摘要
非平稳性是影响风电功率序列和光伏功率序列精准预测的主要问题。信号分解技术能够将非平稳功率序列分解为若干不同频率的固有模态分量,从而平缓序列的波动程度,提取序列特征,建立具有强适应性的预测模型,实现预测精确度的切实提高。首先将信号分解技术进行归类划分,从时域分解和频域分解两个角度系统评述了国内外研究人员对信号分解技术的应用研究现状;其次,从风电和光伏功率预测两个方面详细评述了信号分解技术的应用研究实例并通过实际分解结果对比了分解技术的优缺点;最后,总结了信号分解技术的应用场景,并对分解技术的应用领域和提高预测精度的研究方向进行了展望。
The main problem that affects the accurate prediction is non-stationarity of wind power and photovoltaic power.The signal decomposition technique can decompose the non-stationary power sequence into several intrinsic mode component of different frequencies,smoothing the fluctuation degree of the sequence,extracting sequence features,establishing a prediction model with strong adaptability,and improving the prediction accuracy.This paper firstly classifies and divides the signal decomposition technol-ogy,and systematically reviews the application research status of domestic and foreign researchers on the signal decomposition technology from the perspectives of time domain decomposition and frequency domain decomposition.Secondly,the application research examples of the signal decomposition technology are reviewed in detail from the two aspects of wind power and photovoltaic power prediction,and the advantages and disadvantages of the decomposition technology are compared through the actual decomposi-tion results.Finally,the application scenarios of the signal decomposition technology are summarized,and the application fields of the decomposition technology and the research direction of improving the prediction accuracy are prospected.
作者
李宏仲
叶翔宇
付国
LI Hongzhong;YE Xiangyu;FU Guo(Department of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200082,China;Qingtian Power Supply Company of State Grid Zhejiang Electric Power Company,Qingtian,Zhejiang 323900,China)
出处
《南方电网技术》
CSCD
北大核心
2023年第4期3-15,共13页
Southern Power System Technology
基金
国家自然科学基金资助项目(51777126)。
关键词
信号分解技术
功率预测
非平稳性
固有模态分量
风电
光伏
signal decomposition technique
power forecasting
non-stationarity
intrinsic mode component
wind power
photovoltaic
