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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Rossi, Iacopo Zaccaria, Valentina Traverso, Alberto |
| Copyright Year | 2017 |
| Abstract | The use of model predictive control (MPC) in advanced power systems can be advantageous in controlling highly coupled variables and optimizing system operations. Solid oxide fuel cell/ gas turbine (SOFC/GT) hybrids are an example where advanced control techniques can be effectively applied. For example, to manage load distribution among several identical generation units characterized by different temperature distributions due to different degradation paths of the fuel cell stacks. When implementing a MPC, a critical aspect is the trade-off between model accuracy and simplicity, the latter related to a fast computational time. In this work, a hybrid physical and numerical approach was used to reduce the number of states necessary to describe such complex target system. The reduced number of states in the model and the simple framework allow real-time performance and potential extension to a wide range of power plants for industrial application, at the expense of accuracy losses, discussed in the paper. |
| Sponsorship | International Gas Turbine Institute |
| File Format | |
| ISBN | 9780791850831 |
| DOI | 10.1115/GT2017-64194 |
| Volume Number | Volume 3: Coal, Biomass and Alternative Fuels; Cycle Innovations; Electric Power; Industrial and Cogeneration Applications; Organic Rankine Cycle Power Systems |
| Conference Proceedings | ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition |
| Language | English |
| Publisher Date | 2017-06-26 |
| Publisher Place | Charlotte, North Carolina, USA |
| Access Restriction | Subscribed |
| Subject Keyword | Temperature distribution Solid oxide fuel cells Gas turbines Power systems (machinery) Fuel cells Tradeoffs Power stations Stress Predictive control |
| Content Type | Text |
| Resource Type | Article |
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