Computational Modelling Group

SAVE: Solent Achieving Value through Efficiency

Homepage
http://www.energy.soton.ac.uk/tag/save/
Started
5th May 2014
Ending
28th June 2019
Research Team
Luke Blunden
Investigators
Patrick James, Ben Anderson

SAVE logo

Analysis of 15 minute electricity consumption and 10 second instantaneous power data from 4,000+ households in the Solent region collected over 3 years of a randomised control trial study.

Categories

Physical Systems and Engineering simulation: Data Acquisition, Energy

Socio-technological System simulation: Built Environment

Algorithms and computational methods: Multi-core

Visualisation and data handling methods: Data Aggregation, Data Management

Software Engineering Tools: Git, RStudio

Programming languages and libraries: R

Computational platforms: Iridis, Linux, Mac OS X

Transdisciplinary tags: Computational Social Science, Data Science, Demand Response, Visualisation