This article was published online on [10 October 2011]. Errors were subsequently identified. This notice is included in the online and print versions to indicate that both have been corrected [21 January 2013].
Optimization of a solid oxide fuel cell and micro gas turbine hybrid system†
Article first published online: 10 OCT 2011
Copyright © 2011 John Wiley & Sons, Ltd.
International Journal of Energy Research
Volume 37, Issue 3, pages 242–249, 10 March 2013
How to Cite
Wu, X.-J. and Zhu, X.-J. (2013), Optimization of a solid oxide fuel cell and micro gas turbine hybrid system. Int. J. Energy Res., 37: 242–249. doi: 10.1002/er.1899
- Issue published online: 11 FEB 2013
- Article first published online: 10 OCT 2011
- Manuscript Accepted: 26 JUN 2011
- Manuscript Revised: 8 JUN 2011
- Manuscript Received: 31 JAN 2011
- solid oxide fuel cell (SOFC);
- micro gas turbine (MGT);
- iterative method;
- particle swarm optimization (PSO)
For a solid oxide fuel cell (SOFC) and micro gas turbine (MGT) hybrid system, optimal control of load changes requires optimal dynamic scheduling of set points for the system's controllers. Thus, this paper proposes an improved iterative particle swarm optimization (PSO) algorithm to optimize the operating parameters under various loads. This method combines the iteration method and the PSO algorithm together, which can execute the discrete PSO iteratively until the control profile would converge to an optimal one. In MATLAB environment, the simulation results show that the SOFC/MGT hybrid model with the optimized parameters can effectively track the output power with high efficiency. Hence, the improved iterative PSO algorithm can be helpful for system analysis, optimization design, and real-time control of the SOFC/MGT hybrid system. Copyright © 2011 John Wiley & Sons, Ltd.