Real-Time Optimization of Organic Rankine Cycle Systems by Extremum-Seeking Control

Andres Hernandez, Adriano Desideri, Clara Ionescu, Robin De Keyser, Vincent Lemort and Sylvain Quoilin
Additional contact information
Andres Hernandez: Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium
Adriano Desideri: Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium
Clara Ionescu: Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium
Robin De Keyser: Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium
Vincent Lemort: Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium
Sylvain Quoilin: Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium

Energies, 2016, vol. 9, issue 5, 1-18

Abstract: In this paper, the optimal operation of a stationary sub-critical 11 kW el organic Rankine cycle (ORC) unit for waste heat recovery (WHR) applications is investigated, both in terms of energy production and safety conditions. Simulation results of a validated dynamic model of the ORC power unit are used to derive a correlation for the evaporating temperature, which maximizes the power generation for a range of operating conditions. This idea is further extended using a perturbation-based extremum seeking (ES) algorithm to identify online the optimal evaporating temperature. Regarding safety conditions, we propose the use of the extended prediction self-adaptive control (EPSAC) approach to constrained model predictive control (MPC). Since it uses input/output models for prediction, it avoids the need for state estimators, making it a suitable tool for industrial applications. The performance of the proposed control strategy is compared to PID-like schemes. Results show that EPSAC-MPC is a more effective control strategy, as it allows a safer and more efficient operation of the ORC unit, as it can handle constraints in a natural way, operating close to the boundary conditions where power generation is maximized.

Keywords: extremum-seeking (ES) control; organic Rankine cycle; model predictive control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://www.mdpi.com/1996-1073/9/5/334/pdf (application/pdf)
https://www.mdpi.com/1996-1073/9/5/334/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:9:y:2016:i:5:p:334-:d:69379

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().