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Received December 11, 2016
Accepted April 22, 2017
- This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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A comparative study of models for molten carbonate fuel cell (MCFC) processes
Department of Chemical Engineering, Hanyang University, Seoul 04763, Korea
Korean Journal of Chemical Engineering, July 2017, 34(7), 1952-1960(9), 10.1007/s11814-017-0117-y
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Abstract
The necessity of this work arose from the need for identification of a comprehensive plant model that can be used in the model-based control of the MCFC plant. Various models for molten carbonate fuel cell (MCFC) processes are presented and evaluated in this paper. Both a rigorous model based on mass and energy balances and implicit models based on operation data were investigated and analyzed. In particular, auto regressive moving average (ARMA) model, least-squares support vector machine (LSSVM) model, artificial neural network (ANN) model and partial least squares (PLS) model for a MCFC system were developed based on input output operating data. Among these models, the ARMA model showed the best agreement with plant operation data.
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References
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