Abstract
This paper proposes a stochastic model for optimal bidding of wind power in a day-ahead electricity market. The uncertainties due to wind power generation and market prices are characterized by first carrying out the point forecasts through advanced statistical methods and then, the probable scenarios are generated using Kernal density estimation. The effectiveness of the proposed approach is tested on wind power producers in the area DK2 of Nord pool electricity market. Two year (2011 and 2012) market prices are considered for analysis. The test results are compared with respect to the revenues generated by point forecast, stochastic optimization and perfect prediction based bidding methods.
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