Projects
Projects: Projects for Investigator |
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| Reference Number | EP/I000119/1 | |
| Title | Advanced Dynamic Energy Pricing and Tariffs (ADEPT) | |
| Status | Completed | |
| Energy Categories | Energy Efficiency(Residential and commercial) 30%; Other Power and Storage Technologies(Electricity transmission and distribution) 35%; Other Cross-Cutting Technologies or Research(Environmental, social and economic impacts) 35%; |
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| Research Types | Basic and strategic applied research 100% | |
| Science and Technology Fields | SOCIAL SCIENCES (Economics and Econometrics) 10%; SOCIAL SCIENCES (Sociology) 10%; PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 40%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 40%; |
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| UKERC Cross Cutting Characterisation | Sociological economical and environmental impact of energy (Consumer attitudes and behaviour) 25%; Sociological economical and environmental impact of energy (Technology acceptance) 25%; Sociological economical and environmental impact of energy (Other sociological economical and environmental impact of energy) 25%; Other (Energy technology information dissemination) 25%; |
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| Principal Investigator |
Dr G Taylor No email address given Electronic & Computer Engineering Brunel University |
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| Award Type | Standard | |
| Funding Source | EPSRC | |
| Start Date | 01 October 2010 | |
| End Date | 30 September 2013 | |
| Duration | 36 months | |
| Total Grant Value | £303,898 | |
| Industrial Sectors | No relevance to Underpinning Sectors; Manufacturing; Transport Systems and Vehicles | |
| Region | London | |
| Programme | Digital Economy, Energy Multidisciplinary Applications | |
| Investigators | Principal Investigator | Dr G Taylor , Electronic & Computer Engineering, Brunel University (99.999%) |
| Other Investigator | Professor PR Hobson , Sch of Engineering and Design, Brunel University (0.001%) |
|
| Web Site | ||
| Objectives | Note : This grant is linked to grant EP/I000194/1 | |
| Abstract | 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 additionsof 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 isespecially 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 andthe 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 balancethe system load, and concurrently offer consumers much enhanced mechanisms for reducing their own power demand | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 08/06/10 | |
