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A Novel Optimization Method for a Multi-Year Planning Scheme of an Active Distribution Network in a Large Planning Zone

Author

Listed:
  • Xuejun Zheng

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Shaorong Wang

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Zia Ullah

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Mengmeng Xiao

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Chang Ye

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Zhangping Lei

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

Electric power distribution networks plays a significant role in providing continuous electrical energy to different categories of customers. In the context of the present advancements, future load expansion in the active distribution networks (ADNs) poses the key challenge of planning to be derived as a multi-stage optimization task, including the optimal expansion planning scheme optimization (EPSO). The planning scheme optimization is a multi-attribute decision-making issue with high complexity and solving difficulty, especially when it involves a large-scale planning zone. This paper proposes a novel approach of a multi-year planning scheme for the effective solution of the EPSO problem in large planning zones. The proposed approach comprises three key parts, where the first part covers two essential aspects, i.e., (i) suggesting a project condition set that considers the elements directly related to a group of specific conditions and requirements (collectively referred to as conditions) to ADN planning projects; and (ii) Developing a condition scoring system to evaluate planning projects. The second part of our proposed scheme is a quantization method of correlativity among projects based on two new concepts: contribution index (CI) and dependence index (DI). Finally, considering the multi-year rolling optimization, a detailed mathematical model of condition evaluation and spatiotemporal optimization sequencing of ADN planning projects is developed, where the evaluation and optimization are updated annually. The proposed model has been successfully validated on a practical distribution network located in Xiantao, China. The investigated case study and comparisons verify the various advantages, suitability, and effectiveness of the proposed planning scheme, consequently saving more than 10% of the investment compared with the existing implemented scheme.

Suggested Citation

  • Xuejun Zheng & Shaorong Wang & Zia Ullah & Mengmeng Xiao & Chang Ye & Zhangping Lei, 2021. "A Novel Optimization Method for a Multi-Year Planning Scheme of an Active Distribution Network in a Large Planning Zone," Energies, MDPI, vol. 14(12), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3450-:d:572933
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    References listed on IDEAS

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    1. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    2. Ghadi, Mojtaba Jabbari & Rajabi, Amin & Ghavidel, Sahand & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2019. "From active distribution systems to decentralized microgrids: A review on regulations and planning approaches based on operational factors," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Liang, Z. & Chen, H. & Chen, S. & Lin, Z. & Kang, C., 2019. "Probability-driven transmission expansion planning with high-penetration renewable power generation: A case study in northwestern China," Applied Energy, Elsevier, vol. 255(C).
    4. Jun-Hyeok Kim & Byung-Sung Lee & Chul-Hwan Kim, 2020. "A Study on the Development of Machine-Learning Based Load Transfer Detection Algorithm for Distribution Planning," Energies, MDPI, vol. 13(17), pages 1-12, August.
    5. Zangeneh, Ali & Jadid, Shahram & Rahimi-Kian, Ashkan, 2009. "A hierarchical decision making model for the prioritization of distributed generation technologies: A case study for Iran," Energy Policy, Elsevier, vol. 37(12), pages 5752-5763, December.
    6. Pesaran H.A, Mahmoud & Huy, Phung Dang & Ramachandaramurthy, Vigna K., 2017. "A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 293-312.
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