Day-Ahead Market Model Under Uncertainty Environment: A Probabilistic Constrained Programming Approach

The increasingly penetration of renewable generation resources has brought intermittence and uncertainty to the operation of electric power market. Those stochastic characteristics of renewable generation could potentially jeopardize security operation of power system, if not addressed properly. Therefore, it is desired to have day-ahead market model could handle those uncertainties during the generation scheduling process. Correspondingly, a dynamic probabilistic constraint based day-ahead resource scheduling model is proposed to minimize the economic costs including operation cost and carbon emission cost. The numerical study results illustrate the effectiveness of the proposed model.