现代电子技术2024，Vol.47Issue(17)：153-158,6.DOI:10.16652/j.issn.1004-373x.2024.17.025
基于相似日与加权马尔可夫模型的风力发电功率区间预测
Wind power interval prediction based on similar day and weighted Markov model
摘要
Abstract
A wind power interval prediction method based on the similar day and weighted Markov model(SWMQ)is proposed to improve the wind power prediction.The wind power data is related to wind speed data directly.The abnormal and missing values in the data are preprocessed by the boxplot method and correlation filling method,so as to improve the data correlation.The wind speed is predicted by convolutional neural network(CNN).And then,the predicted wind speed data is used to find out the similar day in the historical data with the method of Pearson correlation coefficient(PCC),and the power data of the similar day is used as the data set for weighted Markov model prediction.The prediction interval is obtained by the principle of quantile regression.The CNN-based model,the model based on correlation filling and CNN,and the weighted Markov model are established.The simulation and comparison of the data of a wind farm in northwest China show that the proposed model is more accurate in wind power prediction,and can better reflect the threshold of data change.关键词
风电功率/卷积神经网络/加权马尔可夫模型/相似日分析/区间预测/分位数回归Key words
wind power/CNN/weighted Markov model/similar day analysis/interval forecasting/quantile regression分类
信息技术与安全科学引用本文复制引用
张志瑞,陈磊,蔡坤哲,张怡..基于相似日与加权马尔可夫模型的风力发电功率区间预测[J].现代电子技术,2024,47(17):153-158,6.基金项目
国家重点研发计划项目(国际合作专项)(2021YFE0190900) （国际合作专项）
教育部产学合作协同育人2023年项目(230802495182120) （230802495182120）
2022年省级研究生示范课程《科技论文写作》立项建设项目(KCJSX2022063) （KCJSX2022063）
