DocumentCode :
1954498
Title :
Hybrid SVM & ARMAX based mid-term electricity market clearing price forecasting
Author :
Xing Yan ; Chowdhury, Nurul A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Saskatchewan, Saskatoon, SK, Canada
fYear :
2013
fDate :
21-23 Aug. 2013
Firstpage :
1
Lastpage :
5
Abstract :
A hybrid mid-term electricity MCP forecasting model combining both support vector machine (SVM) and autoregressive moving average with external input (ARMAX) modules is presented in this paper. Currently, there are many techniques available for short-term electricity market clearing price (MCP) forecasting, but very little has been done in the area of mid-term electricity MCP forecasting. Mid-term electricity MCP forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. The proposed hybrid model showed improved forecasting accuracy compared to a forecasting model using a single SVM. PJM interconnection data have been utilized to illustrate the proposed model with numerical examples.
Keywords :
autoregressive moving average processes; load forecasting; power engineering computing; power markets; pricing; resource allocation; support vector machines; ARMAX modules; PJM interconnection data; autoregressive moving average with external input modules; hybrid SVM-ARMAX based mid-term electricity market clearing price forecasting; hybrid mid-term electricity MCP forecasting model; resource reallocation; support vector machine; Data models; Electricity; Forecasting; Mathematical model; Predictive models; Support vector machines; Training; Auto-regressive moving average with external input (ARMAX); deregulated electric market; electricity market clearing price (MCP); electricity price forecasting; support vector machine (SVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Power & Energy Conference (EPEC), 2013 IEEE
Conference_Location :
Halifax, NS
Print_ISBN :
978-1-4799-0105-0
Type :
conf
DOI :
10.1109/EPEC.2013.6802978
Filename :
6802978
Link To Document :
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