科技创新与应用2025，Vol.15Issue(13)：113-117,5.DOI:10.19981/j.CN23-1581/G3.2025.13.026
基于机器学习的风光功率预测系统研究
贺姗姗 1高金兵 1申彦波1
作者信息
- 1. 中国气象局公共气象服务中心,北京 100081||中国气象局能源气象重点开放实验室,北京 100081
- 折叠
摘要
Abstract
With the rapid development of renewable energy technologies,addressing the inherent stochasticity,fluctuations,and intermittency of wind and solar power generation through advanced artificial intelligence has become critical for industry advancement.This study proposes a smart,integrated,and one-stop forecasting system architecture comprising two core modules:a machine learning algorithm management platform for model development and optimization,and a forecasting support service platform for operational decision-making.The system provides end-to-end technical support spanning model training,algorithm selection,scenario-specific services,energy trading assistance,and benefit allocation mechanisms.By enabling nationwide sharing of data resources,optimized algorithms,and cloud platforms,this framework offers a novel solution to enhance prediction accuracy,timeliness,and grid integration efficiency for hybrid renewable energy systems.关键词
机器学习/风电/光伏/功率预测/系统Key words
machine learning/wind power/solar power/power forecasting/system分类
信息技术与安全科学引用本文复制引用
贺姗姗,高金兵,申彦波..基于机器学习的风光功率预测系统研究[J].科技创新与应用,2025,15(13):113-117,5.
