Experimental Real-Time Optimization of a Solid Oxide Fuel Cell Stack via Constraint Adaptation

The experimental validation of a real-time optimization (RTO) strategy for the optimal operation of a solid oxide fuel cell (SOFC) stack is reported in this paper. Unlike many existing studies, the RTO approach presented here utilizes the constraint-adaptation methodology, which assumes that the optimal operating point lies on a set of constraints and then seeks to satisfy those constraints in practice via bias update terms. These biases correspond to the difference between predicted and measured outputs and are updated at each steady-state iteration, allowing the RTO to successfully meet the optimal operating conditions of a 6-cell SOFC stack, despite significant plant-model mismatch. The effects of the bias update filter values and of the RTO frequency on the power tracking and constraint handling are also investigated.


Editor(s):
Favrat, Daniel
Maréchal, François
Published in:
Proceedings of 23rd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, Lausanne, V - Fuel Cell and International Combustion Engines, 141-148
Presented at:
23rd Int. Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, Lausanne, June 14-17, 2010
Year:
2010
ISBN:
9781456303204
Keywords:
Laboratories:




 Record created 2010-02-15, last modified 2018-03-17

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