Intra-day Multi-time-scale Hierarchical Rolling Scheduling of Integrated Energy System Considering Uncertainty

Abstract

The uncertainty of wind power and demand brings challenges to the secure and economic operation of integrated energy system (IES). In order to effectively deal with the uncertainty, this paper proposes an intra-day multi-time-scale hierarchical rolling scheduling strategy based on model predictive control for IES. First, the mathematical model of the IES is constructed. Then, source-demand uncertainty model is established through fuzzy chance constraints. Finally, according to the response characteristics of heat, gas and electricity, intra-day multi-time-scale hierarchical optimization strategy of integrated energy system is proposed to handle prediction errors layer by layer. The simulation results show that the proposed scheduling model takes into account risks and costs by reasonably selecting confidence level, and smooths fluctuations of different systems by using multi-time-scale.