中国电机工程学报2024，Vol.44Issue(13)：5196-5207,中插15,13.DOI:10.13334/j.0258-8013.pcsee.230412
基于数据集蒸馏的光伏发电功率超短期预测
Ultra-short-term Prediction of Photovoltaic Power Based on Dataset Distillation
摘要
Abstract
Cloud is the main factor affecting the change of direct solar radiation.Due to the different transmittance of various clouds,the solar radiation of photovoltaic power station will fluctuate accordingly.In order to solve the problems of large fluctuation and large number of prediction models of photovoltaic power generation under various clouds,an ultra-short-term prediction model of photovoltaic power generation based on satellite cloud image and data set distillation is proposed.First,based on the historical cloud image above the station to be measured,the Farneback optical flow method is used to predict the cloud image.Then,the sample library of all kinds of clouds is established according to the satellite cloud classification label data,and the cloud class discriminant map is obtained by training sample library of the data set with distillation algorithm.The predicted cloud image is matched with the cloud class discriminant map to obtain the cloud class aggregation matching feature.Finally,the long short-term memory network model is established by using the above features,cloud cover feature and numerical weather forecast data to predict the ultra-short-term photovoltaic power generation.The results show that the proposed model can accurately describe the characteristics of clouds and effectively improve the prediction accuracy of photovoltaic power.关键词
数据集蒸馏/卫星云图/云分类/光流法/超短期光伏功率预测Key words
dataset distillation/satellite cloud images/cloud classification/optical flow method/ultra-short-term PV power forecast分类
信息技术与安全科学引用本文复制引用
郑珂,王丽婕,郝颖,王勃..基于数据集蒸馏的光伏发电功率超短期预测[J].中国电机工程学报,2024,44(13):5196-5207,中插15,13.基金项目
北京信息科技大学"勤信人才"培育计划(QXTCP C202107). Qin Xin Talents Cultivation Program,Beijing Information Science&Technology University(QXTCP C202107). （QXTCP C202107）
