Dr Ruiyang He

(e/fe)

BEng, MSc, PhD

2026

• Li, K. et al., 2026. Advanced wind-cooling coordination by tensor train based higher order dynamic mode decomposition. Renewable Energy 275 126262. (10.1016/j.renene.2026.126262)
• Zheng, S. et al., 2026. An incentive-based integrated demand response model considering value-action gap. Presented at: 2026 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia) Kunming, China 11-14 July 2026. 2026 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia). IEEE. , pp.2040-2049. (10.1109/icpsasia70813.2026.11692127)
• Tao, S. et al., 2026. Active yaw control strategy for a hybrid offshore wind farm under typical wind conditions. Renewable Energy 259 125122. (10.1016/j.renene.2025.125122)
• He, G. , Sun, H. and He, R. 2026. A novel analytical wake model for floating offshore wind turbines with pitch motion effects. Renewable Energy 256 (Part D) 124090. (10.1016/j.renene.2025.124090)

2025

• Tao, S. et al., 2025. A two-stage optimization model for floating offshore wind farm layout and control. Renewable Energy 253 123614. (10.1016/j.renene.2025.123614)
• Chen, J. et al., 2025. Prediction of wind farm wake and output power using generative adversarial network and convolutional neural network. Physics of Fluids 37 (8) 085255. (10.1063/5.0284856)
• Tu, Y. et al., 2025. A multi-fidelity framework for power prediction of wind farm under yaw misalignment. Applied Energy 377 (C) 124600. (10.1016/j.apenergy.2024.124600)

2024

• He, R. et al. 2024. Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms. Renewable Energy 225 120324. (10.1016/j.renene.2024.120324)
• Zhang, S. et al., 2024. Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy. Energy 294 130843. (10.1016/j.energy.2024.130843)

2023

• He, R. , Yang, H. and Lu, L. 2023. Optimal yaw strategy and fatigue analysis of wind turbines under the combined effects of wake and yaw control. Applied Energy 337 120878. (10.1016/j.apenergy.2023.120878)

2022

• He, R. et al. 2022. A machine learning-based fatigue loads and power prediction method for wind turbines under yaw control. Applied Energy 326 120013. (10.1016/j.apenergy.2022.120013)
• He, R. et al. 2022. Wind tunnel tests for wind turbines: a state-of-the-art review. Renewable and Sustainable Energy Reviews 166 112675. (10.1016/j.rser.2022.112675)

2021

• He, R. et al. 2021. A novel three-dimensional wake model based on anisotropic Gaussian distribution for wind turbine wakes. Applied Energy 296 117059. (10.1016/j.apenergy.2021.117059)

2020

• Zhang, L. et al., 2020. A review of rotating stall in vaneless diffuser of centrifugal compressor. Journal of Thermal Science 29 (2), pp.323-342. (10.1007/s11630-020-1261-y)

2019

• Zhang, L. et al., 2019. Study on static and dynamic characteristics of an axial fan with abnormal blade under rotating stall conditions. Energy 170 , pp.305-325. (10.1016/j.energy.2018.12.125)

2017

• Zhang, L. et al., 2017. Numerical study on the acoustic characteristics of a axial fan under rotating stall condition. Energies 10 (12) 1945. (10.3390/en10121945)