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Hybrid parametric islanding detection technique for microgrid system

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In microgrid distribution generation (DG) sources are integrated parallelly for the economic and efficient operation of a power system. This integration of DG sources may cause many challenges in a microgrid. The islanding condition is termed a condition in which the DG sources in the microgrid continue to power the load even when the grid is cut off. This islanding situation must be identified as soon as possible to avoid the collapse of the microgrid. This work presents the hybrid islanding detection technique. This technique consists of both active and parametric estimation methods such as slip mode shift frequency (SMS) and exact signal parametric rotational invariance technique (ESPRIT), respectively. This technique will easily distinguish between islanding and non-islanding events even under very low power perturbations. The proposed method also has no power quality impact. The proposed method is tested with UL741 standard test conditions.
Rocznik
Strony
art. no. e140101
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
autor
  • Sapthagiri College of Engineering, Periyanahali, Dharmapuri, India
  • Thiagarajar College of Engineering, Madurai, India
  • Thiagarajar College of Engineering, Madurai, India
Bibliografia
  • [1] B.K. Panigrahi, A. Bhuyan, J. Shukla, P.K. Ray, and S.Pati, “A comprehensive review on intelligent islanding detection techniques for renewable energy integrated power system”, Int. J. Energy Res., vol. 45, no. 10, pp. 14085–14116, 2021.
  • [2] IEEE Recommended Practice for Utility Interface of Photovoltaic (PV) Systems, IEEE Std. 929-2000, 2000.
  • [3] J.A. Laghari, H. Mokhlis, M. Karimi, A.H.A. Bakar, and H. Mohamad, “Coordinated control strategy for microgrid stability maintenance under isolated island operation”, Bull. Pol. Acad. Sci. Tech. Sci., vol. 70, no. 2, pp. 285-295, 2021.
  • [4] Z. Xi, F. Zhao, X. Zhao, H. Peng, and C. Xi, “Research on islanding detection of solar distributed generation based on best wavelet packet and neural network”, Bull. Pol. Acad. Sci. Tech. Sci., vol. 68, no. 4, pp. 703–717,2019.
  • [5] M. Seyedi, S.T. Taher, B. Ganji, and J.M. Guerrero, “A hybrid islanding detection technique for inverter-based distributed generator units”, Int. Trans. Electr. Energy Syst., vol. 29, no.11, pp. 1–21, 2019.
  • [6] U. Markovic, D. Chrysostomou, P. Aristidou, and G. Hug, “Analysis impact of inverter-based generation on islanding detection schemes in distribution networks”, Electr. Power Syst. Res., vol. 190, pp. 106610, 2021.
  • [7] R. Zamania, M.E.H. Golshana, H.H. Alheloua, and N. Hatziargyriou, “A novel hybrid islanding detection method using dynamic characteristics of synchronous generator and signal processing technique”, Electr. Power Syst. Res., vol. 175, pp. 105911, 2019.
  • [8] S. Raza, H. Mokhlis, H. Arof, J.A. Laghari, and L. Wang, “Application of signal processing techniques for islanding detection of distributed generation in distribution network: A review”, Energy Convers. Manage., vol. 96, pp. 613–624, 2015.
  • [9] P. Deepamangai and P.S. Manoharan, “Detection and estimation of grid-connected issues in quasi-Z-source inverter based photovoltaic system using robust parametric methods”, IET Power Electron., vol. 13, no.16, pp. 3661–3674, 2020.
  • [10] R. Roy and T. Kailath, “ESPRIT-estimation of signal parameters via rotational invariance techniques”, IEEE Trans. Acoust. Speech Signal Process., vol. 37, no. 7, pp. 984–995, 1989.
  • [11] M. Seyedi, S.A. Taher, B. Ganji, and J. Guerrero, “A hybrid islanding detection method based on the rates of changes in voltage and active power for the multi-inverter systems,” in IEEE Trans. Smart Grid, vol. 12, no. 4, pp. 2800–2811, Jul. 2021.
  • [12] M. Pahlevani, S.M. Kaviri, P. Jain, and B. Mohammadpour, “Advanced slip mode frequency shift islanding detection method for single phase grid connected PV inverters”, 2016 IEEE Applied Power Electronics Conference and Exposition (APEC), pp. 378–385, 2016
  • [13] P. Jain and S.K. Jain, “A Computationally Efficient Algorithm for Harmonic Phasors Estimation in Real-time”, 2020 21st National Power Systems Conference (NPSC), 2020, pp. 1–6.
  • [14] R. Azim, F. Li, Y. Xue, M. Starke, and H. Wang, “An islanding detection methodology combining decision trees and sandia frequency shift for inverter based distributed generations”, IET Gener. Transm. Distrib., vol. 11, no. 16, pp. 4104–4113, 2017.
  • [15] B.K. Chaitanya, A. Yadav, and M. Pazoki, “Reliable islanding detection scheme for distributed generation based on pattern-recognition”, in IEEE Trans. Ind. Inf., vol. 17, no. 8, pp. 5230–5238, 2021.
  • [16] M. Liu, W. Zhao, Q. Wang, S. Huang, K. Shi, “A solution to the parameter selection and current static error issues with frequency shift islanding detection methods”, IEEE Trans. Ind. Electron., vol. 68, no. 2, pp. 1401–1411, 2021.
  • [17] S. Nikolovski, H.R. Baghaee, and D. Mlaki ́c, “Islanding detection of synchronous generator-based DGs using rate of change of reactive power”, IEEE Syst. J., vol. 13, no. 4, pp. 4344–4354, 2019.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-874c6c37-667c-487f-844a-dbf89d455727
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