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