PV System Performance Evaluation by Clustering Production Data to Normal and Non-Normal Operation

Odysseas Tsafarakis, Kostas Sinapis and Wilfried G. J. H. M. Van Sark
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Odysseas Tsafarakis: Copernicus Institute, Utrecht University, Heidelberglaan 2, 3584 CS Utrecht, The Netherlands
Kostas Sinapis: Solar Energy Application Centre, High Tech Campus 21, 5656AE Eindhoven, The Netherlands
Wilfried G. J. H. M. Van Sark: Copernicus Institute, Utrecht University, Heidelberglaan 2, 3584 CS Utrecht, The Netherlands

Energies, 2018, vol. 11, issue 4, 1-19

Abstract: The most common method for assessment of a photovoltaic (PV) system performance is by comparing its energy production to reference data (irradiance or neighboring PV system). Ideally, at normal operation, the compared sets of data tend to show a linear relationship. Deviations from this linearity are mainly due to malfunctions occurring in the PV system or data input anomalies: a significant number of measurements (named as outliers) may not fulfill this, and complicate a proper performance evaluation. In this paper a new data analysis method is introduced which allows to automatically distinguish the measurements that fit to a near-linear relationship from those which do not (outliers). Although it can be applied to any scatter-plot, where the sets of data tend to be linear, it is specifically used here for two different purposes in PV system monitoring: (1) to detect and exclude any data input anomalies; and (2) to detect and separate measurements where the PV system is functioning properly from the measurements characteristic for malfunctioning. Finally, the data analysis method is applied in four different cases, either with precise reference data (pyranometer and neighboring PV system) or with scattered reference data (in plane irradiance obtained from application of solar models on satellite observations).

Keywords: photovoltaic (PV) systems monitoring; malfunction detection; data analysis; PV systems; cluster analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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