Abstract
In view of the shortcomings of traditional wind farms, this paper proposes a more efficient and accurate method of grouping and model-turbine selection. The wake effect is fully considered in this method. The Gauss wake model and the sum of squares wake superposition model are combined to solve the problem under the target of maximum wind power. The location relationship and power consistency of the wind turbine(WT) are selected as the clustering index to group the WTs and select the model-turbines. For clustering algorithm, SOM and spectral clustering are compared, and SOM algorithm with better clustering effect is selected.
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Wu, R., Yang, W., Mo, R., Wei, S. (2022). Wind Turbines Grouping and Model-Turbine Selection Method for Offshore Wind Farms Considering Wake Effect. In: Jia, Y., Zhang, W., Fu, Y., Yu, Z., Zheng, S. (eds) Proceedings of 2021 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 804. Springer, Singapore. https://doi.org/10.1007/978-981-16-6324-6_58
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DOI: https://doi.org/10.1007/978-981-16-6324-6_58
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