Climate change resulting from greenhouse gas emissions is a key issue for society. UK and Scottish governments have set an ambitious policy to cut emissions to net zero by 2050 and 2045, respectively. Energy system optimization models (ESOMs) are a key part of government decision support on potential pathways to decarbonisation, including studying the trade-offs between decarbonisation/sustainability, affordability, and security of supply. It is thus vital to consider an appropriate level of detail in energy system modelling studies with the aim of better prediction about relevant features of the real world.
One of the key ESOMs used in Scottish, UK and international energy policy is TIMES, which optimizes energy supply over the long term against given scenarios of planning background. In this project, we will extend current TIMES-like whole system modelling frameworks to stochastic formulations accounting for uncertainty in the background to planning and policy. The whole cycle of uncertainty treatment will be considered, from the uncertainty specification based on policymakers’ judgments, through efficient optimization computation, to communication of modelling results in the policymaking context. The key methodological point will be formulating the necessary stochastic linear program model and associated scenario tree, and solving it through scenario decomposition methods. This work will be informed by collaboration with government colleagues, who will consider how to take relevant applied methodology research to deployment in their energy modelling.
This project will be supervised by Prof. Chris Dent, in collaboration with relevant colleagues from the Operational Research and Statistics theme in the School of Mathematics.
Entry requirements:
Essential:
• A Bachelor’s degree in Statistics, Mathematics, Physics, Computer Science or similar (a First Class or good Upper Second Class Honours degree, or the equivalent from an overseas university, is required for PhD entry; a strong First Class Degree or equivalent is likely to be required for a School of Mathematics scholarship);
• Familiarity with applied linear program modelling, and associated LP decomposition methods;
• Strong verbal and written communication skills in English.
Desirable:
• Masters degree in a relevant subject;
• Familiarity with relevant areas of energy system analysis;
• Applied modelling experience with industry or government.
Application Procedure:
A formal application for this project can be made here: https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&edition=2020&id=516
You are advised to contact the supervisor before applying, although this is not essential.
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