EPSRC Reference: |
EP/M015025/1 |
Title: |
System Architecture Challenges: Supergen+ for HubNet |
Principal Investigator: |
Green, Prof. T |
Other Investigators: |
Milanovic, Professor JV |
Rowland, Professor SM |
Preece, Dr R |
Kockar, Dr I |
Gross, Professor R |
McArthur, Professor S |
Barria, Dr J |
Burt, Professor GM |
Galloway, Professor S |
Wu, Professor J |
Ugalde-Loo, Professor CE |
Strbac, Professor G |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Electrical and Electronic Engineering |
Organisation: |
Imperial College London |
Scheme: |
Standard Research - NR1 |
Starts: |
01 January 2015 |
Ends: |
31 December 2016 |
Value (£): |
763,980
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EPSRC Research Topic Classifications: |
Sustainable Energy Networks |
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EPSRC Industrial Sector Classifications: |
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Related Grants: |
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Panel History: |
Panel Date | Panel Name | Outcome |
28 Aug 2014
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SUPERGEN PLUS
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Announced
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Summary on Grant Application Form |
HubNet is a multi-university collaborative project which is three years into a five-year programme of exploring the future form of energy networks. In particular we are exploring the use of smart grid technologies and HVDC to integrate high penetrations of renewable energy into the electricity system and investigating how to manage changes in energy supply to private vehicles and building heating. It does this through its own programme of core research and through drawing together the research of the Grand Challenges projects in this area and other Research Council activities. This proposal is for an extension to the HubNet's core research in order to address challenges not identified in the original proposal.
Two themes appear in any discussion of the smart grid: (1) the opportunities for consumers to be become more active so that they benefit from trading their energy needs and production, and (2) the creation of an ICT system that generates very large volume of power flow and voltage data that can be harnessed to run the system more efficiently. Despite being a well known topic and the subject of research projects on specific aspects, there is still a lack of consensus over precisely how customers can play their role (in terms of choices they can make, technology to assist and markets that deliver value to all participants). There also remains a lack of clarity over what exactly is the challenge in power system operation to which "big data" technology is the answer. We seek to gain further understanding in these areas through stakeholder engagement activities.
We propose to explore further the opportunities of "big data" through a case study of data used in condition monitoring of transformers and cables to predict accurately lifetime and incipient failure.
A key feature of the electricity system is the low rate power cuts and the high dependence placed on electricity by modern society. Moving from a system where control is exercised primarily by actions in power stations to a system where consumers are encouraged to modify their behaviour and become part of the control and where some power sources (wind and PV for example) are not readily controlled radically changes the risk profile of the system. We propose to develop new analytical techniques to model this and plan future systems. A specific control problem that will be analysed in depth is the gradual removal from the system of the inertia provided by the spinning masses of conventional power station generators. This inertia helps keep the system frequency at 50 Hz. Already Ireland limits the production by wind turbines so that sufficient inertia is retained. We will explore where the limit lies for Great Britain and what innovations might advance that limit.
Finally to address the issues associated with increased uncertainties in system operation and mange the risk of system becoming less controllable and vulnerable to external disturbances, new methodologies will need to be developed to quantify the risk profile of a future power system and how this profile is affected by various epistemic (data shortage or model simplification) and aleatory (inherent random behaviour) uncertainties in system model and operation.
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Key Findings |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.imperial.ac.uk |