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Resilient net-zero decarbonisation in Europe through near-optimal transition pathways of the energy system
Summary
Original abstract (not yet simplified)Europe is decarbonising in turbulent times, a complex endeavour requiring decades of prudent policymaking. The implementation needs to be sustainable, resilient to shocks, and to be truly successful, socially acceptable. Long-term planning of the energy transition is often modelled mathematically by optimising energy system costs. Decision making in the real world is more complex and needs to consider other aspects...
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Europe is decarbonising in turbulent times, a complex endeavour requiring decades of prudent policymaking. The implementation needs to be sustainable, resilient to shocks, and to be truly successful, socially acceptable. Long-term planning of the energy transition is often modelled mathematically by optimising energy system costs. Decision making in the real world is more complex and needs to consider other aspects including modelling that explores cost-near-optimal solutions and other desirable outcomes beyond cost. Methods based on near-optimality show trade-offs and many diverse end states of a net-zero system in Europe, but so far cannot answer the question: How can we design net-zero pathways that are socially acceptable and resilient to risks such as natural disasters or geopolitics? With climate change, geopolitical upheaval, and technological uncertainty, it is crucial to understand how to absorb predictable uncertainties and risks. To date, no framework exists that can integrate such stress tests into energy modelling to produce resilient system designs. RESNOT will develop a novel methodology that applies near-optimal methods to pathway optimisation in energy modelling to enable the identification of no-regrets decisions, the classification of risk factors within the European energy system, and integration into a framework for stress testing near-optimal system designs and transition pathways against risk. During the secondment at Newcastle University, I plan to exemplify the benefits by considering weather and natural disaster risks. This framework can be generalised as a standardised approach including other disciplines and risks in the future. This project will further develop existing open models, PyPSA and PyPSA-Eur, and advance the state-of-the-art of long-term energy planning. Lastly, the MSCA fellowship will expand my skills enabling me to become an independent researcher.
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Original classification
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