An Efficient Islanding Classification Technique for Single Phase Grid Connected Photovoltaic System

Integration of renewable energy systems into low voltage buses leads to complexity for protection systems and unplanned islanding. Therefore, a need to reconfigure the typical protection configurations arises. In this paper an efficient islanding classification technique is developed to provide remote monitoring and operation of grid connected distributed generation systems. A simulation is developed by considering a 1kW grid connected photovoltaic system. The voltage and current measurements at the point of common coupling act as a main source of data for developing the classification algorithm. Wavelet transform is utilised for extracting features and creating a feature matrix for all possible scenarios of islanding. The feature matrix is subjected to machine learning approach for creating a trained data set which helps in classifying the islanding scenario. The results depicted 100% training and 97%testing efficiency under 0.2 seconds which is better when compared with the conventional methods and literature.

• Publication year

  2019

• Venue

  International Conference Communication and Information Systems

• Publication date

  2019-04-01

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1109/ICCISCI.2019.8716438
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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