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.

Potential Impact:
The proposed system has the potential to significantly lower residential electricity demand and improve power management in the distribution network, resulting in a more energy efficient and sustainable system. Network observability and stability can also be improved by forestalling peak demand though dynamic and time-of-use pricing. The end product from the consumer and supplier perspectives is an electricity supply system that: 1) offers opportunities to save both electricity and money, 2) is more flexible, and 3) is potentially more sustainable. High performance computing solutions to large-scale data problems are falling in cost and we expect will offer ubiquitous capabilities to assist with systems such as the supply of electricity, with benefits for both consumers and retailers.