Energy Control Strategy for Fuel Cell Hybrid Power System Based on Adaptive Parametric Virtual DC Machine

An adaptive parametric virtual dc machine (VdcM)-based energy control strategy for fuel cell hybrid power systems is proposed in this article. Compared with the conventional main–secondary and droop control strategies, the VdcM control strategy introduces virtual inertia, virtual damping, and virtual armature impedance by constructing the dc generator’s equations between the dc–dc converter’s common voltage loop and current loop to improve the stability and reliability of the hybrid system. To reduce the system operating cost, an online energy management strategy (EMS) combining auto-regressive integrated moving average (ARIMA) time series prediction and local dynamic programming (LDP) is developed, and applied to the virtual armature resistance adaptive control of the VdcM to realize the economical allocation of power between each energy source and load. To further suppress the fluctuation of bus voltage, a nonlinear adaptive control strategy of virtual inertia for VdcM is proposed. Simulation and experimental results show that the proposed strategy can dynamically adjust the parameters of the VdcM according to the real-time load power, battery state-of-charge (SOC) and bus voltage. It can realize the online optimal allocation of fuel cell and battery power, suppress the bus voltage fluctuations and reduce the bus voltage recovery time by 41% during load variations. It can also effectively improve the power supply quality, and extend the fuel cell’s service life by reducing 53% the operating stress.