Multiple Model Adaptive Estimation of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

[+] Author and Article Information
Alex J Tsai

United States Coast Guard Academy, New London CT, USA

David Tucker

US Department of Energy, National Energy Technology Laboratory, Morgantown WV, USA

Tooran Emami

United States Coast Guard Academy, New London CT, USA

1Corresponding author.

ASME doi:10.1115/1.4038634 History: Received May 11, 2017; Revised September 20, 2017


Operating points of a 300kW Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) power plant simulator is estimated with the use of a Multiple Model Adaptive Estimation (MMAE) algorithm, aimed at improving the flexibility of controlling the system to changing operating conditions. Through a set of empirical Transfer Functions derived at two distinct operating points of a wide operating envelope, the method demonstrates the efficacy of estimating online the probability that the system behaves according to a predetermined dynamic model. By identifying which model the plant is operating under, appropriate control strategies can be switched and implemented upon changes in critical parameters of the SOFC-GT system - most notably the Load Bank (LB) disturbance and FC cathode airflow parameters. The SOFC-GT simulator allows testing of various fuel cell models under a cyber-physical configuration that incorporates a 120kW Auxiliary Power Unit, and Balance-of-Plant components in hardware, and a fuel cell model in software. The adaptation technique is beneficial to plants having a wide range of operation, as is the case for SOFC-GT systems. The practical implementation of the adaptive methodology is presented through simulation in the MATLAB/SIMULINK environment.

Copyright (c) 2017 by ASME
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