Effect of ambient temperature variance on power output of wind turbine and mitigation strategy
DOI:
https://doi.org/10.61435/jese.2025.e42Keywords:
Ambient temperature, Parameter correction, Wind turbine, Power generation, PMSGAbstract
Many challenges have been found in the operation of wind turbine under varying weather conditions, which demands novel strategies to address these issues. As far as we know, the variation of weather parameters is crucial for wind turbine operators to monitor the operation of wind turbines and adjust parameters of generator to ensure safe and efficient operation. This study aims to explore the effect of ambient temperature variation on wind turbine parameters including rotational speed, output power and pitch angle, using 10-minute measurement data for temperature ranges from -5oC to +20oC. By understanding such effects, researches can develop a control strategy to minimize their effect and improve the performance of wind turbines by increasing power production and reducing unnecessary loads and control actions. In this research, the mitigation method was developed within the control system to correct the parameters of wind turbine according to ambient temperature variation, offering a more practical strategy for wind turbines that currently in use. The simulation studies were carried out using Matlab/Simulink® software, and the results revealed that the output power of the wind turbine rose by 5.71% compared to standard strategy after mitigation method was implemented.
References
Alizadeh, M., & Kojori, S. S. (2015). Augmenting effectiveness of control loops of a PMSG (permanent magnet synchronous generator) based wind energy conversion system by a virtually adaptive PI (proportional integral) controller. Energy, 91, 610–629. https://doi.org/10.1016/J.ENERGY.2015.08.047
Baskut, O., Ozgener, O., & Ozgener, L. (2010). Effects of meteorological variables on exergetic efficiency of wind turbine power plants. Renewable and Sustainable Energy Reviews, 14(9), 3237–3241. https://doi.org/10.1016/J.RSER.2010.06.002
Dai, J., Liu, D., Wen, L., & Long, X. (2016). Research on power coefficient of wind turbines based on SCADA data. Renewable Energy, 86, 206–215. https://doi.org/10.1016/J.RENENE.2015.08.023
Danook, S. H., Jassim, K. J., & Hussein, A. M. (2019). The impact of humidity on performance of wind turbine. Case Studies in Thermal Engineering, 14, 100456. https://doi.org/10.1016/J.CSITE.2019.100456
Desalegn, B., Gebeyehu, D., & Tamirat, B. (2022). Wind energy conversion technologies and engineering approaches to enhancing wind power generation: A review. Heliyon, 8(11), e11263. https://doi.org/10.1016/J.HELIYON.2022.E11263
Hassoine, M. A., Lahlou, F., Addaim, A., & Madi, A. A. (2022). Improved evaluation of the wind power potential of a large offshore wind farm using four analytical wake models. International Journal of Renewable Energy Development, 11(1), 35–48. https://doi.org/10.14710/ijred.2022.38263
Homola, M. C., Virk, M. S., Wallenius, T., Nicklasson, P. J., & Sundsbø, P. A. (2010). Effect of atmospheric temperature and droplet size variation on ice accretion of wind turbine blades. Journal of Wind Engineering and Industrial Aerodynamics, 98(12), 724–729. https://doi.org/10.1016/J.JWEIA.2010.06.007
James, M., Haldar, S., Varghese, R., Bhattacharya, S., & Pakrashi, V. (2023). Climate change effects on offshore wind turbines. Wind Energy Engineering: A Handbook for Onshore and Offshore Wind Turbines, 413–422. https://doi.org/10.1016/B978-0-323-99353-1.00030-X
Jargalsaikhan, N., Byambaa, S., Krishnan, N., Prabaharan, N., Adewuyi, O. B., & Senjyu, T. (2023). Study on weakening the effect of air density changes for increased power capture of individual wind energy conversion system. 5th International Conference on Energy, Power and Environment: Towards Flexible Green Energy Technologies (ICEPE, pp.1–5. https://doi.org/10.1109/ICEPE57949.2023.10201566
