电子科技2025，Vol.38Issue(8)：79-86,8.DOI:10.16180/j.cnki.issn1007-7820.2025.08.011
基于相似天气波动分型的短期光伏发电功率预测
Short-Term Photovoltaic Power Generation Forecasting Based on Similar Weather Fluctuation Patterns
摘要
Abstract
In view of the problem that photovoltaic power output is greatly affected by weather fluctuations and the distribution of weather input features is scattered resulting in low prediction accuracy,this study proposes a short-term photovoltaic power prediction model considering similar weather fluctuation fractals.Strongly correlated weather factors are screened as input data through correlation analysis.Multi-dimensional weather features are aggregated into one-dimensional comprehensive weather data using principal component analysis,and the fluctuation features of the comprehensive weather data are used to represent the fluctuation features of most of the weather data.To make the fluctuation characteristics after clustering more concentrated,five statistical indicators of the comprehensive weather data were used as the clustering features of the K-means clustering algorithm to typify the weather data.A BiGRU(Bidirectional Gated Recurrent Unit)-Attention prediction model based on two-channel CNN(Convolutional Neural Networks)is used to predict the photovoltaic power generation data under three weather types.Compared with the traditional algorithm,the accuracy of the proposed prediction method is higher,which verifies the effectiveness of the proposed method and model.关键词
光伏发电/天气分型/相关性分析/主成分分析/卷积神经/统计指标/K-means聚类/BiGRU-ATT模型Key words
photovoltaic power/weather typing/correlation analysis/principal component analysis/convolutional neural/statistical indicators/K-means clustering/BiGRU-ATT model分类
信息技术与安全科学引用本文复制引用
王林,王林先,李伟硕,王涛,雒志恒,朱家君..基于相似天气波动分型的短期光伏发电功率预测[J].电子科技,2025,38(8):79-86,8.基金项目
山东省科技型中小企业创新能力提升工程(2023TSGC0213) Shandong Province Science and Technology-Based Small and Medium-Sized Enterprises Innovation Capacity Enhancement Project(2023TSGC0213) （2023TSGC0213）
