Biography
Professor Thomas Morstyn received the BEng (Hon.) degree from the University of Melbourne in 2011, and the PhD degree from the University of New South Wales in 2016, both in electrical engineering. Previously, Thomas was a lecturer at the University of Edinburgh and an EPSRC research fellow at the University of Oxford. Prior to undertaking his PhD, he also worked as an electrical engineer in Rio Tinto’s Technology and Innovation group.
Thomas is now Associate Professor in Power Systems with the Department of Engineering Science, University of Oxford, a Tutorial Fellow at Hertford College and an Honorary Fellow at the University of Edinburgh. He is also an Associate Editor of IEEE Transactions on Power Systems and Co-Chair of the IEEE Power & Energy Society Taskforce on Power System Operations and Control with Quantum Computing. His research is focused on the design of control systems and markets to enable the large-scale integration of distributed power system flexibility.
Most Recent Publications
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
Opportunities for quantum computing within net-zero power system optimization
Opportunities for quantum computing within net-zero power system optimization
Datasets of Great Britain primary substations integrated with household heating information
Datasets of Great Britain primary substations integrated with household heating information
Research Interests
Power systems are undergoing a fundamental transition due to the rapid adoption of distributed renewable generation, the electrification of heating and transport, and the new availability of customer-level sensing, communications and control. Thomas’s research focuses on the design of control systems and markets which can manage this transition by integrating distributed flexibility at scale into power system operation and design. This is underpinned by work in systems modelling, multi-agent control, optimisation and mechanism design.
Thomas also collaborates with economists, computer scientists and social scientists to incorporate new advances from areas including game theory, machine learning and quantum computing, and to study the wider impacts and policy implications of new power system technologies.
Current Projects
- An AI-Powered Software Platform for Smart Hybrid Distribution Systems (Innovate UK Knowledge Transfer Partnership with IONATE) - This project aims to develop an AI-powered software platform for optimisation and control of IONATE’s hybrid intelligent transformers to enable their widespread integration into distribution systems.
- DIGEST: Data-Driven Exploration of the Carbon Emissions Impact of Grid Energy Storage Deployment and Dispatch (EPSRC project EP/W027321/1) - This project is investigating the potential value for system cost and carbon emissions that optimal grid energy storage deployment and operation could unlock in Great Britain. The project is a collaboration with Professor David Howey at the University of Oxford, Professor Tim Green at Imperial College London and Dr Marko Aunedi at Brunel University London.
- Benchmarking Quantum Advantage (EPSRC project EP/Y004418/1) - This project aims to develop easy to deploy quantum advantage benchmarking techniques. Power system optimisation is being investigated as a high value application. The project is a collaboration with Dr Raul Garcia-Patron Sanchez and Dr Heng Guo at the University of Edinburgh.
Software & Models
- A high fidelity 1900-node model for Great Britain's transmission network and Balancing Mechanism combining data from the National Grid Electricity 10 Year Statement and market data from Elexon. Developed with Dr Iacopo Savelli.
- The Open Platform for Local Energy Markets (OPLEM) is an open-source Python software platform for integrated modelling, design and simulation of local energy markets. Developed with Dr Chaimaa Essayeh.
- The Open Platform for Energy Networks (OPEN) is an open-source Python software platform for integrated modelling, optimisation and simulation of smart local energy systems. Developed in collaboration with Professor Malcolm McCulloch.
- The Home Energy Data Generator (HEDGE) tool for GAN-based synthetic data generation for domestic PV generation, electricity consumption, and electric vehicle consumption/availability based on UK historical datasets. Developed with Dr Flora Charbonnier and Professor Malcolm McCulloch.
Most Recent Publications
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
Opportunities for quantum computing within net-zero power system optimization
Opportunities for quantum computing within net-zero power system optimization
Datasets of Great Britain primary substations integrated with household heating information
Datasets of Great Britain primary substations integrated with household heating information
Most Recent Publications
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
Opportunities for quantum computing within net-zero power system optimization
Opportunities for quantum computing within net-zero power system optimization
Datasets of Great Britain primary substations integrated with household heating information
Datasets of Great Britain primary substations integrated with household heating information
DPhil Opportunities
I am always happy to discuss DPhil supervision with students who share my research interests in power systems and energy markets. Please email me at thomas.morstyn@eng.ox.ac.uk with your CV, latest academic transcript and topic areas you find interesting.
Most Recent Publications
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
An incentive regulation approach for balancing stakeholder interests in transmission merchant investment
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A novel surrogate polytope method for day-ahead virtual power plant scheduling with joint probabilistic constraints
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
A Competitive Showcase of Quantum versus Classical Algorithms in Energy Coalition Formation
Opportunities for quantum computing within net-zero power system optimization
Opportunities for quantum computing within net-zero power system optimization
Datasets of Great Britain primary substations integrated with household heating information
Datasets of Great Britain primary substations integrated with household heating information