摘要
电力负荷数据是电力大数据的核心内容,也是电力系统调度和规划等部门进行决策的重要参考依据。但由于各种不可控因素,原始负荷数据往往存在奇异点和噪声,同时巨量的负荷数据也会给数据存储和管理工作带来困难。为了解决这些问题,运用小波理论探讨了利用小波处理电力负荷数据的可行性,提出了小波双层阈值法,并结合实际案例,给出了小波分析在电力负荷数据去噪和压缩方面的应用。
Power load data is the core content of the power big data, and it is also an important reference for the decisionmaking of the dispatching and planning departments of the power system.However, due to various uncontrollable factors, original load data often have singularity and noise.At the same time, huge amounts of load data also bring difficulties to data storage and management.In order to solve these problems,mathematical basis of wavelet theory is analyzed,feasibility of using wavelet processing power load data is discussed ,the double threshold method is put forward ,application of wavelet analysis in the power load data denoising and compression is given combined with actual cases.
作者
李雨轩
高鹏
赵庆磊
LI Yuxuan;GAO Peng;ZHAO Qinglei(State Grid Shandong Electric Power Maintenance Company, Jinan 25011 $, China)
出处
《山东电力技术》
2018年第5期5-9,共5页
Shandong Electric Power
关键词
小波分析
电力负荷数据
信号降噪
数据压缩
wavelet analysis
power load data
signal noise reduction
data compression
