Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant
Analytical models; Coal fueled furnaces; Codes (symbols); Exergy; Fossil fuel power plants; Thermoelectric power plants; Coal fired thermal power plants; Coal-fired; Energy and exergy; Engineering equation solvers; Feedwater; Feedwater heater; Numerical code; Performance; Power; Predictive models; C...
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2023
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my.uniten.dspace-258762023-05-29T17:05:23Z Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant Khaleel O.J. Ibrahim T.K. Ismail F.B. Al-Sammarraie A.T. 57287206400 36730964600 58027086700 57195757756 Analytical models; Coal fueled furnaces; Codes (symbols); Exergy; Fossil fuel power plants; Thermoelectric power plants; Coal fired thermal power plants; Coal-fired; Energy and exergy; Engineering equation solvers; Feedwater; Feedwater heater; Numerical code; Performance; Power; Predictive models; Coal In the present study, an analytical model has been developed to predict the effectiveness of the closed feedwater heaters based on the measured data available from a coal-fired thermal power plant. Invoking this model, a �Predictive Model� has been developed to anticipate the energy and exergy-based behavior of the coal-fired power plants. In this model, all the components have been assumed to be installed, and hence they could not be changed. Based on this model, a numerical code has been developed to analyze an existing coal-fired power plant using Engineering Equation Solver software. Invoking this code, the impact of the operational conditions on the performance of the power plant is examined. The effects of superheater outlet pressure, superheater outlet temperature, and reheater inlet pressure upon energy and exergy-based parameters of the cycle have been examined. It has been observed that by increasing the superheater pressure by 100%, the net power delivered by the cycle increases more than 8%. While increasing the superheated steam temperature from 539.8 to 580 �C, the net power delivered by the cycle increases more than 6%. Further, by increasing the reheater pressure from 30 to 34 bar, the net power delivered by the cycle reduces 1.57%. � 2021 Final 2023-05-29T09:05:23Z 2023-05-29T09:05:23Z 2021 Article 10.1016/j.csite.2021.101519 2-s2.0-85116571475 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116571475&doi=10.1016%2fj.csite.2021.101519&partnerID=40&md5=cc0b40f66c1e5deb2a46c97f0dda32e6 https://irepository.uniten.edu.my/handle/123456789/25876 28 101519 All Open Access, Gold Elsevier Ltd Scopus |
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Analytical models; Coal fueled furnaces; Codes (symbols); Exergy; Fossil fuel power plants; Thermoelectric power plants; Coal fired thermal power plants; Coal-fired; Energy and exergy; Engineering equation solvers; Feedwater; Feedwater heater; Numerical code; Performance; Power; Predictive models; Coal |
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57287206400 |
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57287206400 Khaleel O.J. Ibrahim T.K. Ismail F.B. Al-Sammarraie A.T. |
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Khaleel O.J. Ibrahim T.K. Ismail F.B. Al-Sammarraie A.T. |
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Khaleel O.J. Ibrahim T.K. Ismail F.B. Al-Sammarraie A.T. Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant |
author_sort |
Khaleel O.J. |
title |
Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant |
title_short |
Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant |
title_full |
Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant |
title_fullStr |
Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant |
title_full_unstemmed |
Developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant |
title_sort |
developing an analytical model to predict the energy and exergy based performances of a coal-fired thermal power plant |
publisher |
Elsevier Ltd |
publishDate |
2023 |
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1806427569575165952 |
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13.214268 |