Abstract
Renewable energy generation techniques have received a lot of attention and development in recent years. As a key source of renewable energy, distributed generation (DG) is effective. These contrasting assets are able to combine as a hybrid energy system with a micro-grid, delivering electric power with the option of cooling or heating. The biggest issue with this type of DG is islanding. When DG deliveries power to loads once severing from the grid, islanding occurs. For islanding detection of distributed generation, the Eradicate Liability Passive Islanding Detection (ELPID) methodologies of Point of Common Coupling (PCC), Rate of Change of Frequency (ROCOF), and Rate of Change of Frequency (ROCOF) are utilized in this study.
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References
M.R. Alam, M.T.A. Begum, B. Mather, Islanding detection of distributed generation using electrical variables in space vector domain. IEEE Trans. Power Deliv. 35(2), 861–870 (2019)
E.C. Pedrino, T. Yamada, T.R. Lunardi, de Melo Vieira Jr, J.C., Islanding detection of distributed generation by using multi-gene genetic programming-based classifier. Appl. Soft Comput. 74, 206–215 (2019)
A. Shrestha, R. Kattel, M. Dachhepatic, B. Mali, R. Thapa, A. Singh, D. Bista, B. Adhikary, A. Papadakis, R.K. Maskey, Comparative study of different approaches for islanding detection of distributed generation systems. Appl. Syst. Innovat. 2(3), 25 (2019)
A. Rostami, A. Jalilian, S. Zabihi, J. Olamaei, E. Pouresmaeil, Islanding detection of distributed generation based on parallel inductive impedance switching. IEEE Syst. J. 14(1), 813–823 (2019)
M. Mishra, P.K. Rout, Fast discrete s-transform and extreme learning machine based approach to islanding detection in grid-connected distributed generation. Energy Syst. 10(3), 757–789 (2019)
M.S. Kim, R. Haider, G.J. Cho, C.H. Kim, C.Y. Won, J.S. Chai, Comprehensive review of islanding detection methods for distributed generation systems. Energies 12(5), 837 (2019)
A.A. Chandio, J.A. Laghari, S. Khokhar, S.A. Almani, A new islanding detection technique based on rate of change of reactive power and radial basis function neural network for distributed generation. J. Intell. Fuzzy Syst. 37(2), 2169–2179 (2019)
B. Pancha, R. Shrestha, A.K. Jha, Islanding detection in distributed generation integrated Thimi-Sallaghari distribution feeder using wavelet transform and artificial neural network. J. Inst. Eng. 15(2), 55–61 (2019)
C.R. Reddy, K.H. Reddy, Passive islanding detection technique for integrated distributed generation at zero power balanced islanding. Int. J. Integr. Eng. 11(6), 126–137 (2019)
C.R. Reddy, K.H. Reddy, A new passive islanding detection technique for integrated distributed generation system using rate of change of regulator voltage over reactive power at balanced islanding. J. Electr. Eng. Technol. 14(2), 527–534 (2019)
A.T. Kolli, N. Ghaffarzadeh, A novel phaselet-based approach for islanding detection in inverter-based distributed generation systems. Electr. Power Syst. Res. 182, 106226 (2020)
M. Gholami, Islanding detection method of distributed generation based on wavenet. Int. J. Eng. 32(2), 242–248 (2019)
C. Darab, R. Tarnovan, A. Turcu, C. Martineac, Artificial intelligence techniques for fault location and detection in distributed generation power systems, in 2019 8th International Conference on Modern Power Systems (MPS), pp. 1–4. IEEE (2019)
P. Nayak, A. Avilash, R.K. Mallick, Faster islanding detection of microgrid based on multiscale mathematical morphology. Int. J. Renew. Energy Res. (IJRER) 10(2), 1005–1011 (2020)
C.R. Reddy, K.H. Reddy, K.V.S. Reddy, Recognition of islanding data for multiple distributed generation systems with ROCOF shore up analysis, in Smart Intelligent Computing and Applications (Springer, Singapore, 2019), pp. 547–558
H. Samet, F. Hashemi, T. Ghanbari, Minimum non detection zone for islanding detection using an optimal Artificial Neural Network algorithm based on PSO. Renew. Sustain. Energy Rev. 52, 1–18 (2015). https://doi.org/10.1016/j.rser.2015.07.080
P.P. Mishra, C.N. Bhende, A passive islanding detection technique with reduced complexity for distributed generations, in 2017 7th International Conference on Power Systems (ICPS), pp. 830–835 (2017). https://doi.org/10.1109/ICPES.2017.8387404
S.S. Mohapatra, M.K. Maharana, S.B. Pati, Comprehensive review to analyze the islanding in distributed generation system, in 2021 1st International Conference on Power Electronics and Energy (ICPEE), pp. 1–7 (2021). https://doi.org/10.1109/ICPEE50452.2021.9358542
B. Matic-Cuka, M. Kezunovic, Islanding detection for inverter-based distributed generation using support vector machine method. IEEE Trans. Smart Grid 5(6), 2676–2686 (2014). https://doi.org/10.1109/TSG.2014.2338736
M.-S. Kim, R. Haider, G. Cho, C.-H. Kim, C.-Y. Won, J.-S. Chai, Comprehensive review of islanding detection methods for distributed generation systems. Energies 12, 837 (2019). https://doi.org/10.3390/en12050837
F. Hashemi, M. Mohammadi, Islanding detection approach with negligible non-detection zone based on feature extraction discrete wavelet transform and artificial neural network. Int. Trans. Electr. Energ. Syst. 26, 2172–2192 (2016). https://doi.org/10.1002/etep.2197
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Mohapatra, S.S., Maharana, M.K., Pradhan, A., Panigrahi, P.K., Prusty, R.C. (2023). Islanding Detection in Distributed Generation System Using MLPNN and ELPID Methods. In: Dash, R.N., Rathore, A.K., Khadkikar, V., Patel, R., Debnath, M. (eds) Smart Technologies for Power and Green Energy. Lecture Notes in Networks and Systems, vol 443. Springer, Singapore. https://doi.org/10.1007/978-981-19-2764-5_18
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