Hybrid Adaptive Fuzzy Neural Network Control for Grid-Connected SOFC System

摘要

The solid oxide fuel cell (SOFC) is widely acknowledged for clean distributed power generation use, but critical process problems frequently occur when the stand-alone fuel cell is directly linked with the electricity grid. To guarantee the optimal operation of the SOFC in a power system, it is essential, that its generation ramp rate and load following is fast enough to sustain power quality. In order to address these problems, a suitable and highly efficient control system will be required to control and track power load demands for complex SOFC power systems under grid connection. Therefore, novel nonlinear hybrid adaptive Fuzzy Neural Network (AFNN) is developed for control of grid connected SOFC. During peak power demand schedules from electric utility grid and large load perturbations, maintaining optimal power quality and load-following is a big challenge. Both the rapid power load following and safe SOFC operation requirement is taken into account in the design of the closed-loop control system. Simulation results showed that the proposed hybrid AFNN enhance the optimal power quality and load-following than conventional PI controller.