DocumentCode :
624404
Title :
A comparison between SVM and LSSVM in mid-term electricity market clearing price forecasting
Author :
Xing Yan ; Chowdhury, Nurul A.
Author_Institution :
Univ. of Saskatchewan, Saskatoon, SK, Canada
fYear :
2013
fDate :
5-8 May 2013
Firstpage :
1
Lastpage :
4
Abstract :
The generating companies as well as the bulk sellers in a deregulated environment want to maximize their profits. For these entities, offering the appropriate amount of electricity at the right time with the right bidding price is of paramount importance. A comparison between support vector machine (SVM) and least squares support vector machine (LSSVM) in mid-term electricity MCP forecasting is presented in this paper. Mid-term electricity MCP forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. 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. PJM interconnection data have been utilized to illustrate the proposed model with numerical examples.
Keywords :
budgeting; contracts; electrical maintenance; least squares approximations; load forecasting; power markets; pricing; profitability; resource allocation; support vector machines; LSSVM; PJM interconnection data; bidding price; bilateral contracting; bulk sellers; generating companies; least squares support vector machine; maintenance scheduling; mid-term electricity MCP forecasting; mid-term electricity market clearing price forecasting; profit maximization; resource reallocation; Data models; Electricity; Electricity supply industry; Forecasting; Predictive models; Support vector machines; Training; Deregulated electric market; PJM; electricity market clearing price (MCP); least squares support vector machine (LSSVM); mid-term electricity MCP forecasting; support vector machine (SVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2013 26th Annual IEEE Canadian Conference on
Conference_Location :
Regina, SK
ISSN :
0840-7789
Print_ISBN :
978-1-4799-0031-2
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2013.6567685
Filename :
6567685
Link To Document :
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