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Midterm Electricity Market Clearing Price Forecasting Using Two-Stage Multiple Support Vector Machine
Joint Authors
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-01-29
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Currently, there are many techniques available for short-term forecasting of the electricity market clearing price (MCP), but very little work has been done in the area of midterm forecasting of the electricity MCP.
The midterm forecasting of the electricity MCP is essential for maintenance scheduling, planning, bilateral contracting, resources reallocation, and budgeting.
A two-stage multiple support vector machine (SVM) based midterm forecasting model of the electricity MCP is proposed in this paper.
The first stage is utilized to separate the input data into corresponding price zones by using a single SVM.
Then, the second stage is applied utilizing four parallel designed SVMs to forecast the electricity price in four different price zones.
Compared to the forecasting model using a single SVM, the proposed model showed improved forecasting accuracy in both peak prices and overall system.
PJM interconnection data are used to test the proposed model.
American Psychological Association (APA)
Yan, Xing& Chowdhury, Nurul A.. 2015. Midterm Electricity Market Clearing Price Forecasting Using Two-Stage Multiple Support Vector Machine. Journal of Energy،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1068167
Modern Language Association (MLA)
Yan, Xing& Chowdhury, Nurul A.. Midterm Electricity Market Clearing Price Forecasting Using Two-Stage Multiple Support Vector Machine. Journal of Energy No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1068167
American Medical Association (AMA)
Yan, Xing& Chowdhury, Nurul A.. Midterm Electricity Market Clearing Price Forecasting Using Two-Stage Multiple Support Vector Machine. Journal of Energy. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1068167
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1068167