Two-Stage Distributionally Robust Optimization Model of Integrated Energy System Considering Flexible Resources

Due to the intermittent and fluctuating properties of renewable energy, Integrated Energy Systems (IES) face great challenges in terms of secure, economic, and low-carbon operation. To improve the penetration rate of renewable energy and the flexibility of IES, a two-stage distributionally robust optimization model is proposed considering flexible resources. Firstly, a fuzzy set of the total error function is established based on the Wasserstein distance. Then a two-stage distributionally robust optimization model is established within the day-ahead and real-time scales. Finally, the flexible resource model is finely established and the flexibility constraints are considered based on the flexibility demand of IES. The simulation results show that the upward and downward flexibility of IES can be maximally increased by 8 342.3 kW and 8 428.6 kW by means of flexible resources, meanwhile the system economy has not significantly decreased.