Research Papers: Gas Turbines: Cycle Innovations

Improved Controller Performance of Selected Hybrid SOFC-GT Plant Signals Based on Practical Control Schemes

[+] Author and Article Information
Alex Tsai

 National Energy Technology Laboratory, 3610 Collins Ferry Road, Morgantown, WV 26505alex.tsai@netl.doe.gov

David Tucker

 National Energy Technology Laboratory, 3610 Collins Ferry Road, Morgantown, WV 26505david.tucker@netl.doe.gov

Craig Groves

 Georgia Institute of Technology, Administration Building, 225 North Avenue, Atlanta, GA 30332cgroves3@gatech.edu

J. Eng. Gas Turbines Power 133(7), 071702 (Mar 16, 2011) (11 pages) doi:10.1115/1.4002253 History: Received April 19, 2010; Revised April 30, 2010; Published March 16, 2011; Online March 16, 2011

This paper compares and demonstrates the efficacy of implementing two practical single input single output multiloop control schemes on the dynamic performance of selected signals of a solid oxide fuel cell gas turbine (SOFC-GT) hybrid simulation facility. The hybrid plant located at the U.S. Department of Energy National Energy Technology Laboratory in Morgantown, WV is capable of simulating the interaction between a 350 kW solid oxide fuel cell and a 120 kW gas turbine using a hardware in the loop configuration. Previous studies have shown that the thermal management of coal based SOFC-GT hybrid systems is accomplished by the careful control of the cathode air stream within the fuel cell (FC). Decoupled centralized and dynamic decentralized control schemes are tested for one critical airflow bypass loop to regulate cathode FC airflow and modulation of turbine electric load to maintain synchronous turbine speed during system transients. Improvements to the studied multivariate architectures include: feed-forward control for disturbance rejection, antiwindup compensation for actuator saturation, gain scheduling for adaptive operation, bumpless transfer for manual to auto switching, and adequate filter design for the inclusion of derivative action. Controller gain tuning is accomplished by Skogestad’s internal model control tuning rules derived from empirical first order plus delay time transfer function models of the hybrid facility. Avoidance of strong input-output coupling interactions is achieved via relative gain array, Niederlinski index, and decomposed relative interaction analysis, following recent methodologies in proportional integral derivative control theory for multivariable processes.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

Open loop step inputs: CA, LB, and FV actuators. Note: CA, LB noisy signals correspond to the speed axis. FV noisy signal corresponds to the FC airflow axis.

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Figure 2

Diagram of the HyPer facility real-time fuel cell model

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Figure 3

Open loop step inputs: CA, LB, and FV actuators

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Figure 4

Decoupled noninteracting control network (13)

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Figure 5

Simplified decoupled control loop (14)

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Figure 6

Decentralized dynamic relative interaction scheme (5)

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Figure 7

Antiwindup back-calculation scheme

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Figure 8

Case I: decentralized control: PID SIMC tuning. Note: Noisy signal on the actuator response plot corresponds to the load bank axis.

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Figure 9

Case II: decentralized control: DRIA tuning

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Figure 10

Case III: DRI with feed-forward compensation. Blue: without FF and black: with FF.

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Figure 11

Case IV: DRI with AW compensation

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Figure 12

Case V: decoupled control: PID SIMC tuning

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Figure 13

Case VI: decoupled with FF

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Figure 14

Decentralized LB/CA scheme

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Figure 15

Centralized decoupled scheme

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Figure 16

PID controller with AW and FF compensation: FV disturbance on ṁ




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