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  •   Open Research
  • AUT Faculties
  • Faculty of Design and Creative Technologies (Te Ara Auaha)
  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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A Systematic Approach to Modelling Organic Rankine Cycle Systems for Global Optimization

Am, V; Currie, J; Wilson, D
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http://hdl.handle.net/10292/10668
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Abstract
As more innovative organic Rankine cycle (ORC) designs are being proposed, it is becoming more important that a reliable and robust modelling approach is crucial for optimizing these systems. While commercial simulation software exists, most are not tailored for optimization and they generally cannot guarantee global optimum. This paper proposes a modelling approach to approximate a rigorous simulation model that is suitable for global optimization. This involves a combination of regression and thermodynamic analysis, in addition to integer programming techniques. Three different global solvers, namely MATLAB’s genetic algorithm solver (ga), SCIP, and BARON are used to optimize the ORC model and are compared against each other to demonstrate the prospect of achieving the global optimum using this approach. In addition, this paper also presents a technique to improve the model accuracy and computation time by using a piecewise fit to approximate the output characteristic of the ORC unit operations.
Keywords
Computational modeling; Enthalpy; Mathematical model; Optimization; Turbines
Date
February 6, 2017
Source
2017 6th International Symposium on Advanced Control of Industrial Processes (AdCONIP), Taipei, Taiwan, 2017, pp. 487-492.
Item Type
Conference Contribution
Publisher
IEEE
DOI
10.1109/ADCONIP.2017.7983829
Publisher's Version
http://ieeexplore.ieee.org/document/7983829/
Rights Statement
Copyright © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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