DocumentCode :
2656678
Title :
Grey Prediction Model and Multivariate Statistical Techniques Forecasting Electrical Energy Consumption in Wenzhou, China
Author :
Wang, Qi
Author_Institution :
Sch. of Life & Environ. Sci., Wenzhou Univ., Wenzhou
fYear :
2009
fDate :
23-25 Jan. 2009
Firstpage :
167
Lastpage :
170
Abstract :
Electricity consumption has always been one of the critical economic issues in Wenzhou. This paper presents a combination method of grey prediction models and multivariate statistical techniques to forecast the trend of electrical energy consumption in Wenzhou. Hierarchical cluster analysis and discriminant analysis grouped 18 sampling years into three clusters, i.e., relatively less electrical energy consumption phase (LEECP), medium electrical energy consumption phase (MEECP) and highly electrical energy consumption phase (HEECP). The two grey prediction models established are the first-degree. Mean absolute percentage error (MAPE) criteria are more suitable than traditional accuracy and error test to evaluate grey models accuracy. Grey prediction model has been tested with high precision in a short-term. Using the grey prediction model, electrical energy consumption of Wenzhou will be 44.4719 billion kilowatt hour in 2010.
Keywords :
load forecasting; statistical analysis; critical economic issues; electrical energy consumption forecasting; grey prediction model; hierarchical cluster analysis; highly electrical energy consumption phase; less electrical energy consumption phase; mean absolute percentage error; medium electrical energy consumption phase; multivariate statistical techniques; Economic forecasting; Energy consumption; Informatics; Information security; Information technology; Load forecasting; Performance analysis; Predictive models; Response surface methodology; Testing; Electrical energy consumption forecasting; Grey prediction model; Multivariate statistical techniques; Wenzhou;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology and Security Informatics, 2009. IITSI '09. Second International Symposium on
Conference_Location :
Moscow
Print_ISBN :
978-1-4244-3580-7
Type :
conf
DOI :
10.1109/IITSI.2009.43
Filename :
4777572
Link To Document :
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