Outliers screening for photovoltaic electric power based on the least square method

With the increase of the photoelectric scale, data with high quality is a necessary prerequisite for accurate prediction. The least square fitting method is one of the typical methods of abnormal data screening, which has not been widely used in screening photovoltaic power. In this paper, Three met...

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Bibliographic Details
Published in2016 Chinese Control and Decision Conference (CCDC) pp. 2799 - 2804
Main Authors Yu, Li, Wang, Hongqing, Che, Jianfeng, Lu, Jing, Zheng, Xueming
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.05.2016
Subjects
Algorithm design and analysis
Clustering Analysis
Conferences
Electric power generation
Electronics
Fitting
Gaussian distribution
Least mean square methods
Least Square Method
Least squares method
Outlier Screening Method
Outliers (statistics)
Photovoltaic cells
Photovoltaic Power
Photovoltaic systems
Power systems
Screening
Solar cells
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Summary:With the increase of the photoelectric scale, data with high quality is a necessary prerequisite for accurate prediction. The least square fitting method is one of the typical methods of abnormal data screening, which has not been widely used in screening photovoltaic power. In this paper, Three methods for outfielders with the abnormal screening of single point, short-term continuous outliers, long-term continuous are put forward based on the least square method. Those methods are used in photovoltaic power, combined with the clustering analysis method, the effectiveness and correctness of the screening method used in photovoltaic power outliers was proved.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Conference-1
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SourceType-Conference Papers & Proceedings-2
ISSN:1948-9447
DOI:10.1109/CCDC.2016.7531458