Neural networks-based control of active and reactive power of a stand-alone PEM fuel cell power plant

This paper presents a neural networks (NN)-based active and reactive power controller of a stand-alone proton exchange membrane (PEM) fuel cell power plant (FCPP). The controller modifies the inverter modulation index and the phase angle of the ac output voltage to control the active and reactive power output from an FCPP to match the terminal load. The control actions are based on feedback signals from the terminal load, output voltage and hydrogen input. The validity of the controller is verified when the FCPP model is used in conjunction with the NN controller to predict the response of the power plant to: (a) computer-simulated step changes in the load active and reactive power demand, and (b) actual active and reactive load demand of a single family residence. The response curves indicate the load following characteristics of the model and the predicted changes in the analytical parameters highlighted by the analysis. (C) 2004 Elsevier B.V. All rights reserved.