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Reliability and Availability Optimization of Smart Microgrid Using Specific Configuration of Renewable Resources and Considering Subcomponent Faults

Author

Listed:
  • Geeta Yadav

    (Manav Rachna International Institute of Research and Studies (MRIIRS), Faridabad 121004, India)

  • Dheeraj Joshi

    (Department of Electrical Engineering, Delhi Technological University, Delhi 110042, India)

  • Leena Gopinath

    (Manav Rachna International Institute of Research and Studies (MRIIRS), Faridabad 121004, India)

  • Mahendra Kumar Soni

    (Manav Rachna International Institute of Research and Studies (MRIIRS), Faridabad 121004, India)

Abstract

In this paper, renewable resources, namely photovoltaic panels (PV), are placed in a specific configuration to obtain the maximum reliability and availability of a microgrid and study the subcomponent-level reliability and availability. The reliability of components can be increased by trying different configurations of the components. We identify the preferred configuration used for the PV panels as bridged linked. The overall reliability of the microgrid is increased when component-wise reliability is considered. Even components are further divided into subcomponents, and the multiple faults of each component are considered. The method used for the reliability evaluation and availability study is Markov state transition modeling. The microgrid’s reliability and availability are plotted concerning time using Matlab. The optimization of reliability and availability is conducted through optimization techniques such as the genetic algorithm (GA) and artificial neural networks (ANN). The results are compared and validated for the optimal values of mean time to failure (MTTF) and mean time to repair (MTTR). Using a genetic algorithm, there is a 96% of improvement in the reliability, and after applying the neural networks, a significant improvement of 97% along with quick results is achieved.

Suggested Citation

  • Geeta Yadav & Dheeraj Joshi & Leena Gopinath & Mahendra Kumar Soni, 2022. "Reliability and Availability Optimization of Smart Microgrid Using Specific Configuration of Renewable Resources and Considering Subcomponent Faults," Energies, MDPI, vol. 15(16), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5994-:d:891901
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    References listed on IDEAS

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    1. A. Sayed & M. El-Shimy & M. El-Metwally & M. Elshahed, 2019. "Reliability, Availability and Maintainability Analysis for Grid-Connected Solar Photovoltaic Systems," Energies, MDPI, vol. 12(7), pages 1-18, March.
    2. Cevasco, D. & Koukoura, S. & Kolios, A.J., 2021. "Reliability, availability, maintainability data review for the identification of trends in offshore wind energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
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    4. Wei, Chun & Shen, Zhuzheng & Xiao, Dongliang & Wang, Licheng & Bai, Xiaoqing & Chen, Haoyong, 2021. "An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining," Applied Energy, Elsevier, vol. 295(C).
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    Cited by:

    1. Bingyin Lei & Yue Ren & Huiyu Luan & Ruonan Dong & Xiuyuan Wang & Junli Liao & Shu Fang & Kaiye Gao, 2023. "A Review of Optimization for System Reliability of Microgrid," Mathematics, MDPI, vol. 11(4), pages 1-30, February.
    2. Kartick Bhushan & Somnath Chattopadhyaya & Shubham Sharma & Kamal Sharma & Changhe Li & Yanbin Zhang & Elsayed Mohamed Tag Eldin, 2022. "Analyzing Reliability and Maintainability of Crawler Dozer BD155 Transmission Failure Using Markov Method and Total Productive Maintenance: A Novel Case Study for Improvement Productivity," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    3. Gia-Shie Liu & Kuo-Ping Lin, 2022. "Availability Optimization Decision Support Design System for Different Repairable n -Stage Mixed Systems," Mathematics, MDPI, vol. 11(1), pages 1-47, December.

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