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Experimental Activity on the Tubular SOFC CHP100 kWe Field Unit in Italy: Factor Significance, Effects and Regression Model Analysis

[+] Author Affiliations
M. Calì, M. Santarelli, P. Leone

Politecnico di Torino, Torino, Italy

G. Orsello

Gas Turbine Technologies, Torino, Italy

Paper No. ESDA2006-95802, pp. 275-284; 10 pages
  • ASME 8th Biennial Conference on Engineering Systems Design and Analysis
  • Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering
  • Torino, Italy, July 4–7, 2006
  • ISBN: 0-7918-4248-7 | eISBN: 0-7918-3779-3
  • Copyright © 2006 by ASME


The CHP 100 kWe tubular SOFC plant built by Siemens is operating at the Gas Turbine Technologies (GTT) in Turin. The generator started up on the June 2005 and produces electric and thermal power used in the factory. A first period of the activity was needed to lead the operation of the SOFC plant at the nominal condition and to reach the complete conditioning of the SOFC tubular fuel cells. Then, in order to characterize the operation of the generator and of the cogenerative system a first experimental campaign was designed by using the factorial analysis. With these methods, the effect of some independent variables (factors) on the plant operation is analyzed in form of screening tests: the analysis allows one to estimate the significance of the main and combined effects of each considered factor through an analysis of variance (ANOVA) on the experimental data. Moreover, the test plan has been designed by using a simple 2k factorial and a 2k factorial with spherical central composite design (CCD); these approaches allow to obtain respectively first-order and second-order regression models for some chosen dependent variables (i.e. DC and AC electric power, generator voltage, recovered heat etc...). The test plan has been performed at the fixed generator current of 500 Amps with two repetitions for each designed treatment. The factorial analysis has been applied considering two factors (22 factorial analysis): setup temperature of the generator and fuel utilization factor. First, the significance of the main and combined effects of the two considered factor has been evaluated. Then, the obtained data have been analyzed by using the Response Surface Methodology analysis (RSM). Finally, the regression models have been obtained for every dependent variable analyzed, with an outline of the sensitivity coefficient linking the dependent and the independent variables.

Copyright © 2006 by ASME



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