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Details of Grant 

EPSRC Reference: EP/I000194/1
Title: Advanced Dynamic Energy Pricing and Tariffs (ADEPT)
Principal Investigator: Wallom, Professor D
Other Investigators:
Axon, Dr C Darby, Dr SJ Olteanu, Professor DA
Researcher Co-Investigators:
Project Partners:
Northern Ireland Electricity Networks
Department: Oxford e-Research Centre
Organisation: University of Oxford
Scheme: Standard Research
Starts: 01 October 2010 Ends: 30 December 2013 Value (£): 695,472
EPSRC Research Topic Classifications:
Artificial Intelligence Building Ops & Management
Energy Efficiency Human-Computer Interactions
EPSRC Industrial Sector Classifications:
Construction Information Technologies
Energy
Related Grants:
EP/I000119/1
Panel History:
Panel DatePanel NameOutcome
17 Mar 2010 Transforming Energy Demand Through Digital Innov Announced
Summary on Grant Application Form
This project addresses a crucial research question that must be answered in the near term is How complicated can, or should, a dynamic electricity tariff be? , such that it is accepted by the public and offers clear enhancements and incentives for reduction in energy demand? The 'can' and 'should' reflect the fact that any ubiquitous technical system is (primarily) designed and implemented by experts, but has to be accepted and operated by non-experts. This project looks at how the information potentially available from smart meters may be exploited to the advantage of both the distribution network operator and the customer. We are looking for the best overall outcome in terms of energy demand reduction, not the best 'engineering solution'. The driving forces towards the need for dynamic tariffs are strong: increased embedded generation, the introduction of plug-in electric vehicles, decreasing national generating capacity, further additions of medium and large scale variable generators, and the prospect of short-term load-shedding by suspending low priority consumption within commercial and domestic. This project aims to discover understanding of the whole interacting system. This project will take account of the smart metering and infrastructure options outlined in the recent Government consulation and response. Using High-Performance Computing to provide a scalable solution to large-scale data management for smart metering is especially timely as it addresses one of the main issues that was raised in the consultation. If, as a nation, we are to lower our overall energy demand, we will have to shift from fossil fuels to less carbon intensive supplies and optimise our energy consumption across all possible sources. This may mean that electricity demand may increase. At the same time, there is an imminent crisis in generating capacity (by whatever means), so we have to make significantly better use of the energy and the assets which make up the infrastructure. The meter is the interface between the consumer and the network operator, so in principle, a smart meter could manage and provide all of the information which describes the state of the network at that point at that time. Increasing data availability will bring benefits to both users and controllers - with detailed knowledge system behaviour in near-to-real-time at the lowest operational level, network operators have a better opportunity to balance the system load, and concurrently offer consumers much enhanced mechanisms for reducing their own power demand.
Key Findings
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Organisation Website: http://www.ox.ac.uk