Estimation of operating parameters of a reheat regenerative power cycle using simplex search and differential evolution based inverse methods. (February 2015)

• Record Type: Journal Article
• Authors: Gogoi, T.K.; Pandey, M.; Das, Ranjan
• Is Part Of: Energy conversion and management. Volume 91(2015)
• Page Start: 204
• Page End: 218
• Publication Date: 2015-02
• Subjects: Inverse analysis -- Reheat regenerative power cycle -- Parameter estimation -- Simplex search -- Differential evolution; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2014.11.046
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: Inverse analysis of a reheat regenerative vapor power cycle is presented. First the energy and exergy based parametric analysis is done. Next, the inverse analysis is done using simplex search and a differential evolution algorithm. Results obtained by both the methods are discussed for comparative analysis. Both the methods are found suitable for inverse solution of ST based power plant. Abstract: In this study, simplex search method (SSM) and a differential evolution (DE) based inverse algorithm are applied to estimate fuel flow rate (FFR), boiler pressure (BP) and steam turbine (ST) inlet temperature (STIT) of a ST based power cycle. First a theoretical model simulates the cycle performance in terms of net power, efficiency (energy and exergy) and total irreversibility at various FFRs, BPs and STITs. The forward model based results show that the net power increases linearly with FFR while also producing more irreversible losses at higher FFR. The cycle performance also improves at higher BP and STIT. The inverse analysis shows that the DE based method is more appropriate than the SSM where the searching range of parameters is specified and parameter estimation is done from the range of specified parameter values. In SSM, the estimation depends upon the chosen initial guess values and convergence criterion sometimes is not fulfilled with some guessed values of the parameters. Both the inverse methods, however give multiple combinations of parameters and thus provides sufficient scope at the hands of the designer to select the appropriate combinations of parameters required for meeting a particular power requirement.