Research

The energy system is undergoing a paradigm shift to integrate renewable and sustainable energy sources for emission reduction and digital technologies for smarter operations and control. The future sustainable energy system will have a large number of renewable generations and digital devices, posing challenges to the reliability, stability, and cybersecurity of the system.

Our team is focused on developing cutting-edge optimisation and AI methods to solve problems of sustainability, from developing scalable algorithms for bulk power system planning under high penetration of renewables, decentralised optimisation for distributed energy source integration to investigating various market mechanisms for multiple stakeholders in the energy system, and cybersecurity problems in digitalised grids.

We work on both targeted and generic solving techniques to address complex optimisation problems (such as discrete and nonconvex problems), with the view to making optimisation technologies more widely accessible, across a range of applications, with a recent focus on addressing the following fundamental energy and sustainability challenges.

1. Computationally efficient tools for supporting decision-making in bulk power system planning toward net-zero, considering available low-carbon sources, economic viability, environmental impact, system stability, and resilience.
2. Distributed and decentralised operational paradigm and AI-accelerated optimisation for integrating new technologies, such as VPP, electric vehicles, battery storage, PV, demand response, and other flexible and distributed energy resources primarily in the distribution network.
3. Market mechanism design and simulations for supporting interactions of strategic players in the future energy system, such as generators, consumers, prosumers, operators, and aggregators.
4. Innovative algorithms for advancing the cybersecurity and privacy of the future grid, such as detection, prevention, and mitigation of cyber-attacks in digitalised energy systems.