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.
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ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology collocated with the ASME 2016 Power Conference and the ASME 2016 10th International Conference on Energy Sustainability
June 26–30, 2016
Charlotte, North Carolina, USA
Conference Sponsors:
- Advanced Energy Systems Division
ISBN:
978-0-7918-5024-4
PROCEEDINGS PAPER
Multiple Model Adaptive Estimation of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator Available to Purchase
Alex Tsai,
Alex Tsai
United States Coast Guard Academy, New London, CT
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David Tucker,
David Tucker
National Energy Technology Laboratory, Morgantown, WV
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Tooran Emami
Tooran Emami
United States Coast Guard Academy, New London, CT
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Alex Tsai
United States Coast Guard Academy, New London, CT
David Tucker
National Energy Technology Laboratory, Morgantown, WV
Tooran Emami
United States Coast Guard Academy, New London, CT
Paper No:
FUELCELL2016-59656, V001T03A004; 10 pages
Published Online:
November 1, 2016
Citation
Tsai, A, Tucker, D, & Emami, T. "Multiple Model Adaptive Estimation of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator." Proceedings of the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology collocated with the ASME 2016 Power Conference and the ASME 2016 10th International Conference on Energy Sustainability. ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology. Charlotte, North Carolina, USA. June 26–30, 2016. V001T03A004. ASME. https://doi.org/10.1115/FUELCELL2016-59656
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