Multiscale Modelling to maximise Demand Side Management (Part 2)
Lead Research Organisation:
University of Edinburgh
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
- University of Edinburgh (Lead Research Organisation)
- International Union for Electricity applications (Project Partner)
- Wilson Energy (United Kingdom) (Project Partner)
- E.ON E&P UK Ltd (Project Partner)
- Areva (Project Partner)
- Scottish and Southern Energy (United Kingdom) (Project Partner)
- Scottish Power (United Kingdom) (Project Partner)
- Alpiq (United Kingdom) (Project Partner)
Publications
Altmann Y
(2016)
Robust Bayesian target detection algorithm for depth imaging from sparse single-photon data
in IEEE Transactions on Computational Imaging
Collin A
(2014)
Development of Low-Voltage Load Models for the Residential Load Sector
in IEEE Transactions on Power Systems
Collin A
(2012)
Multi-scale electrical load modelling for demand-side management
Stephen McLaughlin (Author)
(2011)
Multi-scale Dynamic Modeling to Maximize Demand Side Management
Tsagarakis G
(2013)
Voltage control of UK residential customers for power reduction
| Description | There has been considerable interest in developing demand side management for domestic suppliers, put simply, enable power suppliers to determine when you might switch on and off your domestic appliances to ensure that the smart grid can deliver energy more efficiently. Our work analysed exactly how you might determine the benefits in an objective manner by determining the improvements in electrical power that might accrue. |
| Exploitation Route | These have been taken forward in a subsequent EU grant exploring the use of smart grid technologies |
| Sectors | Energy |