摘要
光伏阵列运行数据中存在大量异常数据,这些异常数据会对光伏阵列性能分析、建模、故障诊断的实现带来困难。为了有效剔除光伏阵列运行数据中的异常数据,提出了一种基于滑动标准差的光伏阵列异常数据清洗方法。分析了阵列异常数据的来源及分布特性,给出了光伏阵列滑动标准差的计算方法。该方法以滑动标准差的曲线上翘作为异常数据的判断依据。最后通过实例分析以及其他方法对比,说明该算法可以有效降低由于异常数据集中分布带来的异常数据清洗困难。
There are a large number of outliers in the PV array operation data.The outlier will bring difficulties to the functions such as PV array performance analysis,modeling,and fault diagnosis.In order to effectively clean the outlier in the PV array operation data,this paper proposes a cleaning method for PV array outlier based on moving standard deviation.It analyzes the source and distribution characteristics of the array outlier data and proposes the algorithm based on moving standard deviation.The curve’s rising of the sliding standard deviation set is used as the basis for judging the outlier data.Finally,through the case analysis and comparison of quartile method,the results show that the algorithm can effectively reduce the cleaning error caused by the concentration distribution of the outlier.
作者
时珉
尹瑞
胡傲宇
吴骥
SHI Min;YIN Rui;HU Aoyu;WU Ji(State Grid Hebei Electric Power Supply Co.,Ltd.,Shijiazhuang 050000,China;North China Electric Power University,Beijing 102206,China;China Electric Power Research Institute,Nanjing 210000,China)
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2020年第6期108-114,共7页
Power System Protection and Control
基金
国家自然科学基金项目(U1765104)
国网河北省电力有限公司科技项目(5204BB170007)“区域风光资源及发电能力中长期预测技术研究与应用”。
