Real-Time Optimization of Organic Rankine Cycle Systems by Extremum-Seeking Control†Report as inadecuate




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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

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





Author: Andres Hernandez 1,2,* , Adriano Desideri 2, Clara Ionescu 1, Robin De Keyser 1, Vincent Lemort 2 and Sylvain Quoilin 2

Source: http://mdpi.com/



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