摘要
【目的】使用高质量的历史数据预测未来光伏发电功率,对高效利用太阳能可再生能源、补充电网供电能力和推进节能减碳具有重要意义。【方法】由于光伏时序数据质量参差不齐,本文提出了面向光伏时序数据的缺失值与异常值处理算法,并基于此搭建了分布式光伏功率预测系统。【结果】该系统可以有效处理多种光伏时序数据,并集成了不同时间尺度及不同时长的功率预测模型,可以对多个电站展开光伏功率预测。【结论】该系统能够满足智能电网对辖区内光伏电站功率预测的需求。
[Objective]Using high-quality historical data to predict future photovoltaic(PV)power generation is of great significance for the efficient use of renewable solar energy,supplementing the power supply capacity of the Power Grid,and promoting energy conservation and carbon reduction.[Methods]Due to the uneven quality of PV time series data,this paper proposes an algorithm for processing missing values and outliers of PV time series data,based on which a distributed PV power prediction system is built.[Results]The system can effectively process a variety of PV time series data,integrate power prediction models of different durations and time scales,and predict PV power for multiple power stations.[Conclusions]This system can meet the demands of a smart Power Grid for power forecasting of PV power stations within its jurisdiction.
作者
刘晓艳
王珏
姚铁锤
迟学斌
王晓光
李凯
LIU Xiaoyan;WANG Jue;YAO Tiechui;CHI Xuebin;WANG Xiaoguang;LI Kai(Computer Network Information Center,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《数据与计算发展前沿》
CSCD
2021年第4期140-148,共9页
Frontiers of Data & Computing
基金
科技部重大科技项目(2020AAA0105202)
中国科学院战略性先导科技专项(A类)(No.XDA27000000)。
关键词
时序数据处理
光伏功率预测
分布式光伏系统
系统设计
time series data processing
photovoltaic power prediction
distributed photovoltaic system
system design