高电压技术2023，Vol.49Issue(7)：2972-2982,11.DOI:10.13336/j.1003-6520.hve.20221331
基于多场景敏感气象因子优选及小样本学习与扩充的转折性天气日前风电功率预测
Transitional-weather-considered Day-ahead Wind Power Forecasting Based on Multi-scene Sensitive Meteorological Factor Optimization and Few-shot Learning
摘要
关键词
转折性天气/敏感气象因子/小样本学习/生成对抗网络/长短期记忆网络/日前风电功率预测Key words
transitional weather/sensitive meteorological factor/few-shot learning/generative adversarial networks/long-short term memory network/day-ahead wind power forecast引用本文复制引用
刘雅婷,杨明,于一潇,李梦林,王勃..基于多场景敏感气象因子优选及小样本学习与扩充的转折性天气日前风电功率预测[J].高电压技术,2023,49(7):2972-2982,11.基金项目
国家电网有限公司总部管理科技项目资助(面向转折性 天气的风电功率预测预警技术研究)(4000-202155063A-0-0-00).Project supported by Science and Technology Project of SGCC(Research on Wind Power Forecasting and Early Warning Technology for Transitional Weather)(4000-202155063A-0-0-00). （面向转折性 天气的风电功率预测预警技术研究）
