Detection of Unauthorized Photo-Voltaic System Connection for Low Voltage Grids

Date

2020-01-01

Author

Pouraltafi-Kheljan, Soheil
Göl, Murat

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Vast and unauthorized penetration of the photovoltaic systems in distribution systems imposed inadequate monitoring challenge to system operators. Although the installation of required monitoring infrastructure does seem as a solution, due to the high installation cost, it is not considered a feasible one, at least for the near future. As an alternative approach, a two-stage method composed of an ANN-based mapping function, and a regression model is presented to detect unauthorized PV connections to the system. A gradient boosting machine is implemented to build the regression model and the corresponding confidence interval. The Monte Carlo simulations are utilized to generate synthetic training data-sets for both models. Finally, the performance of the approach is assessed with real data.

URI

https://hdl.handle.net/11511/92808

DOI

https://doi.org/10.1109/siu49456.2020.9302080

Conference Name

28th Signal Processing and Communications Applications Conference (SIU)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

S. Pouraltafi-Kheljan and M. Göl, “Detection of Unauthorized Photo-Voltaic System Connection for Low Voltage Grids,” presented at the 28th Signal Processing and Communications Applications Conference (SIU), ELECTR NETWORK, 2020, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/92808.