Robust Co-Optimization to Energy and Ancillary Service Joint Dispatch Considering Wind Power Uncertainties in Real-Time Electricity Markets

Abstract

This paper presents an adjustable robust co-optimization model for energy and ancillary service markets joint dispatch considering wind power uncertainties in real-time electricity markets. The participation factors are employed to generate adjustable generation outputs and ensure energy balance. The proposed robust optimization model can be equivalently transformed into a large-scale linear programming model with a huge number of dummy variables and additional constraints that challenge real-time markets. To further reduce the computation burden, the redundant constraint reduction strategy is proposed to fast eliminate redundant transmission security constraints before solving the model. The results from the IEEE 30-bus system with two wind farms show that the proposed robust joint optimization model provides a better solution compared to those cases using sequential dispatch or deterministic dispatch methodologies. Additional results from practical large-scale systems suggest that the number of redundant constraints is less than 6%, indicating the effectiveness of the proposed redundant constraint reduction strategy in improving the computation efficiency of the robust joint dispatch in real-time markets.