Ravelijn

dr. H. Chen (Hao)

Assistant Professor
BMS-HBE-IEBIS
Ravelijn 4402
h.chen-3@utwente.nl
+31534897784
Business card

I work as an assistant professor in AI and sustainable industries. My current research interest is how to innovatively develop and deploy emerging AI technologies for the unique physical principles and economic mechanisms of sustainable industries, especially for future energy and environment systems, to combat climate change.

I am also passionate about popularizing emerging science and how to advance engineering education. I am proud of my classical Oriental cultural background. I am easygoing and like parties, outdoor activities, playing tennis, classical music, painting, and calligraphy.

Welcome to all PhD, MSc and undergraduate students looking for supervision and collaboration.

Expertise

  • Computer Science

    • Models
    • Machine Learning

  • Earth and Planetary Sciences

    • Model
    • Prediction
    • Wind
    • Wind Velocity
    • Wind Power
    • Weather Condition

Organisations

Data-driven study of techno and/or economic in new industries and optimisation of engineering processes.

Publications

2024

Cost-Efficient Vehicular Edge Computing Deployment for Mobile Air Pollution Monitoring (2024)In 2024 IEEE Wireless Communications and Networking Conference, WCNC 2024 - Proceedings (IEEE Wireless Communications and Networking Conference, WCNC). IEEE. Zhang, Q., Chen, H. & Ha, P. H.https://doi.org/10.1109/WCNC57260.2024.10570558A novel wind model downscaling with statistical regression and forecast for the cleaner energy (2024)Journal of cleaner production, 434. Article 140217. Chen, H.https://doi.org/10.1016/j.jclepro.2023.140217Scenario Generation by Physical Model-Free Approaches for Multiple Renewables (2024)Journal of physics: Conference series, 2754(1). Article 012003. Chen, H., Jin, A., Zhao, W., Yi, H. & Zhang, Q.https://doi.org/10.1088/1742-6596/2754/1/012003

2023

A Control Strategy for Electromagnetic Transient in Renewable Energy Systems Based on Virtual Synchronous Generation (2023)In 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). IEEE. Chen, H. & Zhang, Q.https://doi.org/10.1109/ICECCME57830.2023.10252542A southern, middle, and northern Norwegian offshore wind energy resources analysis by a transfer learning method for Energy Internet (2023)Journal of physics: Conference series, 2655(1). Article 012011. Chen, H., Birkelund, Y., Ricaud, B. & Zhang, Q.https://doi.org/10.1088/1742-6596/2655/1/012011Data science in wind energy: A case study for Norwegian offshore wind (2023)Journal of physics: Conference series, 2638(1). Article 012013. Chen, H., Birkelund, Y. & Zhang, Q.https://doi.org/10.1088/1742-6596/2638/1/012013

2022

A comprehensive statistical analysis for residuals of wind speed and direction from numerical weather prediction for wind energy (2022)Energy Reports, 8(Suppl. 9), 618-626. Chen, H.https://doi.org/10.1016/j.egyr.2022.07.080Machine learning forecasts of Scandinavian numerical weather prediction wind model residuals with control theory for wind energy (2022)Energy Reports, 8(Suppl. 13), 661-668. Chen, H., Zhang, Q. & Birkelund, Y.https://doi.org/10.1016/j.egyr.2022.08.105Noise-intensification data augmented machine learning for day-ahead wind power forecast (2022)Energy Reports, 8(Suppl. 10), 916-922. Chen, H., Birkelund, Y., Batalden, B. M. & Barabadi, A.https://doi.org/10.1016/j.egyr.2022.05.265Cluster-based ensemble learning for wind power modeling from meteorological wind data (2022)Renewable & sustainable energy reviews, 167. Article 112652. Chen, H.https://doi.org/10.1016/j.rser.2022.112652

Research profiles

Address

University of Twente

Ravelijn (building no. 10), room 4402
Hallenweg 17
7522 NH Enschede
Netherlands

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Organisations

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