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Details of Grant 

EPSRC Reference: EP/K02115X/1
Title: Development and Evaluation of Sustainable Technologies for Flexible Operation of Conventional Power Plants.
Principal Investigator: Hogg, Professor SI
Other Investigators:
Chalmers, Dr H Ingram, Dr GL Pourkashanian, Professor M
Gibbins, Professor J Williams, Professor A Jones, Professor JM
White, Dr AJ Rosic, Dr B Lucquiaud, Professor MS
Dent, Professor C Harrison, Professor GP Bialek, Dr JW
Young, Professor J He, Professor L Kazemtabrizi, Dr B
Researcher Co-Investigators:
Project Partners:
Alstom Group ANSYS National Grid
Scottish and Southern Energy (SSE) Sinclair Knight Merz(Europe) Ltd(Jacobs)
Department: Engineering
Organisation: Durham, University of
Scheme: Standard Research
Starts: 16 September 2013 Ends: 14 March 2019 Value (£): 1,944,441
EPSRC Research Topic Classifications:
Energy - Conventional Power Systems Plant
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
22 Nov 2012 EPSRC Future Conventional Power Research Consortium Announced
Summary on Grant Application Form
The increasing amounts of renewable energy present on the national grid reduce C02 emissions caused by electrical power but they fit into an electrical grid designed for fossil fuels. Fossil fuels can be turned on and off at will and so are very good at matching variations in load. Renewable energy in the form of wind turbines is more variable (although that variability is much more predictable than most people think) and there is a need for existing power plants to operate much more flexibly to accommodate the changing power output from wind, tidal and solar power.

This work brings together five leading Universities in the UK and a number of industrial partners to make conventional power plants more flexible. The research covers a wide range of activities from detailed analysis of power station parts to determine how they will respond to large changes in load all the way up to modelling of the UK electrical network on a national level which informs us as to the load changes which conventional power plants will need to supply.

The research work is divided up into a number of "workpackages" for which each University is responsible together they contribute to four major themes in the proposal: Maintaining Plant Efficiency, Improving Plant Flexibility, Increasing Fuel Flexibility and Delivering Sustainability.

Cambridge University will be conducting research into wet steam methods. Water is used as the working fluid in power plant as it has excellent heat transfer properties. However in the cold end of power extraction turbine the steam starts to condense into water and droplets form this is especially a problem at part load. The work at Cambridge will allow this process to be predicted better and lead to better designs.

Durham University will contribute two different work packages: modelling work of the entire UK power system and the introduction of the world's first dynamically controlled clearance seal. The modelling work will enable the requirements for plant flexibility to be determined accurately. The dynamic seal developed in conjunction with a major UK manufacturer will allow the turbine to maintain performance as the load varies.

Oxford University - Improved Heat Transfer Methods for Turbine Design. The output from this work will be a highly accurate coupled fluid flow and heat transfer calculations that will enable designers to better predict the thermal transients inside power stations.

Leeds and Edinburgh University will lead work on increasing the use of biomass fuels. The modelling work at Leeds will allow plant operators to devise suitable measures to minimise the environmental impact of burning biomass.

Leeds and Edinburgh University will contribute the development of a Virtual Power Plant Simulation Tool This work acts as a bridge between the different project partners as inputs from the models produced at Durham, Cambridge, Oxford and Leeds are combined. This tool based on the latest research findings can be used to optimize transient operations such as fast start-up and load following as wind turbine output varies.
Key Findings
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