Community and local energy systems are an emerging feature of the global energy systems as communities and organisations look to reduce their carbon footprint in power, transport, and heat use. Smaller scale, decentralised technologies associated with renewable energy such as solar, wind and energy storage and control systems are developing at a much more rapid pace than larger scale infrastructure. At the same time, ICT applications in the energy sector are transforming the traditional ways of design and operating energy systems and how energy markets are organised. Operation of physical infrastructure systems, advanced edge computing and communication and complex controls and energy markets continue to be integrated creating new applications and services in the energy sector.

While the fundamental research in this area continues to be developed, there is a real urgency for innovation and applied research using real-life demonstrators to swiftly move from desktop based simulation studies to near commercial applications through strong partnerships between academia and industry.

This PhD project aims to investigate,

1. the cost-effective integration of real time observability and grid edge computing enabled by advanced ICT to energy systems planning, operation and control
2. mathematical model and data driven approaches supported by machine learning and Artificial Intelligence for multi-vector energy systems modelling
3. advanced control of local multi-vector energy systems for energy system optimisation and grid services provision
4. novel and fast clearing local energy markets for automated distribution grid management
5. set up of Cardiff University campus as a living lab for multi-vector urban energy systems research