An enhanced contingency-based model for joint energy and reserve markets operation by considering wind and energy storage systems

This paper presents a contingency-based stochastic security-constrained unit commitment to address the integration of wind power producers to the joint energy and reserve markets. The contingency ranking is a popular method for reducing the computation burden of the unit commitment problem, but performing the contingency analysis changes the high-impact events in previous ranking methods. This paper employs an intelligent contingency ranking technique to address the above issue and to find the actual top-ranked outages based on the final solution. Also, energy storage systems are considered to evaluate the impact of the scheduling of storage under uncertainties. Numerical results on a six-bus and the IEEE 118-bus test systems show the effectiveness of the proposed approach. Furthermore, it shows that utilizing both wind farms and storage devices will reduce the total operational cost of the system, while the intelligent contingency ranking analysis and enough reserves ensure the security of power supply.