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Estimation of operating parameters of a SOFC integrated combined power cycle using differential evolution based inverse method

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dc.contributor.author Sarmah, P.
dc.contributor.author Gogoi, T. K.
dc.contributor.author Das, R.
dc.date.accessioned 2021-10-15T00:05:33Z
dc.date.available 2021-10-15T00:05:33Z
dc.date.issued 2021-10-15
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/3048
dc.description.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. en_US
dc.language.iso en_US en_US
dc.subject SOFC en_US
dc.subject Combined cycle en_US
dc.subject Exergy en_US
dc.subject Inverse analysis en_US
dc.subject Differential evolution based optimization en_US
dc.title Estimation of operating parameters of a SOFC integrated combined power cycle using differential evolution based inverse method en_US
dc.type Article en_US


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