Multi-time-scale scheduling optimization of regional multi-energy systems considering source-load uncertainty

In the regional multi-energy system (regional multi-energy system, RMES), the uncertainty of source and load changes with the time scale. Traditional scheduling methods cannot achieve optimal scheduling optimization among multi-energy networks. In response to this problem, this paper firstly establishes the basic structure of a regional multi-energy system based on energy hub (EH) and expresses the uncertainty of source load prediction under multiple time scales; secondly, according to the scheduling characteristics and equipment control characteristics of each energy network in RMES, consider Uncertainty, the RMES multi-time-scale scheduling method is proposed; then, according to this method, with the lowest scheduling cost as the optimization goal, the RMES multi-time-scale scheduling optimization model is constructed; finally, the simulation example proves that the optimization model can effectively reduce the RMES Cost of scheduling.