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Wind turbine power curve modeling using radial basis function neural networks and tabu search

Citations

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Cited by:

  1. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  2. Sara Carcangiu & Alessandra Fanni & Augusto Montisci, 2022. "Optimal Design of an Inductive MHD Electric Generator," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
  3. Hanafi, Saïd & Wang, Yang & Glover, Fred & Yang, Wei & Hennig, Rick, 2023. "Tabu search exploiting local optimality in binary optimization," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1037-1055.
  4. Wenguang Chai & Liangguang Zhang & Zhizhe Lin & Jinglin Zhou & Teng Zhou, 2023. "GSA-KELM-KF: A Hybrid Model for Short-Term Traffic Flow Forecasting," Mathematics, MDPI, vol. 12(1), pages 1-16, December.
  5. Qian, Guo-Wei & Ishihara, Takeshi, 2022. "A novel probabilistic power curve model to predict the power production and its uncertainty for a wind farm over complex terrain," Energy, Elsevier, vol. 261(PA).
  6. Li, Tenghui & Liu, Xiaolei & Lin, Zi & Morrison, Rory, 2022. "Ensemble offshore Wind Turbine Power Curve modelling – An integration of Isolation Forest, fast Radial Basis Function Neural Network, and metaheuristic algorithm," Energy, Elsevier, vol. 239(PD).
  7. Cheng, Biyi & Yao, Yingxue, 2023. "Machine learning based surrogate model to analyze wind tunnel experiment data of Darrieus wind turbines," Energy, Elsevier, vol. 278(PA).
  8. Cheng, Biyi & Du, Jianjun & Yao, Yingxue, 2022. "Machine learning methods to assist structure design and optimization of Dual Darrieus Wind Turbines," Energy, Elsevier, vol. 244(PA).
  9. Zou, Runmin & Yang, Jiaxin & Wang, Yun & Liu, Fang & Essaaidi, Mohamed & Srinivasan, Dipti, 2021. "Wind turbine power curve modeling using an asymmetric error characteristic-based loss function and a hybrid intelligent optimizer," Applied Energy, Elsevier, vol. 304(C).
  10. Hu, Yue & Liu, Hanjing & Wu, Senzhen & Zhao, Yuan & Wang, Zhijin & Liu, Xiufeng, 2024. "Temporal collaborative attention for wind power forecasting," Applied Energy, Elsevier, vol. 357(C).
  11. Zhang, Juntao & Cheng, Chuntian & Yu, Shen, 2024. "Recognizing the mapping relationship between wind power output and meteorological information at a province level by coupling GIS and CNN technologies," Applied Energy, Elsevier, vol. 360(C).
  12. Qiao, Yanhui & Han, Shuang & Zhang, Yajie & Liu, Yongqian & Yan, Jie, 2024. "A multivariable wind turbine power curve modeling method considering segment control differences and short-time self-dependence," Renewable Energy, Elsevier, vol. 222(C).
  13. Saeedreza Jadidi & Hamed Badihi & Youmin Zhang, 2021. "Fault-Tolerant Cooperative Control of Large-Scale Wind Farms and Wind Farm Clusters," Energies, MDPI, vol. 14(21), pages 1-29, November.
  14. Davide Astolfi & Ravi Pandit & Andrea Lombardi & Ludovico Terzi, 2022. "Multivariate Data-Driven Models for Wind Turbine Power Curves including Sub-Component Temperatures," Energies, MDPI, vol. 16(1), pages 1-18, December.
  15. P Kannan & M Sivakumar & R Ruban Raja, 2025. "Optimal sizing and optimization of financial cost for EVs using SPOA-RBFNN technique," Energy & Environment, , vol. 36(7), pages 3438-3462, November.
  16. James Roetzer & Xingjie Li & John Hall, 2024. "Review of Data-Driven Models in Wind Energy: Demonstration of Blade Twist Optimization Based on Aerodynamic Loads," Energies, MDPI, vol. 17(16), pages 1-20, August.
  17. Wang, Shun & Vidal, Yolanda & Pozo, Francesc, 2026. "Recent advances in wind turbine condition monitoring using SCADA data: A state-of-the-art review," Reliability Engineering and System Safety, Elsevier, vol. 267(PA).
  18. Pengfei Zhang & Zuoxia Xing & Shanshan Guo & Mingyang Chen & Qingqi Zhao, 2022. "A New Wind Turbine Power Performance Assessment Approach: SCADA to Power Model Based with Regression-Kriging," Energies, MDPI, vol. 15(13), pages 1-15, July.
  19. Wen-Jie Liu & Yu-Ting Bai & Xue-Bo Jin & Ting-Li Su & Jian-Lei Kong, 2022. "Adaptive Broad Echo State Network for Nonstationary Time Series Forecasting," Mathematics, MDPI, vol. 10(17), pages 1-21, September.
  20. Lin Feng & Jian Wang & Chao Ding, 2021. "Image Edge Detection Algorithm Based on Fuzzy Radial Basis Neural Network," Advances in Mathematical Physics, John Wiley & Sons, vol. 2021(1).
  21. Zhizhe Lin & Dawei Wang & Chuxin Cao & Hai Xie & Teng Zhou & Chunjie Cao, 2025. "GSA-KAN: A Hybrid Model for Short-Term Traffic Forecasting," Mathematics, MDPI, vol. 13(7), pages 1-20, March.
  22. Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
  23. Wang, Peng & Li, Yanting & Zhang, Guangyao, 2023. "Probabilistic power curve estimation based on meteorological factors and density LSTM," Energy, Elsevier, vol. 269(C).
  24. Wen, Yi & Kamranzad, Bahareh & Lin, Pengzhi, 2021. "Assessment of long-term offshore wind energy potential in the south and southeast coasts of China based on a 55-year dataset," Energy, Elsevier, vol. 224(C).
  25. Farah, Shahid & David A, Wood & Humaira, Nisar & Aneela, Zameer & Steffen, Eger, 2022. "Short-term multi-hour ahead country-wide wind power prediction for Germany using gated recurrent unit deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  26. Li, Yanting & Wang, Peng & Wu, Zhenyu & Su, Yan, 2024. "Collaborative monitoring of wind turbine performance based on probabilistic power curve comparison," Renewable Energy, Elsevier, vol. 231(C).
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