Multi-objective optimization of a novel syngas fed SOFC power plant using a downdraft gasifier. (1st April 2018)
- Record Type:
- Journal Article
- Title:
- Multi-objective optimization of a novel syngas fed SOFC power plant using a downdraft gasifier. (1st April 2018)
- Main Title:
- Multi-objective optimization of a novel syngas fed SOFC power plant using a downdraft gasifier
- Authors:
- Sadeghi, M.
Mehr, A.S.
Zar, M.
Santarelli, M. - Abstract:
- Abstract: A syngas fed SOFC cogeneration system using a downdraft gasifier is modeled and optimized from the viewpoints of thermodynamics and thermoeconomics. A multi-objective optimization method based on genetic algorithm in the form of two different scenarios is carried out. In scenario I (exergoeconomic) the total exergy gained ( TEG CHP ) and total product unit cost ( c p ) of the system are considered as two objective functions, while in scenario II (exergoenviroment) and normalized CO2 emission ( ε ) are presumed as the two objectives. In both scenarios, optimization process is performed with the aim of maximizing the total exergy gained and minimizing the second objective function (in scenario I and in scenario II). The optimization results demonstrates that minimization of the total product unit cost of system as the only criterion leads to the higher values of normalized CO2 emission and lower values of the system exergy efficiency. In addition, it is revealed that, at the optimal conditions, despite the lower amounts of stack inlet temperature and current density for scenario II, the net electrical power obtained by scenario I is quite higher. Highlights: A cogeneration system based on syngas fed SOFC plant is modeled thermodynamically. A downdraft gasifier is integrated with the SOFC power plant. Multi-objective optimization in the form of two different scenarios is carried out. Total exergy gained and total product unit cost are two objectives in scenario I.Abstract: A syngas fed SOFC cogeneration system using a downdraft gasifier is modeled and optimized from the viewpoints of thermodynamics and thermoeconomics. A multi-objective optimization method based on genetic algorithm in the form of two different scenarios is carried out. In scenario I (exergoeconomic) the total exergy gained ( TEG CHP ) and total product unit cost ( c p ) of the system are considered as two objective functions, while in scenario II (exergoenviroment) and normalized CO2 emission ( ε ) are presumed as the two objectives. In both scenarios, optimization process is performed with the aim of maximizing the total exergy gained and minimizing the second objective function (in scenario I and in scenario II). The optimization results demonstrates that minimization of the total product unit cost of system as the only criterion leads to the higher values of normalized CO2 emission and lower values of the system exergy efficiency. In addition, it is revealed that, at the optimal conditions, despite the lower amounts of stack inlet temperature and current density for scenario II, the net electrical power obtained by scenario I is quite higher. Highlights: A cogeneration system based on syngas fed SOFC plant is modeled thermodynamically. A downdraft gasifier is integrated with the SOFC power plant. Multi-objective optimization in the form of two different scenarios is carried out. Total exergy gained and total product unit cost are two objectives in scenario I. Total exergy gained and normalized CO2 emission are two objectives in scenario II. … (more)
- Is Part Of:
- Energy. Volume 148(2018)
- Journal:
- Energy
- Issue:
- Volume 148(2018)
- Issue Display:
- Volume 148, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 148
- Issue:
- 2018
- Issue Sort Value:
- 2018-0148-2018-0000
- Page Start:
- 16
- Page End:
- 31
- Publication Date:
- 2018-04-01
- Subjects:
- SOFC -- Syngas -- Gasification -- Multi-objective optimization -- CO2 emission -- Exergy
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2018.01.114 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11479.xml