可再生能源2018，Vol.36Issue(2)：236-240,5.
基于KPCA与混合蛙跳算法的并网光伏电站发电量预测模型研究
Study on PV generation power forecasting method based on KPCA and shuffled frog leaping algorithm
摘要
Abstract
A photovoltaic power integrated forecasting method based on hybrid leapfrog algorithm and kernel principal component analysis is Present. The date, time, weather forecast in the clouds and temperature history as input, the photovoltaic power generation system history data and historical weather data as the foundation, and kernel principal component analysis is used to reduce the dimension of input to extract the constituent of primary input,and constitute a historical database, together with the photovoltaic power output to the historical data for training. The comprehensive prediction model is set up, and the relative root mean square error of photovoltaic power is used to evaluate the model. Results show that the proposed method is fast and model prediction accuracy is higher.关键词
发电量预测/核主成分分析/混合蛙跳算法/预测模型Key words
photovoltaic power prediction/kernel principal component analysis/hybrid leapfrog algorithm/predictive model分类
能源科技引用本文复制引用
朱芳..基于KPCA与混合蛙跳算法的并网光伏电站发电量预测模型研究[J].可再生能源,2018,36(2):236-240,5.基金项目
国家自然科学基金项目(5126308) （5126308）
湖北省教育厅创新基金项目(201519632). （201519632）
