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An experimentally validated, energy focused, optimal control strategy for an Organic Rankine Cycle waste heat recovery system

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  • Rathod, Dhruvang
  • Xu, Bin
  • Filipi, Zoran
  • Hoffman, Mark

Abstract

This paper presents a Nonlinear Model Predictive Controller (NMPC) designed to provide optimal control input for maximum turbine power generation in an Organic Rankine Cycle (ORC) Waste Heat Recovery (WHR) system. While the literature is rich in ORC-WHR system modeling and control approaches in simulation environments, the fundamental dynamic analysis, system aging, thermal inertia, and experimental implementation of power optimization based optimal ORC-WHR control are still lacking. These factors are key to fully understanding and controlling the dynamic behavior of the system and are the main focus of this study. In contrast to prior literature, this work experimentally evaluates the nonlinear dynamics of the ORC system to comprehensively understand the controller design requirements. A power optimization-based Nonlinear Model Predictive Controller (NMPC) is derived utilizing an Extended Kalman Filter (EKF) as a state estimator. Simulation results indicate that optimal turbine power generation is obtained with minimal working fluid superheat for the system under study. Consequently, a superheat-tracking controller is designed, and the performance of the controller is simulated over step inputs. The designed controller is then experimentally validated on an ORC test rig with a 13L Heavy Duty Diesel Engine (HDDE).

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  • Rathod, Dhruvang & Xu, Bin & Filipi, Zoran & Hoffman, Mark, 2019. "An experimentally validated, energy focused, optimal control strategy for an Organic Rankine Cycle waste heat recovery system," Applied Energy, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:appene:v:256:y:2019:i:c:s0306261919316782
    DOI: 10.1016/j.apenergy.2019.113991
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ying Zhang & Li Zhao & Shuai Deng & Ming Li & Yali Liu & Qiongfen Yu & Mengxing Li, 2022. "Novel Off-Design Operation Maps Showing Functionality Limitations of Organic Rankine Cycle Validated by Experiments," Energies, MDPI, vol. 15(21), pages 1-19, November.
    2. Shiqi Wang & Zhongyuan Yuan, 2020. "A Hot Water Split-Flow Dual-Pressure Strategy to Improve System Performance for Organic Rankine Cycle," Energies, MDPI, vol. 13(13), pages 1-21, June.
    3. Wang, Xuan & Wang, Rui & Jin, Ming & Shu, Gequn & Tian, Hua & Pan, Jiaying, 2020. "Control of superheat of organic Rankine cycle under transient heat source based on deep reinforcement learning," Applied Energy, Elsevier, vol. 278(C).
    4. Li, Xiaoya & Xu, Bin & Tian, Hua & Shu, Gequn, 2021. "Towards a novel holistic design of organic Rankine cycle (ORC) systems operating under heat source fluctuations and intermittency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    5. Shi, Yao & Zhang, Zhiming & Xie, Lei & Wu, Xialai & Liu, Xueqin Amy & Lu, Shan & Su, Hongye, 2022. "Modified hierarchical strategy for transient performance improvement of the ORC based waste heat recovery system," Energy, Elsevier, vol. 261(PA).
    6. Johannes Petrus Bester & Martin Van Eldik & Philip van Zyl Venter, 2023. "Energy Recovery Maximisation Modelling Subject to Constrained Cooling," Energies, MDPI, vol. 17(1), pages 1-23, December.
    7. Wanming Pan & Junkang Li & Guotao Zhang & Le Zhou & Ming Tu, 2022. "Multi-Objective Optimization of Organic Rankine Cycle (ORC) for Tractor Waste Heat Recovery Based on Particle Swarm Optimization," Energies, MDPI, vol. 15(18), pages 1-24, September.
    8. Qikai Peng & Zhongjie Zhang & Guangmeng Zhou & Surong Dong & Xumin Zhao & Han Zhang & Ruilin Liu & Jun Cai, 2023. "Experimental Study on the Flow Characteristics of Two-Stage Variable Turbines in a Twin-VGT System," Energies, MDPI, vol. 16(23), pages 1-24, December.
    9. Vaupel, Yannic & Huster, Wolfgang R. & Mhamdi, Adel & Mitsos, Alexander, 2021. "Optimal operating policies for organic Rankine cycles for waste heat recovery under transient conditions," Energy, Elsevier, vol. 224(C).
    10. Liao, Gaoliang & E, Jiaqiang & Zhang, Feng & Chen, Jingwei & Leng, Erwei, 2020. "Advanced exergy analysis for Organic Rankine Cycle-based layout to recover waste heat of flue gas," Applied Energy, Elsevier, vol. 266(C).
    11. Pili, R. & Eyerer, S. & Dawo, F. & Wieland, C. & Spliethoff, H., 2020. "Development of a non-linear state estimator for advanced control of an ORC test rig for geothermal application," Renewable Energy, Elsevier, vol. 161(C), pages 676-690.
    12. Imran, Muhammad & Pili, Roberto & Usman, Muhammad & Haglind, Fredrik, 2020. "Dynamic modeling and control strategies of organic Rankine cycle systems: Methods and challenges," Applied Energy, Elsevier, vol. 276(C).
    13. Gu, Zhengzhao & Feng, Kewen & Ge, Lei & Quan, Long, 2023. "Dynamic modeling and optimization of organic Rankine cycle in the waste heat recovery of the hydraulic system," Energy, Elsevier, vol. 263(PB).

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