GRNN Application in Power Systems Simulation for Integrated SOFC Plant Dynamic Model
Commenced in January 2007
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GRNN Application in Power Systems Simulation for Integrated SOFC Plant Dynamic Model

Authors: N. Nim-on, A. Oonsivilai

Abstract:

In this paper, the application of GRNN in modeling of SOFC fuel cells were studied. The parameters are of interested as voltage and power value and the current changes are investigated. In addition, the comparison between GRNN neural network application and conventional method was made. The error value showed the superlative results.

Keywords: SOFC, GRNN, Fuel cells.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1327891

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References:


[1] Y. Zhu, K. Tomsovic, Development of models for analyzing the loadfollowing performance of microturbines and fuel cells, Electric Power systems Research 62 (2002) 1-11.
[2] Oonsivilai, A. and M.E. El-Hawary: "A Self-Organizing Fuzzy Power System Stabilizer", IEEE. CCECE-98, 1998.
[3] Oonsivilai, A. and M.E. El-Hawary: "Power System Dynamic Load Modeling using Adaptive-Network-Based Fuzzy Inference System", IEEE. CCECE-99, 1999.
[4] Oonsivilai, A. and M.E. El-Hawary : "Wavelet Neural Network Based Short Term Load Forecasting of Electric Power System Commercial Load", IEEE. CCECE-99, 1999.
[5] Satonsaowapak, M., Krapeedang, M., Oonsivilai, R., and Oonsivilai, A. 2010. Gas flow rate identification in biomass power plants by response surface method. World Academy of Science, Engineering, and Technology, Paris, France, 27-29 October, pp: 261 - 264.