Day-ahead wind power prediction method and system for wind power plant

• Main Authors: GAO JING, ZHANG MINGLI, JI XING, LI HUA, WANG ZONGYUAN, SHANG WENYING, LIU KAI, LI JINQI, YANG FANGYUAN, LYU XUMING, XU XILIN, PAN XIAO, HUANG NANTIAN, HOU YIXIN, YANG BO, YANG SHUO, MAN LINKUN, SONG ZHUORAN, ZHANG NA, CHENG MENGZENG, ZHAO LIN, LIU YUTONG, YANG HAIFENG
• Format: Patent
• Language: Chinese; English
• Published: 08.02.2022
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a day-ahead wind power prediction method and system for a wind power plant, and belongs to the technical field of wind power generation, and the method comprises the steps: constructing an original data set according to the wind power of a to-be-predicted day, the numerical weather forecast meteorological characteristics, and the correlation of the wind power of a historical day; removing to-be-predicted daily wind power in the original data set, obtaining a clustering data set, carrying out k-means clustering, obtaining an original data set with cluster labels, generating a confrontation network according to robustness auxiliary classification, and generating massive scenes with labels; determining a cluster label category of a to-be-predicted day according to the known historical day wind power and numerical weather forecast meteorological characteristics, and screening out a plurality of scenes with high similarity with the to-be-predicted day wind power according to the cluster lab