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Performance evaluation of the savonius hydrokinetic turbine using soft computing techniques

Author

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  • Khani, Mohammad Sadegh
  • Shahsavani, Younes
  • Mehraein, Mojtaba
  • Kisi, Ozgur

Abstract

Savonius hydrokinetic turbine is a vertical axis turbine suitable for generating electrical power used in rivers and canals. The performance of the turbine is described in terms of power coefficient. The power coefficient (CP) depends on input variables such as aspect ratio, overlap ratio, blockage ratio, number of blades, blade arc angle, blade shape factor, twist angle, Reynolds number, and Tip Speed Ratio (TSR). In this study, different soft computing methods, namely CatBoost, Artificial Neural Network (ANN), Random Forests (RF), Multivariate Adaptive Regression Splines (MARS), Adaptive Neuro-Fuzzy Inference System (ANFIS), ANFIS-Genetic algorithm (ANFIS-GA), ANFIS-Slime Mold Algorithm (ANFIS-SMA), ANFIS-Marine Predators Algorithm (ANFIS-MPA) along with Linear Regression (LR) were used to predict the power coefficient of Savonius hydrokinetic turbines for the first time. In order to obtain appropriate data, experimental tests were conducted in an open water channel for different design configurations of Savonius turbines. Further, more data were collected from different references. These data were used for the training and testing process of the models. The precision of the methods was evaluated using multiple statistical indices. Three different training-testing scenarios were prepared to provide a reliable predictive model, and in all scenarios, the CatBoost method was superior. Sensitive analysis showed that aspect ratio is the most important design parameter among all effective parameters. As a result, the CatBoost is recommended to predict a Savonius hydrokinetic turbine's performance considering multi-input variables.

Suggested Citation

  • Khani, Mohammad Sadegh & Shahsavani, Younes & Mehraein, Mojtaba & Kisi, Ozgur, 2023. "Performance evaluation of the savonius hydrokinetic turbine using soft computing techniques," Renewable Energy, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:renene:v:215:y:2023:i:c:s0960148123008030
    DOI: 10.1016/j.renene.2023.118906
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    References listed on IDEAS

    as
    1. Kerikous, Emeel & Thévenin, Dominique, 2019. "Optimal shape and position of a thick deflector plate in front of a hydraulic Savonius turbine," Energy, Elsevier, vol. 189(C).
    2. Kumar, Anuj & Saini, R.P., 2017. "Performance analysis of a single stage modified Savonius hydrokinetic turbine having twisted blades," Renewable Energy, Elsevier, vol. 113(C), pages 461-478.
    3. Roy, Sukanta & Saha, Ujjwal K., 2013. "Review on the numerical investigations into the design and development of Savonius wind rotors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 73-83.
    4. Jeon, Keum Soo & Jeong, Jun Ik & Pan, Jae-Kyung & Ryu, Ki-Wahn, 2015. "Effects of end plates with various shapes and sizes on helical Savonius wind turbines," Renewable Energy, Elsevier, vol. 79(C), pages 167-176.
    5. Talukdar, Parag K. & Kulkarni, Vinayak & Saha, Ujjwal K., 2018. "Field-testing of model helical-bladed hydrokinetic turbines for small-scale power generation," Renewable Energy, Elsevier, vol. 127(C), pages 158-167.
    6. Golecha, Kailash & Eldho, T.I. & Prabhu, S.V., 2011. "Influence of the deflector plate on the performance of modified Savonius water turbine," Applied Energy, Elsevier, vol. 88(9), pages 3207-3217.
    7. Chong, W.T. & Gwani, M. & Shamshirband, S. & Muzammil, W.K. & Tan, C.J. & Fazlizan, A. & Poh, S.C. & Petković, Dalibor & Wong, K.H., 2016. "Application of adaptive neuro-fuzzy methodology for performance investigation of a power-augmented vertical axis wind turbine," Energy, Elsevier, vol. 102(C), pages 630-636.
    8. Shamshirband, Shahaboddin & Petković, Dalibor & Amini, Amineh & Anuar, Nor Badrul & Nikolić, Vlastimir & Ćojbašić, Žarko & Mat Kiah, Miss Laiha & Gani, Abdullah, 2014. "Support vector regression methodology for wind turbine reaction torque prediction with power-split hydrostatic continuous variable transmission," Energy, Elsevier, vol. 67(C), pages 623-630.
    9. Mauro, S. & Brusca, S. & Lanzafame, R. & Messina, M., 2019. "CFD modeling of a ducted Savonius wind turbine for the evaluation of the blockage effects on rotor performance," Renewable Energy, Elsevier, vol. 141(C), pages 28-39.
    10. Payambarpour, S. Abdolkarim & Najafi, Amir F. & Magagnato, Franco, 2020. "Investigation of deflector geometry and turbine aspect ratio effect on 3D modified in-pipe hydro Savonius turbine: Parametric study," Renewable Energy, Elsevier, vol. 148(C), pages 44-59.
    11. Mohammadi, M. & Lakestani, M. & Mohamed, M.H., 2018. "Intelligent parameter optimization of Savonius rotor using Artificial Neural Network and Genetic Algorithm," Energy, Elsevier, vol. 143(C), pages 56-68.
    12. Rosenberg, Eva & Lind, Arne & Espegren, Kari Aamodt, 2013. "The impact of future energy demand on renewable energy production – Case of Norway," Energy, Elsevier, vol. 61(C), pages 419-431.
    13. Nikolić, Vlastimir & Petković, Dalibor & Shamshirband, Shahaboddin & Ćojbašić, Žarko, 2015. "Adaptive neuro-fuzzy estimation of diffuser effects on wind turbine performance," Energy, Elsevier, vol. 89(C), pages 324-333.
    14. Rostami, Ali Bakhshandeh & Armandei, Mohammadmehdi, 2017. "Renewable energy harvesting by vortex-induced motions: Review and benchmarking of technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 193-214.
    15. Frikha, Sobhi & Driss, Zied & Ayadi, Emna & Masmoudi, Zied & Abid, Mohamed Salah, 2016. "Numerical and experimental characterization of multi-stage Savonius rotors," Energy, Elsevier, vol. 114(C), pages 382-404.
    16. Akwa, João Vicente & Vielmo, Horácio Antonio & Petry, Adriane Prisco, 2012. "A review on the performance of Savonius wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3054-3064.
    17. Petković, Dalibor & Ćojbašič, Žarko & Nikolić, Vlastimir, 2013. "Adaptive neuro-fuzzy approach for wind turbine power coefficient estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 191-195.
    18. Nag, Aditya Kumar & Sarkar, Shibayan, 2018. "Modeling of hybrid energy system for futuristic energy demand of an Indian rural area and their optimal and sensitivity analysis," Renewable Energy, Elsevier, vol. 118(C), pages 477-488.
    19. Kumar, Anuj & Saini, R.P., 2016. "Performance parameters of Savonius type hydrokinetic turbine – A Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 289-310.
    20. Kang, Can & Zhao, Hexiang & Zhang, Yongchao & Ding, Kejin, 2021. "Effects of upstream deflector on flow characteristics and startup performance of a drag-type hydrokinetic rotor," Renewable Energy, Elsevier, vol. 172(C), pages 290-303.
    21. Sun, Haiying & Qiu, Changyu & Lu, Lin & Gao, Xiaoxia & Chen, Jian & Yang, Hongxing, 2020. "Wind turbine power modelling and optimization using artificial neural network with wind field experimental data," Applied Energy, Elsevier, vol. 280(C).
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