Multi-objective optimization of a direct methanol fuel cell system using a genetic-based algorithm

International Journal of Energy Research

Volumn 37, Issue 10, 2013, Pages 1256-1264

  Mert, Suha Orçun ^a   Özçelik, Zehra ^a  

^a EGE UNIVERSITY   (Turkey)

Author keywords

DMFC; Efficiency; Energy; Exergy; Genetic algorithm; Multi objective optimization

Indexed keywords

DIRECT METHANOL; ENERGY; ENERGY AND EXERGY EFFICIENCY; FITNESS FUNCTIONS; GENETIC-BASED ALGORITHMS; OBJECTIVE FUNCTIONS; OPERATING CONDITION; OPTIMIZATION OBJECTIVE FUNCTION;

DIRECT METHANOL FUEL CELLS (DMFC); EFFICIENCY; EXERGY; FUEL SYSTEMS; GENETIC ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION;

ENERGY EFFICIENCY;

EID: 84880314471     PISSN: 0363907X     EISSN: 1099114X     Source Type: Journal    
DOI: 10.1002/er.2963     Document Type: Article

References (23)

1. Dinçer İ, Rosen M. Exergy: Energy, Environment, and Sustainable Development, Vol. 1. Elsevier: China, 2007; 11-14.
2. Larminie J, Dicks A. Fuel Cell Systems Explained. Wiley: New York, 2003.
3. Ehrgott M. Multicriteria Optimization, 2nd edn. Springer: Berlin, 2005.
4. Molla S, Compan V, Lafuente SL, Prats J. On The Methanol Permeability through Pristine Nafion and Nafion/PVA Membranes Measured by Different Techniques: A Comparison of Methodologies. Fuel Cells 2011. doi:10.1002/fuce.201100004.
5. Asplund RW. Profiting from Clean Energy. John Wiley and Sons Inc.: New Jersey, 2008.
6. Zhao TS, Chen R. Recent progress in understanding of coupled heat/mass transport and electrochemical reactions in fuel cells. International Journal of Energy Research 2011; 35(1):15-23.
7. Mahmoud A, Dincer I. A review on methanol crossover in direct methanol fuel cells: challenges and achievements. International Journal of Energy Research V. 2011; 35(14):1213-1228.
8. Baghernejad A, Yaghoubi M. Multi-objective exergoeconomic optimization of an Integrated Solar Combined Cycle System using evolutionary algorithms. International Journal of Energy Research 2011; 35(7):601-615.
9. Barzegar Avval H, Ahmadi P, Ghaffarizadeh AR, Saidi MH. Thermo-economic-environmental multiobjective optimization of a gas turbine power plant with preheater using evolutionary algorithm. International Journal of Energy Research 2011; 35(5):389-403.
10. Ahmadi P, Almasi A, Shahriyari M, Dincer I. Multi-objective optimization of a combined heat and power (CHP) system for heating purpose in a paper mill using evolutionary algorithm. International Journal of Energy Research 2012; 36(1):46-63.
11. Dirk B, Stoll P, Koumoutsakos P. An evolutionary algorithm for multi-objective optimization of combustion processes. Center for Turbulence Research, Annual Research Briefs, 2001; 231-239.
12. Mert SO, Özçelik Z, Özçelik Y, Dincer I. Multi-Objective Optimization of a Vehicular PEM Fuel Cell System. Applied Thermal Engineering 2011; 31(13):2171-2176.
13. Dohle H, Wippermann K. Experimental Evaluation and Semi-empirical Modeling of U/I Characteristics and Methanol Permeation of a Direct Methanol Fuel Cell. Journal of Power Sources 2004; 135:152-164.
14. Hotz N, Lee MT, Grigoropoulos CP, Senn SM, Poulikakos D. Exergetic Analysis of Fuel Cell Micropowerplants Fed by Methanol. International Journal of Heat and Mass Transfer 2006; 49:2397-2411.
15. Jao TC, Jung GB, Ke ST, Chi PH, Chan SH. Diagnosis of PTFE-Nafion MEA degradation modes by an accelerated degradation technique. International Journal of Energy Research 2011; 35(14):1274-1283.
16. Coello CA et al. Evolutionary Algorithms for Solving Multi-Objective Problems. Springer: New York, 2007.
17. Collette Y, Siarry P. Multiobjective Optimization, Principles and Case Studies. Springer: Berlin, 2002.
18. Donoso Y. Multi-objective Optimization in Computer Networks using Metaheuristics. Taylor & Francis: New York, 2007.
19. Timm NH. Applied Multivariate Analysis. Springer: New York, 2002.
20. Özçelik Y. Exergetic Optimization of Shell and Tube Heat Exchangers using a Genetic Based Algorithm. Applied Thermal Engineering 2007; 27:1849-1856.
21. Zitzler E, Laumanns M, Bleuler S. A Tutorial on Evolutionary Multiobjective, Metaheuristics for Multiobjective Optimization. Springer: New York, 2004.
22. Konak A, Coit DW, Smith AE. Multi-objective Optimization using Genetic Algorithms: a Tutorial. Reliability Engineering and System Safety 2006; 91(9):992-1007.
23. Edgar T, Himmelblau D. Optimization of Chemical Processes. McGraw-Hill: New York, 2001.