Design and Application of Centralized Power Forecasting System for Regional Wind Farm Cluster

Jie YAN; Yongrui ZHANG; Hao ZHANG

doi:10.16513/j.2096-2185.DE.2207104

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Distributed Energy ›› 2022, Vol. 7 ›› Issue (1) : 28-36. DOI: 10.16513/j.2096-2185.DE.2207104

Basic Research

Design and Application of Centralized Power Forecasting System for Regional Wind Farm Cluster

Jie YAN ¹^,² ,
Yongrui ZHANG ¹^,² ,
Hao ZHANG ¹^,²

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Wind power forecasting system mostly follows the development mode of "one wind farm, one forecasting system" , in which one wind farm is equipped with one set of forecasting system. In this mode, the data of adjacent wind farms within the region cannot be aggregated, the prediction model cannot fully consider the spatio-temporal dependence between the stations to improve the prediction accuracy, and a large number of independent prediction systems cannot be maintained uniformly and efficiently. Therefore, a regional wind farm cluster Chinese power prediction system is proposed. Firstly, multi-source numerical weather forecast data are introduced as the input of the model. Then, the data of fan level and station level are cleaned in the prediction system. Finally, the spatio-temporal combined prediction model of wind farm group is designed in the prediction system. The model can capture the temporal and spatial dependence of wind farms in the region and provide short-term and ultra-short-term prediction results for all wind farms in the region simultaneously. The designed system is referenced in the regional wind power centralized control center of the wind farm group composed of 10 wind farms. The online operation results show that the prediction system meets the requirements of regional power grid evaluation. The 10 wind farms rank top in the evaluation, and the prediction assessment turns from loss to profit during the operation period.

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wind power / centralized power prediction / spatio-temporal prediction / system design

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Jie YAN , Yongrui ZHANG , Hao ZHANG. Design and Application of Centralized Power Forecasting System for Regional Wind Farm Cluster[J]. Distributed Energy Resources. 2022, 7(1): 28-36 https://doi.org/10.16513/j.2096-2185.DE.2207104

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