Research Papers

Temperature Control of a SOFC and MGT Hybrid System

[+] Author and Article Information
Xiao-Juan Wu1

Qi Huang, Chang-Hua Zhang

 School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China

Xin-Jian Zhu

 Institute of Fuel Cell, Shanghai Jiao Tong University, Shanghai 200030, China


Corresponding author.

J. Fuel Cell Sci. Technol 8(5), 051009 (Jun 17, 2011) (6 pages) doi:10.1115/1.4004174 History: Received May 19, 2010; Revised April 13, 2011; Published June 17, 2011; Online June 17, 2011

Transients in a load have a significant impact on the performance and durability of a solid oxide fuel cell (SOFC) integrated into a micro gas turbine (MGT) hybrid power system. One of the main reasons is that the SOFC operating temperature and turbine inlet temperature change drastically due to the load change. Therefore, in order to guarantee the temperature to operate within a specified range, an adaptive proportional-integral-derivative (PID) decoupling control strategy based on a dynamic radial basis function (RBF) neural network is presented to control the temperature of a natural gas fueled, tubular SOFC/MGT hybrid with internal reforming in this paper. Using the self-learning ability of the dynamic RBF neural network, the proportional, integral, and differential factor of the PID controller are tuned on-line. The simulation results show that it is feasible to build the adaptive PID decoupling controller for temperature control of the SOFC/MGT hybrid system.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

Temperature decoupling control structure of the SOFC/MGT hybrid system

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Figure 2

Response of temperature control system during +20% step change at load

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Figure 3

Response of temperature control system during −15% step change at load

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Figure 4

Response of temperature control system during step changes at load



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