A Multi-Timescale Low Carbon Scheduling Optimization Method for Integrated Energy System Considering Source-load

In order to reduce the instability of integrated energy system caused by wind power, load prediction error, and low-carbon low-cost operation, a multi-time scale scheduling optimization method for is proposed. The fuzzy variables fitting loads under different time scales are obtained analyzing change error energy, user response law time-sharing price. To achieve deviation control at scales, minimize cost daily power purchases, gas discards carbon emissions. satisfy balance, active backup, purchase constraint storage capacity construct an optimized model system. Implementation low requirements systems. experimental results show that this can realize optimal dispatch electric, heat higher accuracy prediction, lower