Optimal Dispatch for Flexible Uncertainty Sets in Multi-Energy Systems: An IGDT Based Two-Stage Decision Framework

The operational stability and economy of multi-energy systems (MES) are threatened by various uncertainties, such as variable renewable energy power, energy demands, and weather conditions. Most of the existing methods for the dispatch decisions of MES are based on the prescribed probability distribution or uncertainty sets of random variables, which have many disadvantages, such as potential infeasibility and over-conservatism. In this paper, we propose a novel dispatch model for MES that integrates dispatch decision making, uncertainty set selection, and operational cost control into a unified framework. First, the deterministic dispatch model of MES is introduced, in which the physical characteristics of district heating systems and buildings are fully considered. Then, a novel decision framework that combines the two-stage dispatch strategy and info-gap decision theory (IGDT) is proposed for MES, where the uncertainty set is flexible and can be optimized based on the operational cost budget. Finally, a revised algorithm, based on the column-and-constraint generation method, is proposed for the model. Case studies are performed on MES that includes a 33-bus distribution system and a heating network modified from a real 51-node network located in Jinlin Province, China. The results verify the effectiveness of the proposed method.