Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6860642 | International Journal of Electrical Power & Energy Systems | 2013 | 7 Pages |
Abstract
A hybrid mid-term electricity market clearing price (MCP) forecasting model combining both least squares support vector machine (LSSVM) and auto-regressive moving average with external input (ARMAX) modules 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. The proposed hybrid model showed improved forecasting accuracy compared to a forecasting model using a single LSSVM.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Xing Yan, Nurul A. Chowdhury,