Robust Real-Time Optimization of a Solid Oxide Fuel Cell Stack

On-line control and optimization can improve the eﬃciency of fuel cell systems whilst simultaneously ensuring that the operation remains within a safe region. Also, fuel cells are subject to frequent variations in their power demand. This paper investigates the real-time optimization (RTO) of a solid oxide fuel cell (SOFC) stack. An optimization problem maximizing the efficiency subject to operating constraints is deﬁned. Due to inevitable model inaccuracies, the open-loop implementation of optimal inputs evaluated oﬀ-line may be suboptimal, or worse, infeasible. Infeasibility can be avoided by controlling the constrained quantities. However, the constraints that determine optimal operation might switch with varying power demand, thus requiring a change in the regulator structure.

Real-time optimization of an experimental solid-oxide fuel-cell system

Dominique Bonvin, Alejandro Gabriel Marchetti, Christophe Salzmann, Jan Van Herle, Zacharie Wuillemin

There still exists a large gap between simulation work and industrial applications in the context of control and optimization of solid-oxide fuel-cell (SOFC) systems. In an effort to bridge this gap, this study describes the experimental implementation of steady-state real-time optimization (RTO) to an SOFC system that consists of both hardware and software components. The proposed adaptive optimization scheme uses an approximate steady-state model of the fuel-cell system and corrects it "appropriately" so that it becomes "excellent" for optimization. This way, the plant can be steered efficiently toward optimality, while meeting the varying electric power demand. In these experiments, the plant efficiency was increased from 55% to 62% through application of RTO. Furthermore, although the SOFC system is characterized by slow thermal dynamics that may take a few hours to settle to steady state, it has been possible to reduce the time necessary to reach the power setpoint from 1 h to about 5 min thanks to the use of transient measurements and a dynamic model. This experimental work has shown that it is possible, not only to control the SOFC system at a desired operating point, but also to operate it near optimality despite changes in power demand.

ELSEVIER SCIENCE BV2019

Fast RTO Applied to a Commercial SOFC System

Dominique Bonvin, Alejandro Gabriel Marchetti, Zacharie Wuillemin

The experimental implementation of real-time optimization (RTO) to a commercial solid-oxide fuel-cell (SOFC) system is reported in this paper. The goal of RTO is to maximize the system efficiency at steady state subject to several operating constraints. The proposed RTO strategy is a constraint-adaptation approach, which consists in adding bias correction terms to the constraints in the optimization problem. These bias terms are estimated during operation using transient measurements in combination with a dynamic model. The scheme enforces plant optimality by continuously detecting and tracking the set of active constraints. This approach drives the fuel-cell system quickly to the desired power demand, while maximizing the efficiency and paying attention to constraint satisfaction. As such, this RTO scheme has the ability to both control and optimize fuel-cell systems. This experimental system reached about 65% efficiency. In addition, it was possible to deal with slow drifts such as degradation without compromising on optimality. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

ELSEVIER SCIENCE BV2019

Thermo-economic Optimization of a Solid Oxide Fuel Cell, Gas Turbine Hybrid System

Nordahl Autissier, Daniel Favrat, François Maréchal, Francesca Palazzi, Jan Van Herle

Background: The electricity production market benefits from combined cycles with their high efficiency. In the lower power range, Fuel Cells are a good candidate to combine with gas turbines. Such systems can achieve efficiencies of 60% and more. High temperature Solid Oxide Fuel Cells (SOFC) offer good opportunities for this coupling. A systematic method to select a design according to user specifications is presented. Method of approach: The most attracting configurations of this technology coupling are identified using a thermo-economic multi-objective optimization approach. The SOFC model includes detailed computation of losses of the electrodes and thermal management. The system is integrated using pinch based methods. A thermo-economic method is then used to compute the integrated system performances, size and cost. This allows to perform the optimization of the system with regard to two objectives: minimize the specific cost and maximize the efficiency. Results: Optimization results prove the existence of designs with costs from 2400

/kW for a 44\% efficiency to 6700

/kW for a 70% efficiency. Several design options are analysed regarding fuel processing, pressure ratio or turbine inlet temperature among others. Conclusions: A pressurized SOFC-

\mu

GT hybrid cycle has been modeled for design purposes. Combining state-of-the-art planar SOFC with high speed micro gas turbine sustained by air bearings. The proposed optimization method allows to identify the most interesting design configurations to reach high efficiencies for a given cost.

2005

Thermo-economic Optimization of a Solid Oxide Fuel Cell, Gas Turbine Hybrid System

Nordahl Autissier, Daniel Favrat, François Maréchal, Francesca Palazzi, Jan Van Herle

/kW for a 44\% efficiency to 6700

/kW for a 70% efficiency. Several design options are analysed regarding fuel processing, pressure ratio or turbine inlet temperature among others. Conclusions: A pressurized SOFC-

\mu

2005