Optimal Energy Management Design Using Bi-Level Model Predictive Control for Multiple Time Scales

Multi-energy systems are increasingly studied in the energy sector to reduce economic costs and environmental impacts. This research studies an Integrated Energy System (IES) coupling multiple energy sources, including electricity, heat, and gas. An energy management strategy is essential to efficiently schedule the energy sources to meet all subsystem operational requirements, and optimize the economic costs and energy efficiency of the IES. A bi-level Model Predictive Control (MPC) strategy is consequently proposed. The upper-layer MPC considers the long-term optimization of electric, heating and gas energies considering the slow dynamics of the energy sources. In contrast, the lower-layer MPC responds to the quick dynamics of the sub-electrical power system, and simultaneously considers the updated limitations based on the upper-layer MPC decisions. Therefore, the proposed control strategy can meet all dynamic adjustment requirements. A case study is provided for a regional IES to verify the proposed method. The results show that, by adopting the proposed bi-level MPC, the energy resources are scheduled and respond to the dynamics of each subsystem, achieving optimal economic operation of the whole system and efficient energy utilisation.