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A Wind Power Prediction Framework for Distributed Power Grids

Bin Chen1, Ziyang Li1, Shipeng Li1, Qingzhou Zhao1, Xingdou Liu2,*

1 Power Grid Design Institute, Shandong Electric Power Engineering Consulting Institute Co., Ltd., Jinan, 250013, China
2 School of Electrical Engineering, Shandong University, Jinan, 250012, China

* Corresponding Author: Xingdou Liu. Email: email

Energy Engineering 2024, 121(5), 1291-1307.


To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve, and historical power is reconstructed using variational mode decomposition (VMD) filtering to form input variables in chronological order. Finally, input variables of a single turbine enter the temporal convolutional network (TCN) to complete initial feature extraction, and then integrate the outputs of all TCN layers using Long Short Term Memory Networks (LSTM) to obtain power prediction sequences for all turbine positions. The proposed method was tested on a wind farm connected to a distributed power grid, and the results showed it to be superior to existing typical methods.


Cite This Article

APA Style
Chen, B., Li, Z., Li, S., Zhao, Q., Liu, X. (2024). A wind power prediction framework for distributed power grids. Energy Engineering, 121(5), 1291-1307.
Vancouver Style
Chen B, Li Z, Li S, Zhao Q, Liu X. A wind power prediction framework for distributed power grids. Energ Eng. 2024;121(5):1291-1307
IEEE Style
B. Chen, Z. Li, S. Li, Q. Zhao, and X. Liu "A Wind Power Prediction Framework for Distributed Power Grids," Energ. Eng., vol. 121, no. 5, pp. 1291-1307. 2024.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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