Jargalsaikhan, N., Masrur, H., Iqbal, A., Rangarajan, S. S., Byambaa, S., & Senjyu, T. (2022). A control algorithm to increase the efficient operation of wind energy conversion systems under extreme wind conditions. Energy Reports, 8, 11429–11439. https://doi.org/10.1016/J.EGYR.2022.08.243
Larsen, G. C., & Hansen, K. S. (2008). Rational Calibration of Four IEC 61400-1 Extreme External Conditions. Wind Energy, 11(6), 685-702. https://doi.org/10.1002/we.302
Li, Y., Liang, X., Cai, A., Zhang, L., Lin, W., & Ge, M. (2023). Effects of Blade Extension on Power Production and Ultimate Loads of Wind Turbines. Applied Sciences, 13(6), 3538. https://doi.org/10.3390/app13063538
Liu, J., Meng, H., Hu, Y., Lin, Z., & Wang, W. (2015). A novel MPPT method for enhancing energy conversion efficiency taking power smoothing into account. Energy Conversion and Management, 101, 738–748. https://doi.org/10.1016/J.ENCONMAN.2015.06.005
Nasiri, M., Milimonfared, J., & Fathi, S. H. (2014). Modeling, analysis and comparison of TSR and OTC methods for MPPT and power smoothing in permanent magnet synchronous generator-based wind turbines. Energy Conversion and Management, 86, 892–900. https://doi.org/10.1016/J.ENCONMAN.2014.06.055
Rodríguez-López, M. Á., Cerdá, E., & Rio, P. d. (2020). Modeling Wind-Turbine Power Curves: Effects of Environmental Temperature on Wind Energy Generation. Energies, 13(18), 4941. https://doi.org/10.3390/en13184941
Şahin, Mustafa & Farsadi, Touraj. (2023). The impacts of atmospheric icing on performance and behavior of a controlled large-scale wind turbine. Journal of Renewable and Sustainable Energy. 15. 24. 10.1063/5.0161724.
Sang, L. Q., Maeda, T., Kamada, Y., & Li, Q. (2017). Experiment and simulation effects of cyclic pitch control on performance of horizontal axis wind turbine. International Journal of Renewable Energy Development, 6(2), 119–125. https://doi.org/10.14710/ijred.6.2.119-125
Song, D., Liu, J., Yang, J., Su, M., Yang, S., Yang, X., & Joo, Y. H. (2019). Multi-objective energy-cost design optimization for the variable-speed wind turbine at high-altitude sites. Energy Conversion and Management, 196, 513–524. https://doi.org/10.1016/J.ENCONMAN.2019.06.039
Takahashi, K., Jargalsaikhan, N., Rangarajan, S., Hemeida, A. M., Takahashi, H., & Senjyu, T. (2020). Output Control of Three-Axis PMSG Wind Turbine Considering Torsional Vibration Using H Infinity Control. Energies, 13(13), 3474. https://doi.org/10.3390/en13133474
Tian, Q., Huang, G., Hu, K., & Niyogi, D. (2019). Observed and global climate model based changes in wind power potential over the Northern Hemisphere during 1979–2016. Energy, 167, 1224–1235. https://doi.org/10.1016/J.ENERGY.2018.11.027
Van den Berg, G.P. (2008), Wind turbine power and sound in relation to atmospheric stability. Wind Energ., 11: 151-169. https://doi.org/10.1002/we.240
Xu, Z., Zhang, T., Li, X., & Li, Y. (2023). Effects of ambient temperature and wind speed on icing characteristics and anti-icing energy demand of a blade airfoil for wind turbine. Renewable Energy, 217, 119135. https://doi.org/10.1016/J.RENENE.2023.119135
Yang, W., Court, R., & Jiang, J. (2013). Wind turbine condition monitoring by the approach of SCADA data analysis. Renewable Energy, 53, 365–376. https://doi.org/10.1016/J.RENENE.2012.11.030
Downloads
Submitted
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Nyam Jargalsaikhan, Sergelen Byambaa, Baigali Erdenebat, Nomuulin Batjargal, Munkhjargal Sukhbaatar

This work is licensed under a Creative Commons Attribution 4.0 International License.
Journal of Emerging Science and Engineering published under the terms of a Creative Commons Attribution 4.0 International License / CC BY 4.0 This license permits anyone to copy and redistribute this material in any form or format, compose, modify, and make derivative works of this material for any purpose, including commercial purposes, so long as they include credit to the Authors of the original work.











