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SUMMARY:Robust Market Potential Assessment: Designing optimal low-carbon po
 licies in an increasingly uncertain world
DESCRIPTION:Robust Market Potential Assessment: Designing optimal low-carbo
 n policies in an increasingly uncertain world\nAssessing the potential of 
 low-carbon technologies is vital to ensure successful transition to net-ze
 ro emissions. This may include technical assessment of technologies\, or t
 he design of future energy scenarios via policy-instruments. The design of
  successful policies becomes increasingly difficult when associated factor
 s are uncertain\, such as energy prices or technology efficiencies.\nIn th
 is work we formulate the market potential assessment problem as a robust o
 ptimisation problem\, resulting in policies that are immune to uncertain f
 actors. We demonstrate two case studies: the potential use of carbon captu
 re and storage for iron and steel production across the EU\, and the trans
 ition to hydrogen from natural gas in steam boilers across the chemicals i
 ndustry in the UK. Each robust optimisation problem is solved using an ite
 rative cutting planes algorithm which enables existing models to be solved
  under uncertainty with no reformulation. By taking advantage of paralleli
 sation we are able to solve the nonlinear robust market allocation problem
  in times within the same order of magnitude to the nominal problem. Polic
 y makers often wish to trade-off certainty with effectiveness of a solutio
 n. Therefore\, we apply an approximation to chance constraints\, varying t
 he amount of uncertainty to locate less certain but more effective solutio
 ns. Our results demonstrate the possibility of locating robust policies fo
 r the implementation of low-carbon technologies\, as well as providing dir
 ect insights for policy-makers into the decrease in policy effectiveness t
 hat results from increasing robustness. The approach we present is extensi
 ble to a large number of policy design and market potential assessment pro
 blems.\nBiography:\nTom Savage is a PhD student working in the Centre for
  Process Systems Engineering\, supervised by Dr Antonio Del Rio Chanona an
 d Dr Gbemi Oluleye. His research focusses on the use of machine learning a
 nd optimisation for process systems engineering. Currently he is working o
 n the optimisation of energy policy problems under uncertainty as well as 
 the optimisation of expensive CFD simulations under collaboration with Pro
 f Matar’s group. Before attending Imperial College he studied at the Uni
 versity of Manchester and the University of Cambridge.\nAbout Energy Futur
 es Lab\nEnergy Futures Lab is one of seven Global Institutes at Imperial 
 College London. The institute was established to address global energy cha
 llenges by identifying and leading new opportunities to serve industry\, g
 overnment and society at large through high quality research\, evidence an
 d advocacy for positive change. The institute aims to promote energy innov
 ation and advance systemic solutions for a sustainable energy future by br
 inging together the science\, engineering and policy expertise at Imperial
  and fostering collaboration with a wide variety of external partners.
URL:https://www.imperial.ac.uk/events/156500/robust-market-potential-assess
 ment-designing-optimal-low-carbon-policies-in-an-increasingly-uncertain-wo
 rld/
DTSTART;TZID=Europe/London:20230126T120000
DTEND;TZID=Europe/London:20230126T130000
LOCATION:Room 611\, Electrical & Electronic Engineering\, South Kensington 
 Campus\, Imperial College London\, London\, SW7 2AZ\, United Kingdom
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