SVM based pattern recognised islanding detection approach in a multiple distributed generation system

  • Authors

    • Gundala Srinivasa Rao K L E F, Vaddeswaram, Guntur-522502
    • G. Kesava Rao K L E F, Vaddeswaram
    2018-03-01
    https://doi.org/10.14419/ijet.v7i1.9559
  • Islanding, Support Vector Machine (SVM), Pattern Recognising Approach.

  • The penetration of Distributed generation (DG) ensures the increase of demand for consistent, reasonable and spotless electricity facing with some design and operational challenges such as islanding. Several active and passive methods have been suggested in the past to detect islanding. Since they suffer from the large non detection zone and a high cost. In order to defeat such issues we propose a SVM based pattern recognising approach for islanding detection in a multiple DG system. The results show that our proposed method detects islanding with high accuracy.

  • References

    1. [1] Ray, Prakash K., Soumya R. Mohanty, and Nand Kishor. "Disturbance detection in grid-connected distributed generation system using wavelet and S-transform." Electric Power Systems Research, Vol.81, No.3, pp. 805-819, 2011. https://doi.org/10.1016/j.epsr.2010.11.011.

      [2] Hashemi, Farid, Noradin Ghadimi, and Behrooz Sobhani. "Islanding detection for inverter-based DG coupled with using an adaptive neuro-fuzzy inference system." International Journal of Electrical Power & Energy Systems, Vol.45, No.1, pp.443-455, 2013 https://doi.org/10.1016/j.ijepes.2012.09.008.

      [3] Nasirian, Vahidreza, et al. "Distributed cooperative control of dc microgrids." IEEE Transactions on Power Electronics, Vol.30, No.4, pp. 2288-2303, 2015. https://doi.org/10.1109/TPEL.2014.2324579.

      [4] Guerrero, Josep M., et al. "Advanced control architectures for intelligent microgrids—Part II: Power quality, energy storage, and AC/DC microgrids." IEEE Transactions on Industrial Electronics, Vol.60, No.4, pp. 1263-1270, 2013. https://doi.org/10.1109/TIE.2012.2196889.

      [5] Miller, Laurie E., et al. "Smart grid opportunities in islanding detection." 2013 IEEE Power & Energy Society General Meeting. IEEE, 2013.

      [6] Ahmad, Ku Nurul Edhura Ku, Jeyraj Selvaraj, and Nasrudin Abd Rahim. "A review of the islanding detection methods in grid-connected PV inverters." Renewable and Sustainable Energy Reviews, Vol.21, pp. 756-766, 2013. https://doi.org/10.1016/j.rser.2013.01.018.

      [7] Dong, Dong, et al. "Analysis of phase-locked loop low-frequency stability in three-phase grid-connected power converters considering impedance interactions." IEEE Transactions on Industrial Electronics, Vol.62, No.1, pp. 310-321, 2015. https://doi.org/10.1109/TIE.2014.2334665.

      [8] Trujillo, C. L., et al. "Analysis of active islanding detection methods for grid-connected microinverters for renewable energy processing." Applied Energy, Vol.87, No.11, pp. 3591-3605, 2010. https://doi.org/10.1016/j.apenergy.2010.05.014.

      [9] Khamis, Aziah, et al. "A review of islanding detection techniques for renewable distributed generation systems." Renewable and sustainable energy reviews, Vol.28, pp. 483-493, 2013. https://doi.org/10.1016/j.rser.2013.08.025.

      [10] Alshareef, Sami, Saurabh Talwar, and Walid G. Morsi. "A new approach based on wavelet design and machine learning for islanding detection of distributed generation." IEEE Transactions on Smart Grid, Vol. 5, No.4, pp. 1575-1583, 2014. https://doi.org/10.1109/TSG.2013.2296598.

      [11] Karegar, H. Kazemi, and B. Sobhani. "Wavelet transform method for islanding detection of wind turbines." Renewable Energy, Vol.38, No.1, pp. 94-106, 2012. https://doi.org/10.1016/j.renene.2011.07.002.

      [12] ElNozahy, M. S., R. A. EL-Shatshat, and M. M. A. Salama. "Single-phasing detection and classification in distribution systems with a high penetration of distributed generation." Electric Power Systems Research, Vol.131, pp. 41-48, 2016. https://doi.org/10.1016/j.epsr.2015.10.008.

      [13] Merlin, V.L., R.C. Santos, A.P. Grilo, J.C.M. Vieira, D.V. Coury, and M. Oleskovicz. "A new artificial neural network based method for islanding detection of distributed generators", International Journal of Electrical Power & Energy Systems, 2016. https://doi.org/10.1016/j.ijepes.2015.08.016.

      [14] Samet, Haidar, Farid Hashemi, and Teymoor Ghanbari. "Minimum non detection zone for islanding detection using an optimal Artificial Neural Network algorithm based on PSO." Renewable and Sustainable Energy Reviews, Vol.52, pp. 1-18, 2015. https://doi.org/10.1016/j.rser.2015.07.080.

      [15] Raza, Safdar, et al. "A Sensitivity Analysis of Different Power System Parameters on Islanding Detection." IEEE Transactions on Sustainable Energy, Vol.7, No.2, pp. 461-470, 2016. https://doi.org/10.1109/TSTE.2015.2499781.

      [16] Li, Canbing, Chi Cao, Yijia Cao, Yonghong Kuang, Long Zeng, and Baling Fang. "A review of islanding detection methods for microgrid", Renewable and Sustainable Energy Reviews, 2014. https://doi.org/10.1016/j.rser.2014.04.026.

      [17] Sharma, Rashmi, and Pratibha Singh. "Islanding detection and control in grid based system using wavelet transform", 2012 IEEE. Fifth Power India Conference, 2012. https://doi.org/10.1109/PowerI.2012.6479557.

      [18] Alam, M. R., K. M. Mut t aqi, and A. Bouzerdoum. "A Multi feature-Based Approach f or Islanding Detection of DG in the Subcritical Region of Vect or Surge Relays", IEEE Transact ions on Power Delivery, 2014. https://doi.org/10.1109/TPWRD.2014.2315839.

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  • How to Cite

    Srinivasa Rao, G., & Kesava Rao, G. (2018). SVM based pattern recognised islanding detection approach in a multiple distributed generation system. International Journal of Engineering & Technology, 7(1), 228-231. https://doi.org/10.14419/ijet.v7i1.9559