DocumentCode :
49887
Title :
Mid-term electricity market clearing price forecasting using multiple least squares support vector machines
Author :
Xing Yan ; Chowdhury, Nurul A.
Author_Institution :
Dept. of Electr. Eng., Univ. of Saskatchewan, Saskatoon, SK, Canada
Volume :
8
Issue :
9
fYear :
2014
fDate :
Sept. 2014
Firstpage :
1572
Lastpage :
1582
Abstract :
Mid-term electricity market clearing price (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 MCP forecasting, but very little has been done in the area of mid-term electricity MCP forecasting. A multiple least squares support vector machine (LSSVM) based mid-term electricity MCP forecasting model is proposed in this study. Data classification and price forecasting modules are designed to first pre-process the input data into corresponding price zones, and then forecast the electricity price. The proposed model showed improved forecasting accuracy on both peak prices and overall system compared to the forecasting model using a single LSSVM. PJM interconnection data are used to test the proposed model.
Keywords :
least squares approximations; maintenance engineering; power engineering computing; power markets; support vector machines; LSSVM-based mid-term electricity MCP forecasting model; PJM interconnection data; bilateral contracting; budgeting purpose; data classification; maintenance scheduling; mid-term electricity market clearing price forecasting; multiple-least square support vector machines; planning purpose; price forecasting module; price zones; resource reallocation; short-term electricity MCP forecasting;
fLanguage :
English
Journal_Title :
Generation, Transmission & Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd.2013.0610
Filename :
6887472
Link To Document :
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