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

Richard Green; Iain Staffell; Nicholas Vasilakos

doi:10.1109/TEM.2013.2284386

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

Richard Green, Iain Staffell, Nicholas Vasilakos

Research output: Contribution to journal › Article › peer-review

89 Citations (Scopus)

Original language	English
Pages (from-to)	251-260
Number of pages	10
Journal	IEEE Transactions on Engineering Management
Volume	61
Issue number	2
Early online date	30 Jan 2014
DOIs	https://doi.org/10.1109/TEM.2013.2284386
Publication status	Published - 1 May 2014

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

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10.1109/TEM.2013.2284386

Nicholas Vasilakos
- N.Vasilakosuea.acuk
- Norwich Business School - Associate Professor in Sustainable Business Economics and Public Policy
- Centre for Competition Policy - Member
- Tyndall Centre for Climate Change Research - Member
- Responsible Business Regulation Group - Member
Person: Research Group Member, Research Centre Member, Academic, Teaching & Research

Cite this

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

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",

author = "Richard Green and Iain Staffell and Nicholas Vasilakos",

year = "2014",

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T1 - Divide and Conquer? k-Means Clustering of Demand Data Allows Rapid and Accurate Simulations of the British Electricity System

AU - Green, Richard

AU - Staffell, Iain

AU - Vasilakos, Nicholas

PY - 2014/5/1

Y1 - 2014/5/1

KW - pattern clustering

KW - power generation dispatch

KW - power system simulation

KW - British electricity system

KW - complex Monte Carlo simulations

KW - data partitioning

KW - dispatch model

KW - intermittent wind generation

KW - k-means clustering algorithm

KW - national electricity demand data

KW - profiling method

KW - sensitivity analysis

U2 - 10.1109/TEM.2013.2284386

DO - 10.1109/TEM.2013.2284386

M3 - Article

VL - 61

SP - 251

EP - 260

JO - IEEE Transactions on Engineering Management

JF - IEEE Transactions on Engineering Management

SN - 0018-9391

IS - 2

ER -

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

Keywords

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Nicholas Vasilakos

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