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Real-time optimization of organic rankine cycle systems by extremum-seeking control

(2016) ENERGIES. 9(5).
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Abstract
In this paper, the optimal operation of a stationary sub-critical 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
DIESEL-ENGINES, WASTE HEAT-RECOVERY, ORC, PERFORMANCE, extremum-seeking (ES) control, organic Rankine cycle, model predictive control

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Please use this url to cite or link to this publication:

MLA
Hernandez Naranjo, Jairo Andres et al. “Real-time Optimization of Organic Rankine Cycle Systems by Extremum-seeking Control.” ENERGIES 9.5 (2016): n. pag. Print.
APA
Hernandez Naranjo, J. A., Desideri, A., Ionescu, C.-M., De Keyser, R., Lemort, V., & Quoilin, S. (2016). Real-time optimization of organic rankine cycle systems by extremum-seeking control. ENERGIES, 9(5).
Chicago author-date
Hernandez Naranjo, Jairo Andres, Adriano Desideri, Clara-Mihaela Ionescu, Robain De Keyser, Vincent Lemort, and Sylvain Quoilin. 2016. “Real-time Optimization of Organic Rankine Cycle Systems by Extremum-seeking Control.” Energies 9 (5).
Chicago author-date (all authors)
Hernandez Naranjo, Jairo Andres, Adriano Desideri, Clara-Mihaela Ionescu, Robain De Keyser, Vincent Lemort, and Sylvain Quoilin. 2016. “Real-time Optimization of Organic Rankine Cycle Systems by Extremum-seeking Control.” Energies 9 (5).
Vancouver
1.
Hernandez Naranjo JA, Desideri A, Ionescu C-M, De Keyser R, Lemort V, Quoilin S. Real-time optimization of organic rankine cycle systems by extremum-seeking control. ENERGIES. 2016;9(5).
IEEE
[1]
J. A. Hernandez Naranjo, A. Desideri, C.-M. Ionescu, R. De Keyser, V. Lemort, and S. Quoilin, “Real-time optimization of organic rankine cycle systems by extremum-seeking control,” ENERGIES, vol. 9, no. 5, 2016.
@article{7204530,
  abstract     = {In this paper, the optimal operation of a stationary sub-critical 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.},
  articleno    = {334},
  author       = {Hernandez Naranjo, Jairo Andres and Desideri, Adriano and Ionescu, Clara-Mihaela and De Keyser, Robain and Lemort, Vincent and Quoilin, Sylvain},
  issn         = {1996-1073},
  journal      = {ENERGIES},
  keywords     = {DIESEL-ENGINES,WASTE HEAT-RECOVERY,ORC,PERFORMANCE,extremum-seeking (ES) control,organic Rankine cycle,model predictive control},
  language     = {eng},
  number       = {5},
  title        = {Real-time optimization of organic rankine cycle systems by extremum-seeking control},
  url          = {http://dx.doi.org/10.3390/EN9050334},
  volume       = {9},
  year         = {2016},
}

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