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 :
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