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Energies 2016, 9(5), 334; doi:10.3390/en9050334

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

1
Department of Electrical Energy, Systems and Automation, Ghent University, 9000 Ghent, Belgium
2
Thermodynamics Laboratory, University of Liege, Campus du Sart Tilman B49, 4000 Liege, Belgium
This paper is an extended version of our paper published in Proceedings of the ASME ORC 2015 Conference, Brussels, Belgium, 12–14 October 2015
*
Author to whom correspondence should be addressed.
Academic Editor: Antonio Calvo Hernández
Received: 1 February 2016 / Revised: 20 April 2016 / Accepted: 26 April 2016 / Published: 4 May 2016
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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. View Full-Text
Keywords: extremum-seeking (ES) control; organic Rankine cycle; model predictive control extremum-seeking (ES) control; organic Rankine cycle; model predictive control
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Hernandez, A.; Desideri, A.; Ionescu, C.; De Keyser, R.; Lemort, V.; Quoilin, S. Real-Time Optimization of Organic Rankine Cycle Systems by Extremum-Seeking Control. Energies 2016, 9, 334.

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