainties; (iii) AI methods to streamline the complex outputs of uncertainty studies into interpretable policy decisions.

The transferable and interdisciplinary developments across the data science, energy, and social sciences domains, unique to Europe and not available in concert elsewhere in the world, will bring about a breakthrough scientific contribution by overcoming important barriers for uncertainty analyses in a wide array of disciplines. The project will also be highly impactful on society, bringing together for the first time quantitative and qualitative dimensions to provide decisionmakers with actionable policies to steer the energy transition, which will be central to ensuring that we can meet our climate neutrality targets in the face of a highly unpredictable future.