Abstract
In this paper, short-term electricity price forecasting considering residual electricity demand is investigated. Residual, or net, demand is determined by subtracting any unpredictable generation from the system load. Focusing on wind energy as the main hard-to-predict source of electricity, we first examine the dependency of short-term electricity prices and wind power using data association mining algorithms. Second, we investigate the impact of including net demand in short-term electricity price forecasting, and we propose a new electricity price forecasting model. Data from the Alberta and the Nordic electricity markets are used to conduct studies and evaluate the forecasting results.
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