Multi - Objective Optimization for Hybrid Fuel Cells Power System Design

Unpublished AIChE will not be responsible for statements or opinions contained in papers or printed in its publications 1 Abstract The design and optimization of fuel cells in hybrid power systems is a complex problem involving integration of various components. At conceptual level, fuel cell power system consists of four components: (1) fuel processor, (2) fuel Power system, (3) power conditioner, and (4) a co-generation or bottoming cycle to reduce utilize rejected heat. The problem involves multiple objectives such as cost, pollutant emissions and process efficiency. The conflicting nature of these objectives makes the handling of this problem an even more formidable task. The solution of a multi-objective problem is not a single solution but a complete non-dominated or Pareto set, which includes the alternatives representing potential compromise solutions among the objectives. This makes a range of choice available to decision makers and provides them with the trade-off information among the multiple objectives effectively. We present a new and efficient approach to design optimal fuel cell hybrid power systems to address this problem. This methodology for multi-objective process design consistent with almost any simulation environment is based on an algorithmic approach, which formulates the synthesis tasks as a multi-objective optimization problem. A new efficient algorithm MINSOOP has been used which results in considerable computational savings. The Pareto optimal set for a SOFC-PEM hybrid power plant have been obtained which has designs with up to 55% savings in cost, 5% reduction in CO 2 emissions and up to 12 times higher SOFC current density than the base case. This provides a great deal of flexibility to decision makers by giving an effective knowledge of the trade-offs involved.