Day-ahead Optimal Dispatch of an Integrated Energy System Considering Multiple Uncertainty

The uncertainties of renewable energy output and load have posed a challenge to the integrated energy system (IES) optimization dispatch. An economic dispatch model of the IES is constructed, which consists of the renewable energy, the utility grid, the thermal and electrical load, and the relevant equipment including the combined heat and power (CHP) units, the electricity storage systems, the thermal storage systems and the gas boilers. Considering the multiple uncertainties of renewable energy generation and load forecasting errors in the system, an optimal dispatch strategy based on the interval linear stochastic chance constrained programming is proposed. In this programming, the uncertainty of renewable energy power generation prediction is described with the probability distribution function, and the uncertainty of load prediction with the interval number. Thus, an interval linear stochastic chance constrained programming model, solved with the Gurobi solver, is constructed. The proposed model is compared with a single interval linear programming and stochastic chance constrained programming model in a thermoelectric integrated system. The results show that the proposed method has a lower average operating cost and a lower dependence on prediction accuracy. It can improve the economics of integrated energy system operation while ensuring the safe operation of the system. © 2020, Power System Technology Press. All right reserved.