Research

Our Leverhulme Global Power System Transformation team, hosted by the Department of Electrical and Electronic Engineering at Imperial College London, is set on developing  a set of new essential services based on electrical engineering, economics, and social factors to guide the transition towards higher penetrations of variable renewables in electricity grids. The research is done as an integral part of the Global Power System Transformation (G-PST) Consortium.  The research will address part of the G-PST Research Agenda and attention is drawn to a recent report on the evolution of needs and services with increasing penetration of Inverter Based Resources (IBRs).

These services aim to: 

  1. define physical characteristics of services across the entire range of time scales from milliseconds to seasons;
  2.  ensure that these services cover the whole space parsimoniously, avoiding negative interactions and redundancy;
  3. be robust and economic under all possible systems;
  4. be forward looking with respect to an electricity grid that has increasing levels of variable renewables; and
  5. be non-discriminatory towards various potential technical routes and hence both stimulate and be open to radical innovation.

To enable the energy transition by developing new essential services, the research programme have three distinct but inter-related strands:

Fundamental Analysis of Electricity Grids

Fundamental analysis of electricity grids with high penetrations of variable renewables to extract the core characteristics across all time scales and physical attributes that deliver on the socio-technical objectives described above.

Analytical Underpinning of Digitisation

The “smart grid” concept is maturing into fundamental research into how to harness “digitisation”, i.e. machine-learning, internet-of-things and edge technologies, to characterise and access millions of distributed resources (renewables, storage and active demand) that can provide essential services in a secure and efficient manner.

Testing and Validation

This will require development of best in class models and case studies of future grids to validate the essential services and the digital algorithms for different renewable mixes, gird size, social, economic and climate conditions.