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Technology Selection of High-Voltage Offshore Substations Based on Artificial Intelligence

Author

Listed:
  • Tiago A. Antunes

    (Electrical Engineering Department, Instituto Superior Técnico (IST), Alameda Campus, University of Lisbon, 1049-001 Lisbon, Portugal)

  • Rui Castro

    (Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID) Co-Owned by Instituto Superior Técnico (IST), University of Lisbon, 1000-029 Lisbon, Portugal)

  • Paulo J. Santos

    (MARE-URI IPS & Escola Superior Tecnologia (EST) Setúbal, Polytechnic Institute of Setúbal, 2910-761 Setúbal, Portugal)

  • Armando J. Pires

    (CTS-UNINOVA, LASI & Escola Superior Tecnologia (EST) Setúbal, Polytechnic Institute of Setúbal, 2910-761 Setúbal, Portugal)

Abstract

This paper proposes an automated approach to the technology selection of High-Voltage Alternating Current (HVAC) Offshore Substations (OHVS) for the integration of Oil & Gas (O&G) production and Offshore Wind Farms (OWF) based on Artificial Intelligence (AI) techniques. Due to the complex regulatory landscape and project diversity, this is enacted via a cost decision-model which was developed based on Knowledge-Based Systems (KBS) and incorporated into an optioneering software named Transmission Optioneering Model (TOM). Equipped with an interactive dashboard, it uses detailed transmission and cost models, as well as a technological and commercial benchmarking of offshore projects to provide a standardized selection approach to OHVS design. By automating this process, the deployment of a technically sound and cost-effective connection in an interactive sandbox environment is streamlined. The decision-model takes as primary inputs the power rating requirements and the distance of the offshore target site and tests multiple voltage/rating configurations and associated costs. The output is then the most technically and economically efficient interconnection setup. Since the TOM process relies on equivalent models and on a broad range of different projects, it is manufacturer-agnostic and can be used for virtually any site as a method that ensures both energy transmission and economic efficiency.

Suggested Citation

  • Tiago A. Antunes & Rui Castro & Paulo J. Santos & Armando J. Pires, 2024. "Technology Selection of High-Voltage Offshore Substations Based on Artificial Intelligence," Energies, MDPI, vol. 17(17), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4278-:d:1464883
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    References listed on IDEAS

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    1. Tiago A. Antunes & Rui Castro & Paulo J. Santos & Armando J. Pires, 2023. "Standardization of Power-from-Shore Grid Connections for Offshore Oil & Gas Production," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
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