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research-article

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
alex.j.tsai@gmail.com

David Tucker

US Department of Energy, National Energy Technology Laboratory, Morgantown WV, USA
david.tucker@netl.doe.gov

Tooran Emami

United States Coast Guard Academy, New London CT, USA
Tooran.Emami@uscga.edu

1Corresponding author.

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

Abstract

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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