A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization

Based on the benefits of integrated gasification combined cycles (IGCCs), a cogeneration plant for providing electricity and freshwater is proposed. The main novelties of the devised system are the integration of biomass gasification and a regenerative gas turbine with intercooling and a syngas comb...

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Main Authors: Farzad Hamrang, S. M. Seyed Mahmoudi, Marc A. Rosen
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/13/11/6448
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spelling doaj-6ec7c331df814b12a283730d8382e0a22021-06-30T23:26:03ZengMDPI AGSustainability2071-10502021-06-01136448644810.3390/su13116448A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective OptimizationFarzad Hamrang0S. M. Seyed Mahmoudi1Marc A. Rosen2Department of Mechanical Engineering, University of Tabriz, Tabriz 51666-14766, IranDepartment of Mechanical Engineering, University of Tabriz, Tabriz 51666-14766, IranFaculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, ON L1G 0C5, CanadaBased on the benefits of integrated gasification combined cycles (IGCCs), a cogeneration plant for providing electricity and freshwater is proposed. The main novelties of the devised system are the integration of biomass gasification and a regenerative gas turbine with intercooling and a syngas combustor, where the syngas produced in the gasifier is burned in the combustion chamber and fed to a gas turbine directly. The energy discharged from the gas turbine is utilized for further electricity and freshwater generation via Kalina and MED hybridization. The proposed system is analyzed from energy, exergy, exergoeconomic, and reliability–availability viewpoints. The optimal operating condition and optimum performance criteria are obtained by hybridizing an artificial neural network (ANN), the multi-objective particle swarm optimization (MOPSO) algorithm. According to results obtained, for the fourth scenario of the optimization process, optimal values of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>45.10</mn><mo>%</mo></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>14.27</mn><mrow><mtext> </mtext><mi>kg</mi></mrow><mo>·</mo><msup><mi mathvariant="normal">s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>12.95</mn><mrow><mtext> </mtext><mi>USD</mi></mrow><mo>·</mo><msup><mrow><mi>GJ</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>8141</mn><mrow><mtext> </mtext><mi>kW</mi></mrow></mrow></semantics></math></inline-formula> are obtained for the exergy efficiency, freshwater production rate, sum unit cost of products, and net output power, respectively. According to reliability and availability assessment, the probability of the healthy working state of all components and subsystems is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>88.4403</mn><mo>%</mo><mo>;</mo></mrow></semantics></math></inline-formula> the system is shown to be <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>87.74</mn><mo>%</mo></mrow></semantics></math></inline-formula> available of the time over the 20-year lifetime.https://www.mdpi.com/2071-1050/13/11/6448electricity and freshwater cogenerationavailability and reliabilityexergoeconomic assessmentmulti-objective optimizationartificial neural network
collection DOAJ
language English
format Article
sources DOAJ
author Farzad Hamrang
S. M. Seyed Mahmoudi
Marc A. Rosen
spellingShingle Farzad Hamrang
S. M. Seyed Mahmoudi
Marc A. Rosen
A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization
Sustainability
electricity and freshwater cogeneration
availability and reliability
exergoeconomic assessment
multi-objective optimization
artificial neural network
author_facet Farzad Hamrang
S. M. Seyed Mahmoudi
Marc A. Rosen
author_sort Farzad Hamrang
title A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization
title_short A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization
title_full A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization
title_fullStr A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization
title_full_unstemmed A Novel Electricity and Freshwater Production System: Performance Analysis from Reliability and Exergoeconomic Viewpoints with Multi-Objective Optimization
title_sort novel electricity and freshwater production system: performance analysis from reliability and exergoeconomic viewpoints with multi-objective optimization
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2021-06-01
description Based on the benefits of integrated gasification combined cycles (IGCCs), a cogeneration plant for providing electricity and freshwater is proposed. The main novelties of the devised system are the integration of biomass gasification and a regenerative gas turbine with intercooling and a syngas combustor, where the syngas produced in the gasifier is burned in the combustion chamber and fed to a gas turbine directly. The energy discharged from the gas turbine is utilized for further electricity and freshwater generation via Kalina and MED hybridization. The proposed system is analyzed from energy, exergy, exergoeconomic, and reliability–availability viewpoints. The optimal operating condition and optimum performance criteria are obtained by hybridizing an artificial neural network (ANN), the multi-objective particle swarm optimization (MOPSO) algorithm. According to results obtained, for the fourth scenario of the optimization process, optimal values of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>45.10</mn><mo>%</mo></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>14.27</mn><mrow><mtext> </mtext><mi>kg</mi></mrow><mo>·</mo><msup><mi mathvariant="normal">s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>12.95</mn><mrow><mtext> </mtext><mi>USD</mi></mrow><mo>·</mo><msup><mrow><mi>GJ</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>8141</mn><mrow><mtext> </mtext><mi>kW</mi></mrow></mrow></semantics></math></inline-formula> are obtained for the exergy efficiency, freshwater production rate, sum unit cost of products, and net output power, respectively. According to reliability and availability assessment, the probability of the healthy working state of all components and subsystems is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>88.4403</mn><mo>%</mo><mo>;</mo></mrow></semantics></math></inline-formula> the system is shown to be <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>87.74</mn><mo>%</mo></mrow></semantics></math></inline-formula> available of the time over the 20-year lifetime.
topic electricity and freshwater cogeneration
availability and reliability
exergoeconomic assessment
multi-objective optimization
artificial neural network
url https://www.mdpi.com/2071-1050/13/11/6448
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