Abstract
The purpose of this study is the development of an algorithmic tool to cluster the points of a scatterplot of "System Yield vs. Reference Yield" of photovoltaic systems, which tends to follow a linear regression. From such clustering one can distinguish data points that comply with the linearity (inliers) and the data points which do not (outliers). The tool then is applied to the scatterplot for two main purposes: a) to detect and exclude any data input anomalies or b) to detect and separate measurements where the PV system is functioning properly from the measurements that show that the photovoltaic (PV) system is malfunctioning.
| Original language | English |
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| Pages | 423-425 |
| Number of pages | 3 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | 46th IEEE Photovoltaic Specialists Conference (PVSC 46) - Chicago, Il, United States Duration: 16 Jun 2019 → 21 Jun 2019 |
Conference
| Conference | 46th IEEE Photovoltaic Specialists Conference (PVSC 46) |
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| Country/Territory | United States |
| City | Chicago, Il |
| Period | 16/06/19 → 21/06/19 |
Keywords
- photovoltaic power systems
- power system measurement
- regression analysis
- data input anomalies
- photovoltaic system
- PV system performance evaluation
- production data
- nonnormal operation
- algorithmic tool
- system yield
- reference yield
- linear regression
- data points
- normal operation
