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Maintenance optimization of power systems with renewable energy sources integrated

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  • Shayesteh, E.
  • Yu, J.
  • Hilber, P.

Abstract

This paper proposes a quantitative maintenance optimization problem for developing reliability centred maintenance for a power system with renewable energy sources. Reliability and cost are two important interlinked aspects considered by system operators in many deregulated power systems. Reliability centred maintenance is an effective method to consider both of these aspects when performing the maintenance optimization. Nevertheless, this method has not adequately studied for a power system with renewable energy sources included.

Suggested Citation

  • Shayesteh, E. & Yu, J. & Hilber, P., 2018. "Maintenance optimization of power systems with renewable energy sources integrated," Energy, Elsevier, vol. 149(C), pages 577-586.
    • Handle: RePEc:eee:energy:v:149:y:2018:i:c:p:577-586
    DOI: 10.1016/j.energy.2018.02.066
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    References listed on IDEAS

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    Cited by:

    1. Rusin, Andrzej & Wojaczek, Adam, 2019. "Improving the availability and lengthening the life of power unit elements through the use of risk-based maintenance planning," Energy, Elsevier, vol. 180(C), pages 28-35.
    2. Yu-Chung Tsao & Thuy-Linh Vu, 2023. "Electricity pricing, capacity, and predictive maintenance considering reliability," Annals of Operations Research, Springer, vol. 322(2), pages 991-1011, March.
    3. Martyna Tomala & Andrzej Rusin & Adam Wojaczek, 2020. "Risk-Based Planning of Diagnostic Testing of Turbines Operating with Increased Flexibility," Energies, MDPI, vol. 13(13), pages 1-16, July.
    4. LaCommare, Kristina Hamachi & Eto, Joseph H. & Dunn, Laurel N. & Sohn, Michael D., 2018. "Improving the estimated cost of sustained power interruptions to electricity customers," Energy, Elsevier, vol. 153(C), pages 1038-1047.
    5. Toubeau, Jean-François & Pardoen, Lorie & Hubert, Louis & Marenne, Nicolas & Sprooten, Jonathan & De Grève, Zacharie & Vallée, François, 2022. "Machine learning-assisted outage planning for maintenance activities in power systems with renewables," Energy, Elsevier, vol. 238(PC).
    6. Kuen-Suan Chen & Kuo-Ping Lin & Jun-Xiang Yan & Wan-Lin Hsieh, 2019. "Renewable Power Output Forecasting Using Least-Squares Support Vector Regression and Google Data," Sustainability, MDPI, vol. 11(11), pages 1-13, May.
    7. Ajagekar, Akshay & You, Fengqi, 2019. "Quantum computing for energy systems optimization: Challenges and opportunities," Energy, Elsevier, vol. 179(C), pages 76-89.
    8. Wilberforce, Tabbi & El Hassan, Zaki & Durrant, A. & Thompson, J. & Soudan, Bassel & Olabi, A.G., 2019. "Overview of ocean power technology," Energy, Elsevier, vol. 175(C), pages 165-181.
    9. Ahmed Daeli & Salman Mohagheghi, 2022. "Power Grid Infrastructural Resilience against Extreme Events," Energies, MDPI, vol. 16(1), pages 1-17, December.
    10. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.
    11. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.
    12. Andrés A. Zúñiga & Alexandre Baleia & João Fernandes & Paulo Jose Da Costa Branco, 2020. "Classical Failure Modes and Effects Analysis in the Context of Smart Grid Cyber-Physical Systems," Energies, MDPI, vol. 13(5), pages 1-26, March.

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