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Optimizing the operation of a solid oxide fuel cell power system with a supervisory controller based on the extremum-seeking approach
- Source :
- Energy Conversion and Management. 187:53-62
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Maintaining a high fuel-to-electricity conversion efficiency over a long period of time is important for successful market deployment of SOFC power systems. The conventional control solutions usually do not suffice to reach this goal. In order to properly handle variable load conditions and to mitigate degradation processes, on-line optimization is needed to adjust the process variables and to run the process as close as possible to the operational optimum. In this paper, a supervisory controller is proposed to optimize the operation of the SOFC power system. The outputs of the supervisory controller are references for the low-level controllers. The optimization is solved by means of the extremum-seeking approach where optimum is sought directly on the process. The main advantage is that the model of the process is not needed. The supervisory controller is assessed on a detailed physical model of a 2.5 kW SOFC power system at different load conditions. Simulation results show that the supervisory controller is capable to improve electrical efficiency and keep the system temperatures within the safe ranges. Consequently, degradation processes associated with the thermal stress of the stack are reduced. Due to the slow dynamics of the stack thermal processes, the convergence rate of the supervisory controller is rather slow. The proposed supervisory controller is thus appropriate for SOFC power systems that operate at constant load conditions over long periods of time.
- Subjects :
- Renewable Energy, Sustainability and the Environment
Computer science
020209 energy
Process (computing)
Energy Engineering and Power Technology
02 engineering and technology
Electric power system
Fuel Technology
020401 chemical engineering
Nuclear Energy and Engineering
Rate of convergence
Stack (abstract data type)
Control theory
Software deployment
0202 electrical engineering, electronic engineering, information engineering
Solid oxide fuel cell
0204 chemical engineering
Electrical efficiency
Subjects
Details
- ISSN :
- 01968904
- Volume :
- 187
- Database :
- OpenAIRE
- Journal :
- Energy Conversion and Management
- Accession number :
- edsair.doi...........f70144a29dbf31cad98df8a8a2099e5c
- Full Text :
- https://doi.org/10.1016/j.enconman.2019.03.012