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Reliability Assessment of Major Feeders of the Atoabo Substation, Tarkwa Using Autorecloser-Based ETAP Simulation

Author

Listed:
  • J. K. Annan

    (University of Mines and Technology, Tarkwa)

  • J. M. Yevunya

    (Electricity Company of Ghana, Ahomaso, Kumasi)

Abstract

Reliable Medium Voltage (MV) distribution networks are critical to economic activities in Ghana, particularly in mining-intensive municipalities such as Tarkwa, where prolonged outages impose substantial operational losses. This study evaluates the reliability performance of the 11 kV Town 1, Town 2 and Manganese feeders supplied from the Atoabo Bulk Supply Point (BSP), a strategically important node feeding high-value industrial and residential loads. Six years of outage data (2016–2021) were analysed and used to calibrate an ETAP probabilistic reliability model, addressing the absence of simulation-based reliability evaluation and automation-planning studies for Ghanaian MV distribution networks. The calibrated ETAP model replicated historical SAIFI and SAIDI values within ±5–10%, confirming strong model fidelity. Simulation results show that ACR deployment yields significant reliability improvement at SAIFI reduction of 35–40% on Town 2, SAIDI reduction of 32–35% on Manganese feeder, and overall reliability improvement of 25–30% on Town 1. The findings demonstrate that targeted MV automation at Atoabo BSP provides a cost-effective and high-impact reliability intervention, capable of reducing cumulative annual customer interruption duration by over 100 hours per feeder. This work provides an investable pathway for Electricity Company of Ghana to achieve Public Utilities and Regulatory Commission’s reliability benchmarks in similar radial distribution environments.

Suggested Citation

  • J. K. Annan & J. M. Yevunya, 2025. "Reliability Assessment of Major Feeders of the Atoabo Substation, Tarkwa Using Autorecloser-Based ETAP Simulation," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(11), pages 971-993, November.
  • Handle: RePEc:bjf:journl:v:10:y:2025:i:11:p:971-993
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    References listed on IDEAS

    as
    1. Siyabonga Brian Gumede & Akshay Kumar Saha, 2022. "Optimizing Recloser Settings in an Active Distribution System Using the Differential Evolution Algorithm," Energies, MDPI, vol. 15(22), pages 1-16, November.
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