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Two strategies for multi-objective optimisation of solid oxide fuel cell stacks

Roshandel, R ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1080/14786451.2013.777337
  3. Abstract:
  4. This paper focuses on multi-objective optimisation (MOO) to optimise the planar solid oxide fuel cell (SOFC) stacks performance using a genetic algorithm. MOO problem does not have a single solution, but a complete Pareto curve, which involves the optional representation of possible compromise solutions. Here, two pairs of different objectives are considered as distinguished strategies. Optimisation of the first strategy predicts a maximum power output of 108.33 kW at a breakeven per-unit energy cost of 0.51 $/kWh and minimum breakeven per-unit energy cost of 0.30 $/kWh at a power of 42.18 kW. In the second strategy, maximum efficiency of 63.93%at a breakeven per-unit energy cost of 0.42 $/kWh is predicted, while minimum breakeven per-unit energy cost of 0.25 $/kWh at efficiency of 48.3% is obtained. The present study creates the basis for selecting optimal operating conditions of SOFC under the face of multiple conflicting objectives
  5. Keywords:
  6. Costs ; Genetic algorithms ; Models ; Multiobjective optimization ; Conflicting objectives ; Maximum Efficiency ; Maximum power output ; Optimal operating conditions ; Pareto curve ; Planar solid oxide fuel cells ; Solid oxide fuel cells (SOFC) ; Efficiency measurement ; Fuel cell ; Modeling ; Optimization ; Performance assessment
  7. Source: International Journal of Sustainable Energy ; Vol. 33, issue. 4 , 2014 , p. 854-868
  8. URL: http://www.tandfonline.com/doi/abs/10.1080/14786451.2013.777337