A Dispatching Method for Integrated Energy System Based on Dynamic Time-interval of Model Predictive Control

In integrated energy systems (IESs), traditional fixed time-interval dispatching scheme is unable to adapt to the need of dynamic properties of the transient network, demand response characteristics, dispatching time scales in energy subsystems and renewable power uncertainties. This scheme may easily result in uneconomic source-grid-load-storage operations in IES. In this paper, we propose a dispatching method for IES based on dynamic time-interval of model predictive control (MPC). We firstly build models for energy sub-systems and multi-energy loads in the power-gas-heat IES. Then, we develop an innovative optimization method leveraging trajectory deviation control, energy control, and cost control frameworks in MPC to handle the requirements and constraints over the time-interval of dispatching. Finally, a dynamic programming algorithm is introduced to efficiently solve the proposed method. Experiments and simulation results prove the effectiveness of the method.