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Editorial to the Special Issue “AI Applications to Power Systems”

Author

Listed:
  • Tek-Tjing Lie

    (Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1010, New Zealand)

Abstract

This Special Issue consists of the successful invited submissions to Energies on the very topical subject area of “AI applications to power systems”.

Suggested Citation

  • Tek-Tjing Lie, 2021. "Editorial to the Special Issue “AI Applications to Power Systems”," Energies, MDPI, vol. 14(18), pages 1-3, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5667-:d:632059
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    References listed on IDEAS

    as
    1. Jin-Gyeom Kim & Bowon Lee, 2020. "Automatic P2P Energy Trading Model Based on Reinforcement Learning Using Long Short-Term Delayed Reward," Energies, MDPI, vol. 13(20), pages 1-27, October.
    2. Mahmoud G. Hemeida & Salem Alkhalaf & Al-Attar A. Mohamed & Abdalla Ahmed Ibrahim & Tomonobu Senjyu, 2020. "Distributed Generators Optimization Based on Multi-Objective Functions Using Manta Rays Foraging Optimization Algorithm (MRFO)," Energies, MDPI, vol. 13(15), pages 1-37, July.
    3. Carlo Olivieri & Francesco de Paulis & Antonio Orlandi & Cosimo Pisani & Giorgio Giannuzzi & Roberto Salvati & Roberto Zaottini, 2020. "Estimation of Modal Parameters for Inter-Area Oscillations Analysis by a Machine Learning Approach with Offline Training," Energies, MDPI, vol. 13(23), pages 1-20, December.
    4. Alvaro Furlani Bastos & Surya Santoso, 2021. "Optimization Techniques for Mining Power Quality Data and Processing Unbalanced Datasets in Machine Learning Applications," Energies, MDPI, vol. 14(2), pages 1-21, January.
    5. Miftah Al Karim & Jonathan Currie & Tek-Tjing Lie, 2020. "Distributed Machine Learning on Dynamic Power System Data Features to Improve Resiliency for the Purpose of Self-Healing," Energies, MDPI, vol. 13(13), pages 1-20, July.
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