发电技术2024，Vol.45Issue(2)：299-311,13.DOI:10.12096/j.2096-4528.pgt.23017
一种二模态天气分型方法及其在光伏功率概率预测的应用
A Two-Modal Weather Classification Method and Its Application in Photovoltaic Power Probability Prediction
摘要
Abstract
Weather classification is an indispensable preprocessing step in photovoltaic power prediction.A new photovoltaic power clustering based two-modal weather classification method was proposed to finely depict the uncertainty of photovoltaic power.Both photovoltaic power data and meteorological data were considered for weather classification,which provided a novel and effective path for weather classification based photovoltaic power prediction.In addition,data fusion technology was used to mine relevant information between numeric weather prediction(NWP)data and measured meteorological data to help for weather classification,so as to reduce the model reliance on the accuracy of forecasted meteorological indicators as well as improve the robustness of the model.In experiments based on the data of a photovoltaic power station in Jilin,the rationality of the weather classification method was demonstrated.The photovoltaic power probability prediction combined with the proposed weather classifier resulted in the prediction interval coverage probability closer to the preassigned confidence level,and a narrower mean prediction interval width.关键词
光伏发电/天气分型/光伏功率概率预测/时间序列K均值聚类/多模态学习/不确定性Key words
photovoltaic power generation/weather classification/photovoltaic power probability prediction/time series K-means clustering/multi-modal learning/uncertainty分类
能源科技引用本文复制引用
付小标,李德鑫,侯嘉琪,李宝聚,温亚坤,赖晓文,郭雷,王志伟,王尧,张海锋..一种二模态天气分型方法及其在光伏功率概率预测的应用[J].发电技术,2024,45(2):299-311,13.基金项目
国网吉林省电力有限公司揭榜挂帅项目(2021JBGS-09). Project Supported by Science and Technology Project Selected by the Open Competition Mechanism of State Grid Jilinsheng Electric Power Supply Company(2021JBGS-09). （2021JBGS-09）
