Currently, there are many techniques available for short-term forecasting of the electricity market clearing price (MCP), but very\nlittle work has been done in the area of midterm forecasting of the electricity MCP. The midterm forecasting of the electricity\nMCP is essential for maintenance scheduling, planning, bilateral contracting, resources reallocation, and budgeting. A two-stage\nmultiple support vector machine (SVM) based midterm for e casting model of the electricity MCP is proposed in this paper.The first\nstage is utilized to separate the input data into corresponding price zones by using a single SVM. Then, the second stage is applied\nutilizing four parallel designed SVMs to forecast the electricity price in four different price zones. Compared to the forecasting\nmodel using a single SVM, the proposed model showed improved forecasting accuracy in both peak prices and overall system.\nPJM interconnection data are used to test the proposed model.
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