Computational Model for High-Pressurized Heat Recovery Steam Generator Heat Transfer Study

Author(s):  
D.A. Khokhlov ◽  
M. N. Zaichenko ◽  
K. V. Sterkhov ◽  
K.A. Pleshanov
2013 ◽  
Vol 845 ◽  
pp. 596-603
Author(s):  
Mesfin G. Zewge ◽  
T.A. Lemma ◽  
A.A. Ibrahim ◽  
D. Sujan

In a cogeneration or combined heat and power plant, a heat recovery steam generator (HRSG) helps achieve overall thermal efficiency as high as 80%. The purpose of this study is to model and simulate the HRSG given partial design point data. The pinch and approach temperatures are optimized within generally accepted range. In order to satisfy the energy conservation equation, tuning parameters are used for the overall heat transfer coefficients corresponding to the evaporator and economizer. For the off-design simulation, the values of pinch and approach temperatures are adjusted until the modeling error is within a set limit. The effect of mass flow rate on the heat transfer coefficient is accounted for & by employing empirical relations. A 12 Ton/hr natural circulation HRSG was considered as a case study. The validation test on inlet temperatures of the exhaust gas and feed water to the economizer demonstrated relative percentage errors of 0.4246% and 1.8776%, respectively. The model can be used for fault detection and diagnostic system design, performance optimization, and environmental load assessment.


Author(s):  
Jose Ramon Vega-Galaz ◽  
Oscar Garci´a-Bulle´ ◽  
Ken Cassel

The mobile cogeneration unit (MCU) consists of two gas turbines and one heat recovery steam generator mounted in a trailer with standard dimensions to supply 3 MW of electricity at ISO conditions and 14,000 to 28,000 pounds per hour of superheated steam depending on duct burner duty and steam conditions. A computational model using Thermoflex software was developed to adjust Test Cell measurements with it. The purpose of this model is to predict MCU performance in different sites of implementation. Some field measurements in Test Cell and other sites are compared with model results showing very good approach.


2019 ◽  
Vol 66 (5) ◽  
pp. 331-339
Author(s):  
M. N. Maidanik ◽  
A. N. Tugov ◽  
N. I. Mishustin ◽  
A. E. Zelinskii

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