A Pivotal Supplier Identification Approach Considering Unit Ramp Rate in Day-ahead Electricity Market

With wind power, solar energy and other large-scale intermittent renewable energy integrating to the grid, the demand for the ramp rate will be significantly increased in day-ahead electricity market. The power producers may use their ramp rate to become the pivotal supplier and exercise their market power. Therefore, it is necessary to quantitatively analyze the influence that the ramp rate of units may have on their possibility to become the pivotal suppliers. In this paper, a multi-period ex-ante pivotal supplier identification model with considering the unit ramp rate constraints is proposed to quantify the ex-ante market power. The objective function is to minimize the sum of the output slack variables for each period. The constraints include unit output constraints, transmission constraints and unit ramp rate constraints. Considering that the slack variables of different periods may affect with each other, a progressive optimization strategy is proposed to accurately locate the periods that pivotal suppliers emerge. Meanwhile, the multi-scenario analysis is used to deal with the uncertainty of the net load forecasting. The proposed model is a linear programming problem which is implemented on the GAMS platform and solved by the CPLEX solver efficiently. Finally, the effectiveness of the method proposed in this paper is verified through the case study which is based on the modified IEEE14-node system.