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Open AccessArticle

A Novel Photovoltaic Array Outlier Cleaning Algorithm Based on Sliding Standard Deviation Mutation

by Aoyu Hu 1,2, Qian Sun 3, Hao Liu 3, Ning Zhou 3, Zhan’ao Tan 4 and Honglu Zhu 1,2,*
1
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
2
School of Renewable Energy, North China Electric Power University, Beijing 102206, China
3
State Grid HeNan Electric Power Company Research Institute, Zhengzhou 450000, China
4
Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(22), 4316; https://doi.org/10.3390/en12224316
Received: 9 October 2019 / Revised: 7 November 2019 / Accepted: 11 November 2019 / Published: 13 November 2019
(This article belongs to the Special Issue Photovoltaic Modules)
There is a large number of outliers in the operation data of photovoltaic (PV) array, which is caused by array abnormalities and faults, communication issues, sensor failure, and array shutdown during PV power plant operation. The outlier will reduce the accuracy of PV system performance analysis and modeling, and make it difficult for fault diagnosis of PV power plant. The conventional data cleaning method is affected by the outlier data distribution. In order to solve the above problems, this paper presents a method for identifying PV array outliers based on sliding standard deviation mutation. Considering the PV array output characteristics under actual environmental conditions, the distribution of array outliers is analyzed. Then, an outlier identification method is established based on sliding standard deviation calculation. This method can identify outliers by analyzing the degree of dispersion of the operational data. The verification part is illustrated by case study and algorithm comparison. In the case study, multiple sets of actual operating data of different inverters are cleaned, which is selected from a large grid-connected power station. The cleaning results illustrate the availability of the algorithm. Then, the comparison against the quantile-algorithm-based outlier identification method explains the effectiveness of the proposed algorithm. View Full-Text
Keywords: PV array; power curve; raw operation data; data cleaning; cleaning algorithm PV array; power curve; raw operation data; data cleaning; cleaning algorithm
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MDPI and ACS Style

Hu, A.; Sun, Q.; Liu, H.; Zhou, N.; Tan, Z.; Zhu, H. A Novel Photovoltaic Array Outlier Cleaning Algorithm Based on Sliding Standard Deviation Mutation. Energies 2019, 12, 4316.

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