Divide and Conquer? k-Means Clustering of Demand Data Allows Rapid and Accurate Simulations of the British Electricity System

Tools

Green, Richard, Staffell, Iain and Vasilakos, Nicholas ORCID: https://orcid.org/0000-0003-3279-2885 (2014) Divide and Conquer? k-Means Clustering of Demand Data Allows Rapid and Accurate Simulations of the British Electricity System. IEEE Transactions on Engineering Management, 61 (2). pp. 251-260. ISSN 0018-9391

Full text not available from this repository. (Request a copy)

Item Type:	Article
Uncontrolled Keywords:	pattern clustering,power generation dispatch,power system simulation,british electricity system,complex monte carlo simulations,data partitioning,dispatch model,intermittent wind generation,k-means clustering algorithm,national electricity demand data,profiling method,sensitivity analysis
Faculty \ School:	Faculty of Social Sciences > Norwich Business School University of East Anglia > Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research
Depositing User:	Pure Connector
Date Deposited:	25 Jul 2014 13:26
Last Modified:	24 Oct 2022 23:58
URI:	https://ueaeprints.uea.ac.uk/id/eprint/49413
DOI:	10.1109/TEM.2013.2284386

Actions (login required)

View Item