DocumentCode
685317
Title
Regional electricity load profile subclasses for distribution network planning
Author
Booysen, J. ; Dekenah, Marcus
Author_Institution
Enerweb-Demand Intell. Group, Johannesburg, South Africa
fYear
2013
fDate
20-21 Aug. 2013
Firstpage
1
Lastpage
8
Abstract
Distribution electricity network planning needs consolidated regional and national views of predicted future loads. A power utility established load forecasting tool requires load profile data that will be used in calculating coincidence factors between loads of different classes and sub-classes as per economic activity and geospatial location. Regional industrial and commercial electricity load profile subclass models were developed for planning using clustering, geospatial significance testing and a BIC (Bayesian information criterion) technique to trade-off regional subclass complexity with overall profile model accuracy.
Keywords
Bayes methods; load forecasting; power distribution planning; BIC; Bayesian information criterion technique; clustering; commercial electricity load profile subclass models; distribution electricity network planning; geospatial location; geospatial significance testing; load forecasting tool; power utility; regional electricity load profile subclass model; Animals; Biological system modeling; Complexity theory; Economics; Electricity; Shape; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial and Commercial Use of Energy Conference (ICUE), 2013 Proceedings of the 10th
Conference_Location
Cape Town
ISSN
2166-0581
Print_ISBN
978-0-9922041-3-6
Type
conf
Filename
6761637
Link To Document