基于风速时空关联的多步预测方法

doi:10.19912/j.0254-0096.tynxb.2020-0410

太阳能学报 ›› 2022, Vol. 43 ›› Issue (2): 458-464.DOI: 10.19912/j.0254-0096.tynxb.2020-0410

基于风速时空关联的多步预测方法

潘超¹, 李润宇¹, 王典¹, 蔡国伟¹, 张友会²

1.现代电力系统仿真控制与绿色电能新技术教育部重点实验室（东北电力大学）, 吉林 132012;
2.松花江水力发电有限公司吉林白山发电厂,吉林 132400

收稿日期:2020-05-08 出版日期:2022-02-28 发布日期:2022-08-28
通讯作者: 潘超（1981—）,男,博士、副教授,主要从事电力系统稳定与电磁兼容方面的研究。31563018@qq.com
基金资助:
国家重点研发计划专项（2016YFB0900100）

MULTI-STEP WIND SPEED PREDICTION METHOD BASED ON WIND SPEED SPATIAL-TIME CORRELATION

Pan Chao¹, Li Runyu¹, Wang Dian¹, Cai Guowei¹, Zhang Yonghui²

1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education, Northeast Electric Power University, Jilin 132012, China;
2. Songhuajiang Hydropower Co., Ltd., Jilin Baishan Power Plant, Jilin 132400, China

Received:2020-05-08 Online:2022-02-28 Published:2022-08-28

摘要/Abstract

摘要： 基于风速的空间关联性提出一种新的多位置多步风速组合预测方法。对风场内各风力机进行灰色关联分析,并据此利用昆虫优化算法进行优选重构,获取目标风力机及临近域空间信息。利用卷积神经网络对重构矩阵进行空间特征提取,并输入长短时记忆网络进行多步预测。最后,将所提方法应用于不同风场进行风速预测,通过对比分析验证所提方法的预测精度和泛化能力。

关键词: 多步风速预测, 灰色关联分析, 长短时记忆网络, 卷积神经网络, 时空关联

Abstract: Ultra-short-term prediction for considering the spatial correlation of wind speed is a research hotspot for large-scale wind power grid connection. This paper proposes a new multi-position and multi-step combined wind speed prediction method based on the spatial correlation of wind speed. The grey correlation analysis on each wind turbine in the wind farm is carried out, and then the pity beetle algorithm is adopted to perform optimal and reconstruct to obtain the target wind turbine and its adjacent space information. The convolutional neural network is used to extract the spatial features of the reconstructed matrix, which are input the long-short-term memory networks for multi-step prediction. Finally, the method in this paper is applied to different wind farms for wind speed prediction. The prediction accuracy and generalization ability of the proposed method are verified through comparative analysis.

Key words: multi-step wind speed prediction, grey correlation analysis, long-short-term memory networks, convolutional neural network, spatial-temporal correlation

中图分类号:

TM721

潘超, 李润宇, 王典, 蔡国伟, 张友会. 基于风速时空关联的多步预测方法[J]. 太阳能学报, 2022, 43(2): 458-464.

Pan Chao, Li Runyu, Wang Dian, Cai Guowei, Zhang Yonghui. MULTI-STEP WIND SPEED PREDICTION METHOD BASED ON WIND SPEED SPATIAL-TIME CORRELATION[J]. Acta Energiae Solaris Sinica, 2022, 43(2): 458-464.

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基于风速时空关联的多步预测方法

MULTI-STEP WIND SPEED PREDICTION METHOD BASED ON WIND SPEED SPATIAL-TIME CORRELATION

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