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Enhanced IoT-Based Optimization for a Hybrid Power System in Cartwright, Labrador

Author

Listed:
  • Raymond Orie

    (Department of Engineering, School of Graduate Studies, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1C5S7, Canada)

  • Lynna Otabil

    (Department of Engineering, School of Graduate Studies, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1C5S7, Canada)

  • Jonathan Agorua

    (Department of Engineering, School of Graduate Studies, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1C5S7, Canada)

  • Mohammad Tariq Iqbal

    (Department of Engineering, School of Graduate Studies, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1C5S7, Canada)

Abstract

The existing electricity infrastructure in Cartwright depends on diesel generators and needs renewable energy integration and remote monitoring. This project aims to enhance the proposed hybrid system with IoT-based optimization by leveraging a low-cost open-source SCADA system and accomplished monitoring and control capabilities. Electrical data were collected and analyzed from the energy system via sensors using the Arduino UNO R4 Wi-Fi as an RTU. The designed SCADA system would optimize Cartwright’s energy system, allowing for real-time remote tracking and control via the Arduino IoT cloud platform. The voltage and current values obtained with the setup were accurate and close to the actual multimeter values over the measurement range. The project outcome included efficient real-time data acquisition and visualization on remote dashboards, enabling cloud monitoring of key electrical parameters. An alert mechanism was incorporated as a buzzer alarm in the event of under-voltage readings to trigger intervention from operators to take swift action to ensure system reliability and safety. One observation made was that, while the buzzer is not directly tied to current readings, it can be programmed to signal more issues like over-current.

Suggested Citation

  • Raymond Orie & Lynna Otabil & Jonathan Agorua & Mohammad Tariq Iqbal, 2025. "Enhanced IoT-Based Optimization for a Hybrid Power System in Cartwright, Labrador," Energies, MDPI, vol. 18(7), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1566-:d:1617412
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    More about this item

    Keywords

    Arduino UNO R4; cartwright; hybrid systems; internet of things; remote monitoring; renewable energy integration; supervisory control and data acquisition;
    All these keywords.

    JEL classification:

    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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