Distributed Model Predictive Consensus Control for Stable Operation of Integrated Energy System
Haichen Han, Huaguang Zhang, Jun Yang, Hanguang Su
Abstract
The stable operation of the integrated energy system (IES) is affected by the fluctuation of heat or electricity loads, energy or communication problems, and the interaction of different energy networks. To overcome above challenges, firstly, the integrated dynamic models with three-time scales are established for control design, fully considering dynamic behaviors, energy coupling, and constraints of power flow including electrical, heat and gas on network stability. Then, a novel distributed model predictive control (DMPC) consensus algorithm with process control and trajectory control is proposed to achieve stable operation for IES based on second-order cone programming (SOCP). A unified distributed cooperative control mode is formed in IES by implementing the proposed stability control method, which is suitable for different forms of energy. The control design takes into account the different dynamic characteristics of energy equipment and the energy coupling feature, which realizes the multi-scale time cooperation and dynamic process control for IES by tuning the control parameters. The optimal solution is obtained by rolling optimization for achieving frequency/voltage/temperature/pressure/flow regulation and consensus objectives. Finally, the proposed model and method are validated in various simulation scenarios, such as load variation, energy flow variation, nodes removed, and topology change.