Exergy Analysis of a Subcritical Reheat Steam Power Plant with Regression Modeling and Optimization

  • Muhib Ali Rajper Jamshoro Power Company Limited, Jamshoro.
  • Abdul Ghafoor Memon Department of Mechanical Engineering, Mehran University of Engineering and Technology, Jamshoro.
  • Khanji Harijan Department of Mechanical Engineering, Mehran University of Engineering and Technology, Jamshoro.

Abstract

In this paper, exergy analysis of a 210 MW SPP (Steam Power Plant) is performed. Firstly, the plant is modeled and validated, followed by a parametric study to show the effects of various operating parameters on the performance parameters. The net power output, energy efficiency, and exergy efficiency are taken as the performance parameters, while the condenser pressure, main steam pressure, bled steam pressures, main steam temperature, and reheat steam temperature isnominated as the operating parameters. Moreover, multiple polynomial regression models are developed to correlate each performance parameter with the operating parameters. The performance is then optimizedby using Direct-searchmethod. According to the results, the net power output, energy efficiency, and exergy efficiency are calculated as 186.5 MW, 31.37 and 30.41%, respectively under normal operating conditions as a base case. The condenser is a major contributor towards the energy loss, followed by the boiler, whereas the highest irreversibilities occur in the boiler and turbine. According to the parametric study, variation in the operating parameters greatly influences the performance parameters. The regression models have appeared to be a good estimator of the performance parameters. The optimum net power output, energy efficiency and exergy efficiency are obtained as 227.6 MW, 37.4 and 36.4, respectively, which have been calculated along with optimal values of selected operating parameters.

Published
Jul 1, 2016
How to Cite
RAJPER, Muhib Ali; MEMON, Abdul Ghafoor; HARIJAN, Khanji. Exergy Analysis of a Subcritical Reheat Steam Power Plant with Regression Modeling and Optimization. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 35, n. 3, p. 459-472, july 2016. ISSN 2413-7219. Available at: <https://publications.muet.edu.pk/index.php/muetrj/article/view/473>. Date accessed: 26 apr. 2024. doi: http://dx.doi.org/10.22581/muet1982.1603.16.
Section
Articles
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License