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Robust optimal scheduling of integrated energy systems based on hybrid energy storage and multiple time scales

In order to solve the multiple uncertainties of wind, light and load forecasting, as well as the influence of the different transmission characteristics of heterogeneous energy flow in power grid, gas network and cold/hot network on the optimal scheduling of integrated energy system (IES). A multi-time-scale robust optimal scheduling strategy for IES based on hybrid energy storage is proposed to promote the local absorption of renewable energy through the formation of multiple absorption technology and multiple storage technology. The multi-time scale robust scheduling model of day-ahead, day rolling and real-time feedback is established with the optimal scheduling instruction cycle of multi-energy flow equipment to improve the scheduling accuracy. The column and constraint generation(C&CG) algorithm is used to solve the two-stage robust optimization. The result of the example shows that hybrid energy storage can improve the economy of IES; multi-time scale robust optimization and different scheduling instruction cycles of energy flow devices can effectively reduce the influence of uncertainty and different inertia characteristics of electric/gas/thermal on the actual operation of the system.