Hierarchical Energy Management Based on Distributed Aggregation for Large-Scale Fuel Cell Cluster Hybrid Power Systems

Traditional centralized energy management strategies (EMSs) increase the burden of communication and computation for large-scale fuel cell cluster hybrid power systems (FCCHPSs), potentially causing the “curse of dimensionality” in optimization problems of energy management. This article proposes a hierarchical EMS based on distributed aggregation for large-scale FCCHPSs, aiming to reduce the burden of communication and computation while enhancing EMS flexibility and scalability. First, the distributed aggregation of fuel cell cluster systems (FCCSs) is modeled using distributed algorithms, enabling the FCCS to function as an aggregated system that presents its output characteristics. Second, the FCCS is treated as a holistic system to participate in the optimal energy management solution for obtaining the total reference power. Then, a distributed assignment model for FCCSs is established to allocate the total reference power optimized by energy management solver, with fuel cell power optimization control achieved through the proposed power ramp rate control. Finally, a MW-scale FCCHPS is built on the hardware-in-the-loop test platform, verifying the effectiveness and superiority of the proposed scheme through experimental results. The results demonstrate that the proposed scheme has excellent performance in estimating FCCS characteristic parameters and significantly reduces the computation time for EMS optimization of FCCHPS.