Multi-time Scale Optimal Scheduling of Regional Integrated Energy System Considering Demand Response and Carbon Trading

Due to the source and load uncertainties of the regional integrated energy system(RIES), the real operating state may deviate from the expected state, which makes the system unable to achieve the expected control effect. In order to reduce the influence of the source and load uncertainties and control the total carbon emissions, this paper proposed a multi-time scale optimal scheduling model of the RIES considering demand response and carbon trading. First, an objective function with carbon emission cost was established in the day-ahead stage, and a robust optimization method was adopted to cope with the low-frequency component of the source and load uncertainties, which can maintain the safe and stable operation of the system even in the case of large-scale fluctuations. In addition, the model predictive control is used to track and correct the day-ahead scheduling plan in the intraday stage, which is able to cope with the high-frequency component of the source and load uncertainties. Finally, simulation results demonstrated the feasibility and effectiveness of the proposed method.