###A Data-driven Distributionally Robust Optimization Framework for Coordinated Decision Making in Whole Energy Systems
Project ID: 2228bd1086 (You will need this ID for your application)
Research Theme: Mathematical Sciences
UCL Lead department: Statistical Science
Lead Supervisor: Sebastian Maier
Project Summary:
Why this research is important?
This project will investigate how coordinated decision-making policies between actors in power, heat, transport and related systems can be used for effective decarbonisation of energy systems under uncertainty. Doing so is especially challenging due to the actors’ conflicting objectives and the technology’s multiple flexibilities. Moreover, decision making is plagued by various sources of uncertainty including wholesale gas and electricity prices as well as transport and heat demand.
Who you will be working with?
The supervisory team consists of Dr Sebastian Maier (UCL Department of Statistical Science; primary), Prof Afzal Siddiqui (UCL Department of Statistical Science, and Department of Computer and Systems Sciences at Stockholm University; subsidiary), and Prof Paul Dodds (UCL Energy Institute and Institute for Sustainable Resources; subsidiary).
What you will be doing?
To achieve these ambitious goals, this PhD project will leverage various OR methodologies including (but not limited to) distributionally robust optimisation, bi-level programming and game/decision theory as well as stochastic and equilibrium modelling.
Who we are looking for?
Prospective applicants should have strong quantitative skills and evidence of research experience (e.g., MSc dissertation project), but there is flexibility to take a candidate from a range of quantitative backgrounds (incl. mathematics, OR, statistics, economics/finance, (industrial) engineering, and computer science), adjusting the precise direction of PhD research accordingly.