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Microgrids formed by renewable energy integration into power grids pose electrical protection challenges

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  • Akhtar, Zohaib
  • Saqib, Muhammad Asghar

Abstract

System parameters of a microgrid change in its two operating modes primarily due to output current limitation of PWM based inverters connected with renewable energy sources. The unavailability of an appropriate protection scheme, which must be compatible with both modes of a microgrid operation, is a major problem in the implementation of a microgrid. Two important properties of the microgrid components are peer-to-peer, and plug-and-play. It means that there is no component like a master controller which is critical for the operation of a system, and a distributed-generation unit can be installed at any location in a microgrid. These properties further complicate the protection of a microgrid. This paper reports the MATLAB/SIMULINK model of a microgrid along with the models of the conventional protection schemes and renewable energy distributed-generation resources. Malfunctioning in the conventional protection schemes in islanding mode is identified and models of newly proposed protection schemes are developed. Different types of faults are simulated in all the protection zones of the system and the system parameters are analysed to identify the possible fault detection methods. Based on the simulation results, a protection scheme is recommended that can meet the protection standards such as selectivity, co-ordination and reliability.

Suggested Citation

  • Akhtar, Zohaib & Saqib, Muhammad Asghar, 2016. "Microgrids formed by renewable energy integration into power grids pose electrical protection challenges," Renewable Energy, Elsevier, vol. 99(C), pages 148-157.
    • Handle: RePEc:eee:renene:v:99:y:2016:i:c:p:148-157
    DOI: 10.1016/j.renene.2016.06.053
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    Cited by:

    1. Sajadi, A. & Strezoski, L. & Clark, K. & Prica, M. & Loparo, K.A., 2018. "Transmission system protection screening for integration of offshore wind power plants," Renewable Energy, Elsevier, vol. 125(C), pages 225-233.
    2. Wang, Yifei & Wang, Xiuli & Shao, Chengcheng & Gong, Naiwei, 2020. "Distributed energy trading for an integrated energy system and electric vehicle charging stations: A Nash bargaining game approach," Renewable Energy, Elsevier, vol. 155(C), pages 513-530.
    3. Lu, Tianguang & Ai, Qian & Wang, Zhaoyu, 2018. "Interactive game vector: A stochastic operation-based pricing mechanism for smart energy systems with coupled-microgrids," Applied Energy, Elsevier, vol. 212(C), pages 1462-1475.
    4. Nadeem Javaid & Sardar Mehboob Hussain & Ibrar Ullah & Muhammad Asim Noor & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2017. "Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations," Energies, MDPI, vol. 10(8), pages 1-29, August.
    5. Kyritsis, A. & Voglitsis, D. & Papanikolaou, N. & Tselepis, S. & Christodoulou, C. & Gonos, I. & Kalogirou, S.A., 2017. "Evolution of PV systems in Greece and review of applicable solutions for higher penetration levels," Renewable Energy, Elsevier, vol. 109(C), pages 487-499.
    6. Rameshrao, Awagan Goyal & Koley, Ebha & Ghosh, Subhojit, 2022. "A LSTM-based approach for detection of high impedance faults in hybrid microgrid with immunity against weather intermittency and N-1 contingency," Renewable Energy, Elsevier, vol. 198(C), pages 75-90.

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