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Energy Regulator Supply Restoration Time

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  • Mohd Ikhwan Muhammad Ridzuan

    (Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, Pekan 26600, Malaysia)

  • Sasa Z. Djokic

    (Institute for Energy System, The University of Edinburgh, Edinburgh EH9 3DW, UK)

Abstract

In conventional reliability analysis, the duration of interruptions relied on the input parameter of mean time to repair (MTTR) values in the network components. For certain criteria without network automation, reconfiguration functionalities and/or energy regulator requirements to protect customers from long excessive duration of interruptions, the use of MTTR input seems reasonable. Since modern distribution networks are shifting towards smart grid, some factors must be considered in the reliability assessment process. For networks that apply reconfiguration functionalities and/or network automation, the duration of interruptions experienced by a customer due to faulty network components should be addressed with an automation switch or manual action time that does not exceed the regulator supply restoration time. Hence, this paper introduces a comprehensive methodology of substituting MTTR with maximum action time required to replace/repair a network component and to restore customer duration of interruption with maximum network reconfiguration time based on energy regulator supply requirements. The Monte Carlo simulation (MCS) technique was applied to medium voltage (MV) suburban networks to estimate system-related reliability indices. In this analysis, the purposed method substitutes all MTTR values with time to supply (TTS), which correspond with the UK Guaranteed Standard of Performance (GSP-UK), by the condition of the MTTR value being higher than TTS value. It is nearly impossible for all components to have a quick repairing time, only components on the main feeder were selected for time substitution. Various scenarios were analysed, and the outcomes reflected the applicability of reconfiguration and the replace/repair time of network component. Theoretically, the network reconfiguration (option 1) and component replacement (option 2) with the same amount of repair time should produce exactly the same outputs. However, in simulation, these two options yield different outputs in terms of number and duration of interruptions. Each scenario has its advantages and disadvantages, in which the distribution network operators (DNOs) were selected based on their operating conditions and requirements. The regulator reliability-based network operation is more applicable than power loss-based network operation in counties that employed energy regulator requirements (e.g., GSP-UK) or areas with many factories that required a reliable continuous supply.

Suggested Citation

  • Mohd Ikhwan Muhammad Ridzuan & Sasa Z. Djokic, 2019. "Energy Regulator Supply Restoration Time," Energies, MDPI, vol. 12(6), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:6:p:1051-:d:215144
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    References listed on IDEAS

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    1. Ke-yan Liu & Wanxing Sheng & Yongmei Liu & Xiaoli Meng, 2017. "A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks," Energies, MDPI, vol. 10(5), pages 1-17, May.
    2. Firas M. F. Flaih & Xiangning Lin & Mohammed Kdair Abd & Samir M. Dawoud & Zhengtian Li & Owolabi Sunday Adio, 2017. "A New Method for Distribution Network Reconfiguration Analysis under Different Load Demands," Energies, MDPI, vol. 10(4), pages 1-19, April.
    3. Juan Wen & Yanghong Tan & Lin Jiang, 2016. "A Reconfiguration Strategy of Distribution Networks Considering Node Importance," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-19, December.
    4. Fábio Usberti & Christiano Lyra & Celso Cavellucci & José González, 2015. "Hierarchical multiple criteria optimization of maintenance activities on power distribution networks," Annals of Operations Research, Springer, vol. 224(1), pages 171-192, January.
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    Cited by:

    1. Bordin, Chiara & Mishra, Sambeet & Palu, Ivo, 2021. "A multihorizon approach for the reliability oriented network restructuring problem, considering learning effects, construction time, and cables maintenance costs," Renewable Energy, Elsevier, vol. 168(C), pages 878-895.
    2. Marcin Szott & Szymon Wermiński & Marcin Jarnut & Jacek Kaniewski & Grzegorz Benysek, 2021. "Battery Energy Storage System for Emergency Supply and Improved Reliability of Power Networks," Energies, MDPI, vol. 14(3), pages 1-21, January.

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