Estimation of operating parameters of a SOFC integrated combined power cycle using differential evolution based inverse method. (5th June 2017)

• Record Type: Journal Article
• Authors: Sarmah, P.; Gogoi, T.K.; Das, R.
• Is Part Of: Applied thermal engineering. Volume 119(2017)
• Page Start: 98
• Page End: 107
• Publication Date: 2017-06-05
• Subjects: SOFC, Combined cycle -- Exergy -- Inverse analysis -- Differential evolution based optimization; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2017.03.060
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: Inverse analysis of a SOFC integrated combined power cycle is presented. Differential evolution (DE) based optimization algorithm is used. Six unknown operating parameters are estimated simultaneously. Net power, total irreversibility, energy and exergy efficiencies are taken as objective functions. Multiple combinations of operating parameters satisfy a given objective function. Abstract: Inverse analysis is an efficient method to estimate parameters that characterizes a given system. It offers lot of flexibility at the designer's hand in selecting the most suitable combination of parameters satisfying a given set of objective functions. In this study, inverse analysis of a solid oxide fuel cell (SOFC)–gas turbine (GT)–steam turbine (ST) combined cycle (CC) power system is performed. The system's net power, efficiencies (energy and exergy) and the total irreversibility at compressor pressure ratio (CPR) 6 and 14 are considered as objective functions for the inverse problem. A differential evolution (DE) based inverse algorithm is used for simultaneously estimating six operating parameters of the plant. It was seen that the inverse technique was very effective in estimating the operating parameters of a hybrid SOFC–GT–ST plant correctly within the prescribed lower and upper bound of the parameters. Multiple combinations of parameters are obtained from the study and all these combinations of parameters satisfy the given single objective function/set of objective functions. Any objective function value be set and then operating parameters be determined accordingly using the inverse method. The results offer plenty of scope for selection of suitable operating parameters for the plant.