LSS26Jan23

Robust Market Potential Assessment: Designing optimal low-carbon policies in an increasingly uncertain world

Assessing the potential of low-carbon technologies is vital to ensure successful transition to net-zero emissions. This may include technical assessment of technologies, or the design of future energy scenarios via policy-instruments. The design of successful policies becomes increasingly difficult when associated factors are uncertain, such as energy prices or technology efficiencies.

In this work we formulate the market potential assessment problem as a robust optimisation problem, resulting in policies that are immune to uncertain factors. We demonstrate two case studies: the potential use of carbon capture and storage for iron and steel production across the EU, and the transition to hydrogen from natural gas in steam boilers across the chemicals industry in the UK. Each robust optimisation problem is solved using an iterative cutting planes algorithm which enables existing models to be solved under uncertainty with no reformulation. By taking advantage of parallelisation we are able to solve the nonlinear robust market allocation problem in times within the same order of magnitude to the nominal problem. Policy makers often wish to trade-off certainty with effectiveness of a solution. Therefore, we apply an approximation to chance constraints, varying the amount of uncertainty to locate less certain but more effective solutions. Our results demonstrate the possibility of locating robust policies for the implementation of low-carbon technologies, as well as providing direct insights for policy-makers into the decrease in policy effectiveness that results from increasing robustness. The approach we present is extensible to a large number of policy design and market potential assessment problems.

Biography:

Tom Savage is a PhD student working in the Centre for Process Systems Engineering, supervised by Dr Antonio Del Rio Chanona and Dr Gbemi Oluleye. His research focusses on the use of machine learning and optimisation for process systems engineering. Currently he is working on the optimisation of energy policy problems under uncertainty as well as the optimisation of expensive CFD simulations under collaboration with Prof Matar’s group. Before attending Imperial College he studied at the University of Manchester and the University of Cambridge.

About Energy Futures Lab

Energy Futures Lab is one of seven Global Institutes at Imperial College London. The institute was established to address global energy challenges by identifying and leading new opportunities to serve industry, government and society at large through high quality research, evidence and advocacy for positive change. The institute aims to promote energy innovation and advance systemic solutions for a sustainable energy future by bringing together the science, engineering and policy expertise at Imperial and fostering collaboration with a wide variety of external partners.

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