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

Abstract

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.