The University of Southampton
University of Southampton Institutional Repository

Putting the "Smarts" into the Smart Grid: A Grand Challenge for Artificial Intelligence

Record type: Article

The phenomenal growth in material wealth experienced in developed countries throughout the twentieth century has largely been driven by the availability of cheap energy derived from fossil fuels (originally coal, then oil, and most recently natural gas). However, the continued availability of this cheap energy cannot be taken for granted given the growing concern that increasing demand for these fuels (and particularly, demand for oil) will outstrip our ability to produce them (so called 'peak oil'). Many mature oil and gas fields around the world have already peaked and their annual production is now steadily declining. Predictions of when world oil production will peak vary between 0-20 years into the future, but even the most conservative estimates provide little scope for complacency given the significant price increases that peak oil is likely to precipitate. Furthermore, many of the oil and gas reserves that do remain are in environmentally or politically sensitive regions of the world where threats to supply create increased price volatility (as evidenced by the 2010 Deepwater Horizon disaster and 2011 civil unrest in the Middle East). Finally, the growing consensus on the long term impact of carbon emissions from burning fossil fuels suggests that even if peak oil is avoided, and energy security assured, a future based on fossil fuel use will expose regions of the world to damaging climate change that will make the lives of many of the world's poorest people even harder.

PDF ramchurn_etal_smart_grid.pdf - Accepted Manuscript
Download (151kB)
PDF appendix.pdf - Accepted Manuscript
Download (73kB)
PDF p86-ramchurn.pdf - Version of Record
Download (6MB)

Citation

Ramchurn, Sarvapali, Vytelingum, Perukrishnen, Rogers, Alex and Jennings, Nicholas R. (2012) Putting the "Smarts" into the Smart Grid: A Grand Challenge for Artificial Intelligence Communications of the ACM, 55, (4), pp. 86-97.

More information

Published date: 2012
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 272606
URI: http://eprints.soton.ac.uk/id/eprint/272606
PURE UUID: d06e8ff5-4354-465d-aa4a-d3496b237675
ORCID for Sarvapali Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

Catalogue record

Date deposited: 29 Jul 2011 15:25
Last modified: 18 Jul 2017 06:22

Export record

Contributors

Author: Sarvapali Ramchurn ORCID iD
Author: Perukrishnen Vytelingum
Author: Alex Rogers
Author: Nicholas R. Jennings

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×