Patent number: 12159245
Abstract: A method for predicting a day-ahead wind power of wind farms, comprising: constructing a raw data set based on a correlation between the to-be-predicted daily wind power, the numerical weather forecast meteorological feature and a historical daily wind power; obtaining a clustered data set and performing k-means clustering, obtaining a raw data set with cluster labels, and generating massive labeled scenes based on robust auxiliary classifier generative adversarial networks; determining the cluster label category of the to-be-predicted day based on the known historical daily wind power and numerical weather forecast meteorological feature, and screening out multiple scenes with high similarity to the to-be-predicted daily wind power based on the cluster label category; and obtaining the prediction results of the to-be-predicted daily wind power at a plurality of set times based on an average value, an upper limit value and a lower limit value of the to-be-predicted daily wind power.
Type:
Grant
Filed:
February 26, 2022
Date of Patent:
December 3, 2024
Assignees:
Economic and Technological Research Institute of State Grid Liaoning Electric Power Co., Ltd., State Grid Corporation of China, Northeast Electric Power University
Inventors:
Xiao Pan, Mingli Zhang, Lin Zhao, Na Zhang, Zhuoran Song, Nantian Huang, Jing Gao, Xuming Lv, Hua Li, Mengzeng Cheng, Xing Ji, Wenying Shang, Yixin Hou, Suo Yang, Bo Yang, Yutong Liu, Linkun Man, Xilin Xu, Haifeng Yang, Fangyuan Yang, Kai Liu, Jinqi Li, Zongyuan Wang