Robust Optimal Scheduling of EHG-IES Based on Uncertainty of Wind Power and PV Output

The Electricity-Heat-Gas Integrated Energy System (EHG-IES) is important for achieving carbon neutrality. However, the uncertainty of wind power and photovoltaic (PV) output has a large impact on EHG-IES scheduling optimization. In order to solve this problem, a robust scheduling optimization method considering the uncertainty of wind power and PV output and the coupling relationship of each device in EHG-IES is proposed. In the proposed optimization method, the uncertainty of wind power and PV output is described by an additive maximum uncertainty set. Then, the day-ahead scheduling optimization model is proposed based on the coupling relationship of each equipment and electric vehicle (EV) traveling demand. Also, the proposed model is introduced in detail. The simulation is verified by a park calculation example. The economy and accuracy of the proposed method in this paper are verified by comparing the robust optimization results under different uncertainties with stochastic optimization. For robust parameters of 20% and 10%, the economic cost is 1.016% and 1.041% lower than that of the stochastic optimization. Meanwhile, the proposed method can improve the economy of the EHG-IES and realize the economic and safe operation of the EHG-IES under the consideration of EVs and heating storage equipment.