Multiscale Modelling to maximise Demand Side Management (Part 2)
Lead Research Organisation:
Heriot-Watt University
Department Name: Sch of Engineering and Physical Science
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
People |
ORCID iD |
| Stephen McLaughlin (Principal Investigator) |
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
(2012)
Multi-scale electrical load modelling for demand-side management
Collin A
(2014)
Development of Low-Voltage Load Models for the Residential Load Sector
in IEEE Transactions on Power Systems
Kiprakis A
(2011)
Multi-scale dynamic modeling to maximize demand side management
Stephen McLaughlin (Author)
(2011)
Multi-scale Dynamic Modeling to Maximize Demand Side Management
Tsagarakis G
(2012)
Modelling the electrical loads of UK residential energy users
Tsagarakis G
(2016)
Assessment of the Cost and Environmental Impact of Residential Demand-Side Management
in IEEE Transactions on Industry Applications
Tsagarakis G
(2013)
A Statistical Survey of the UK Residential Sector Electrical Loads
in International Journal of Emerging Electric Power Systems
| 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 |