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Variational Control Approach to Energy Extraction from a Fluid Flow

Author

Listed:
  • Gianluca Pepe

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00164 Rome, Italy)

  • Federica Mezzani

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00164 Rome, Italy)

  • Antonio Carcaterra

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00164 Rome, Italy)

  • Luca Cedola

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00164 Rome, Italy)

  • Franco Rispoli

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 18, 00164 Rome, Italy)

Abstract

Energy harvesting from the environment is an important aspect of many technologies. The scale of energy capturing and storage can involve the power range from mWatt up to MWatt, depending on the used devices and the considered environments (from ambient acoustic and vibration to ocean wave motion, or wind). In this paper, the wind turbine energy harvesting problem is approached as an optimal control problem, where the objective function is the absorption of an amount of energy in a given time interval by a fluid-flow environment, that should be maximized. The interest relies on outlining general control models of fluid-flow-based extraction plants and identifying an optimum strategy for the regulation of an electrical machine to obtain a maximum-efficiency process for the related energy storage. The mathematical tools are found in the light of optimal control theory, where solutions to the fundamental equations are in the frame of Variational Control (the basis of the Pontryagin optimal control theory). A special problem, named Optimally Controlled Betz’s Machine OCBM-optimal control steady wind turbine, is solved in closed form, and it is shown that, in the simpler steady case, it reproduces the maximum efficiency machine developed in Betz’s theory.

Suggested Citation

  • Gianluca Pepe & Federica Mezzani & Antonio Carcaterra & Luca Cedola & Franco Rispoli, 2020. "Variational Control Approach to Energy Extraction from a Fluid Flow," Energies, MDPI, vol. 13(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4913-:d:415990
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    References listed on IDEAS

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    1. Lin, Zhongwei & Chen, Zhenyu & Wu, Qiuwei & Yang, Shuo & Meng, Hongmin, 2018. "Coordinated pitch & torque control of large-scale wind turbine based on Pareto efficiency analysis," Energy, Elsevier, vol. 147(C), pages 812-825.
    2. Koh, J.H. & Ng, E.Y.K., 2016. "Downwind offshore wind turbines: Opportunities, trends and technical challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 797-808.
    3. Wakui, Tetsuya & Yoshimura, Motoki & Yokoyama, Ryohei, 2017. "Multiple-feedback control of power output and platform pitching motion for a floating offshore wind turbine-generator system," Energy, Elsevier, vol. 141(C), pages 563-578.
    4. Song, Dongran & Yang, Jian & Dong, Mi & Joo, Young Hoon, 2017. "Model predictive control with finite control set for variable-speed wind turbines," Energy, Elsevier, vol. 126(C), pages 564-572.
    5. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    6. Serri, Laura & Lembo, Ettore & Airoldi, Davide & Gelli, Camilla & Beccarello, Massimo, 2018. "Wind energy plants repowering potential in Italy: technical-economic assessment," Renewable Energy, Elsevier, vol. 115(C), pages 382-390.
    7. Akram, Umer & Nadarajah, Mithulananthan & Shah, Rakibuzzaman & Milano, Federico, 2020. "A review on rapid responsive energy storage technologies for frequency regulation in modern power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
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