Associate Professor at China University of Mining and Technology-Beijing, China.
Wenting Zha is a researcher at China University of Mining and Technology-Beijing. His research focuses on machine learning, data analysis, and their applications in energy and power systems.
Professional Profile
scholar
scopus
🎓 Education
– PhD, (no specific information available)
💼 Experience
– Researcher, China University of Mining and Technology-Beijing
🔬 Research Interests
– Machine Learning: deep learning, data analysis
– Energy and Power Systems: wind power prediction, load forecasting, power transmission
🏆 Awards
– No specific information available
📚Top Noted Publications
– A novel wind power prediction method of the lower upper bound evaluation based on GRU 🌬️
– Published in Transactions of the Institute of Measurement and Control, 2024
– 3D Data scattergram image classification based protection for transmission line connecting BESS using depth-wise separable convolution based CNN 🔍
– Published in Journal of Modern Power Systems and Clean Energy, 2024
– Short-term load forecasting method based on secondary decomposition and improved hierarchical clustering 📊
– Published in Results in Engineering, 2024
– An aero-engine remaining useful life prediction model based on feature selection and the improved TCN ✈️
– Published in Franklin Open, 2024
– Semi-supervised learning-based satellite remote sensing object detection method for power transmission towers 📡
– Published in Energy Reports, 2023
– A wind speed vector-wind power curve modeling method based on data denoising algorithm and the improved transformer 🌟
– Published in Electric Power Systems Research, 2023
– Current trajectory image-based protection algorithm for transmission lines connected to MMC-HVDC stations using CA-CNN 🔌
– Published in Protection and Control of Modern Power Systems, 2023
– ENG-BiFPN: A remote sensing object detection model based on grouped deformable convolution for power transmission towers 🌆
– Published in Multimedia Tools and Applications, 2023
– Ultra-short-term power forecast method for the wind farm based on feature selection and temporal convolution network 💨
– Published in ISA Transactions, 2022
– Adaptive mho characteristic-based distance protection for lines emanating from photovoltaic power plants under unbalanced faults
Conclusion
Wenting Zha’s prolific publication record, innovative research, and interdisciplinary approach make him a strong candidate for the Best Researcher Award. By emphasizing collaboration and knowledge translation, he could further strengthen his application and demonstrate his potential for continued excellence in research.