Research article

Islanding detection in utility grid with renewable energy using rate of change of frequency and signal processing technique

  • Received: 02 January 2022 Revised: 18 March 2022 Accepted: 22 March 2022 Published: 31 March 2022
  • This manuscript has introduced an algorithm based on current signals and frequency rate change (ROCOF) to identify islanding events. Current is analyzed by the use of Stockwell transform (ST) at 3.84 kHz sampling frequency (SF) and a median of absolute values of every column of output matrix (CSIRI) is computed. Rate of change of CSIRI (ROCOCSIRI) is computed. Proposed current based islanding recognition index (IRIC) is computed by multiplying ROCOF with CSIRI & ROCOCSIRI and a weight factor (WC). Threshold values THI1 & THI2 are selected 100 and 3000 for IRIC for identifying the Islanding condition. These are also effective to differentiate islanding conditions from non-islanding events which include both the faulty and operational events. Magnitude of IRIC is greater than 3000 for the faulty events and lower than 100 for operational events. For islanding events magnitude of IRIC falls in between the 100 and 3000. Algorithm is effective to identify and classify the events in three categories which are islanding events, faulty events and operational events effectively. Study is realized in MATLAB/Simulink scenario.

    Citation: Om Prakash Mahela, Pappu Ram Bheel, M.K. Bhaskar, Baseem Khan. Islanding detection in utility grid with renewable energy using rate of change of frequency and signal processing technique[J]. AIMS Electronics and Electrical Engineering, 2022, 6(2): 144-160. doi: 10.3934/electreng.2022009

    Related Papers:

  • This manuscript has introduced an algorithm based on current signals and frequency rate change (ROCOF) to identify islanding events. Current is analyzed by the use of Stockwell transform (ST) at 3.84 kHz sampling frequency (SF) and a median of absolute values of every column of output matrix (CSIRI) is computed. Rate of change of CSIRI (ROCOCSIRI) is computed. Proposed current based islanding recognition index (IRIC) is computed by multiplying ROCOF with CSIRI & ROCOCSIRI and a weight factor (WC). Threshold values THI1 & THI2 are selected 100 and 3000 for IRIC for identifying the Islanding condition. These are also effective to differentiate islanding conditions from non-islanding events which include both the faulty and operational events. Magnitude of IRIC is greater than 3000 for the faulty events and lower than 100 for operational events. For islanding events magnitude of IRIC falls in between the 100 and 3000. Algorithm is effective to identify and classify the events in three categories which are islanding events, faulty events and operational events effectively. Study is realized in MATLAB/Simulink scenario.



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