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Review on Distribution Network Optimization under Uncertainty

Author

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  • Huilian Liao

    (Power, Electrical and Control Engineering, Sheffield Hallam University, Sheffield S1 1WB, UK)

Abstract

With the increase of renewable energy in electricity generation and increased engagement from demand sides, distribution network planning and operation face great challenges in the provision of stable, secure and dedicated service under a high level of uncertainty in network behaviors. Distribution network planning and operation, at the same time, also benefit from the changes of current and future distribution networks in terms of the availability of increased resources, diversity, smartness, controllability and flexibility of the distribution networks. This paper reviews the critical optimization problems faced by distribution planning and operation, including how to cope with these changes, how to integrate an optimization process in a problem-solving framework to efficiently search for optimal strategy and how to optimize sources and flexibilities properly in order to achieve cost-effective operation and provide quality of services as required, among other factors. This paper also discusses the approaches to reduce the heavy computation load when solving large-scale network optimization problems, for instance by integrating the prior knowledge of network configuration in optimization search space. A number of optimization techniques have been reviewed and discussed in the paper. This paper also discusses the changes, challenges and opportunities in future distribution networks, analyzes the possible problems that will be faced by future network planning and operations and discusses the potential strategies to solve these optimization problems.

Suggested Citation

  • Huilian Liao, 2019. "Review on Distribution Network Optimization under Uncertainty," Energies, MDPI, vol. 12(17), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3369-:d:263005
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    References listed on IDEAS

    as
    1. Singh, Bindeshwar & Sharma, Janmejay, 2017. "A review on distributed generation planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 529-544.
    2. Viral, Rajkumar & Khatod, D.K., 2012. "Optimal planning of distributed generation systems in distribution system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 5146-5165.
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    Cited by:

    1. Marie-Cécile Alvarez-Herault & Jean-Pierre Dib & Oana Ionescu & Bertrand Raison, 2022. "Long-Term Planning of Electrical Distribution Grids: How Load Uncertainty and Flexibility Affect the Investment Timing," Energies, MDPI, vol. 15(16), pages 1-27, August.
    2. Peng Jiang & Xihao Dou & Jun Dong & Hexiang Huang & Yuanyuan Wang, 2022. "Terminal Node of Active Distribution Network Correlation Compactness Model and Application Based on Complex Network Topology Graph," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    3. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    4. Farooq, Asma & Shahid, Kamal & Olsen, Rasmus Løvenstein, 2024. "Securing the green grid: A data anomaly detection method for mitigating cyberattacks on smart meter measurements," International Journal of Critical Infrastructure Protection, Elsevier, vol. 46(C).
    5. Xiangwu Yan & Yan Guo & Jiaoxin Jia & Waseem Aslam & Bingbao Qi & Yang Wang & Xiaolin Xu, 2022. "An Electromagnetic Var Compensator Suitable for Wind Power Access and Its Control Strategy," Energies, MDPI, vol. 15(15), pages 1-15, July.
    6. Tao Zhang & Minli Wang & Peihong Wang & Junyu Liang, 2020. "Optimal Design of a Combined Cooling, Heating, and Power System and Its Ability to Adapt to Uncertainty," Energies, MDPI, vol. 13(14), pages 1-17, July.

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