IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v275y2023ics0360544223009052.html
   My bibliography  Save this article

A multiple uncertainty-based Bi-level expansion planning paradigm for distribution networks complying with energy storage system functionalities

Author

Listed:
  • Zhou, Siyu
  • Han, Yang
  • Chen, Shuheng
  • Yang, Ping
  • Mahmoud, Karar
  • Darwish, Mohamed M.F.
  • Matti, Lehtonen
  • Zalhaf, Amr S.

Abstract

Reliability improvement is regarded as a crucial task in modern distribution network expansion planning. Compared to previous works, this paper presents a bi-level optimization model to optimize the planning of the distribution network complying with multiple renewable energy and energy storage system (ESS) functionalities to guarantee the economical and reliable operation of the distribution network. The candidate assets include substations, distribution lines, renewable energy-based distributed generations (DGs), and ESSs are systematically involved. The load level affected by seasonal change and the multiple uncertainties, including renewable energy, load fluctuation, and contingency outage, are comprehensively considered. The uncertainties caused by the stochastic of renewable energy and load demand are described using Latin Hypercube Sampling (LHS) method. To address the computational burden and complexities associated with non-linear AC power flow, the mixed-integer linear programming (MILP)-based bi-level model is proposed via piecewise linearization methodology. Therein, the upper-level optimization model is proposed to minimize the total present value cost of the planning scheme in normal operating conditions. The lower level model, which is constrained to investment decision-making of the upper-level framework, aims to minimize the total cost of expected energy not supplied (EENS) considering the uncertainties of the single contingency outage. The effectiveness of the proposed bi-level planning model is validated by numerical studies to guarantee economic and reliability improvement for distribution network.

Suggested Citation

  • Zhou, Siyu & Han, Yang & Chen, Shuheng & Yang, Ping & Mahmoud, Karar & Darwish, Mohamed M.F. & Matti, Lehtonen & Zalhaf, Amr S., 2023. "A multiple uncertainty-based Bi-level expansion planning paradigm for distribution networks complying with energy storage system functionalities," Energy, Elsevier, vol. 275(C).
    • Handle: RePEc:eee:energy:v:275:y:2023:i:c:s0360544223009052
    DOI: 10.1016/j.energy.2023.127511
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223009052
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127511?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Canizes, Bruno & Soares, João & Lezama, Fernando & Silva, Cátia & Vale, Zita & Corchado, Juan M., 2019. "Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation," Renewable Energy, Elsevier, vol. 138(C), pages 937-954.
    2. Li, Rui & Wang, Wei & Wu, Xuezhi & Tang, Fen & Chen, Zhe, 2019. "Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis," Energy, Elsevier, vol. 168(C), pages 30-42.
    3. Chabok, Hossein & Aghaei, Jamshid & Sheikh, Morteza & Roustaei, Mahmoud & Zare, Mohsen & Niknam, Taher & Lehtonen, Matti & Shafi-khah, Miadreza & Catalão, João P.S., 2022. "Transmission-constrained optimal allocation of price-maker wind-storage units in electricity markets," Applied Energy, Elsevier, vol. 310(C).
    4. Sixiang Zhao & William Benjamin Haskell & Michel-Alexandre Cardin, 2018. "Decision rule-based method for flexible multi-facility capacity expansion problem," IISE Transactions, Taylor & Francis Journals, vol. 50(7), pages 553-569, July.
    5. Li, Xin & Wu, Xian & Gui, De & Hua, Yawen & Guo, Panfeng, 2021. "Power system planning based on CSP-CHP system to integrate variable renewable energy," Energy, Elsevier, vol. 232(C).
    6. Saboori, Hedayat & Hemmati, Reza & Jirdehi, Mehdi Ahmadi, 2015. "Reliability improvement in radial electrical distribution network by optimal planning of energy storage systems," Energy, Elsevier, vol. 93(P2), pages 2299-2312.
    7. Li, Yang & Feng, Bo & Wang, Bin & Sun, Shuchao, 2022. "Joint planning of distributed generations and energy storage in active distribution networks: A Bi-Level programming approach," Energy, Elsevier, vol. 245(C).
    8. Alotaibi, Majed A. & Salama, M.M.A., 2016. "An efficient probabilistic-chronological matching modeling for DG planning and reliability assessment in power distribution systems," Renewable Energy, Elsevier, vol. 99(C), pages 158-169.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Junxiao Zhang & Chengmin Wang & Jing Zuo & Chong Gao & Shurong Zheng & Ran Cheng & Yao Duan & Yawu Wang, 2024. "Multi-Stage Rolling Grid Expansion Planning for Distribution Networks Considering Conditional Value at Risk," Energies, MDPI, vol. 17(20), pages 1-20, October.
    2. Xiang, Shizhe & Xu, Da & Wang, Pengda & Bai, Ziyi & Zeng, Lingxiong, 2024. "Optimal expansion planning of 5G and distribution systems considering source-network-load-storage coordination," Applied Energy, Elsevier, vol. 366(C).
    3. Hu, Junjie & Wang, Yudong & Dong, Lei, 2024. "Low carbon-oriented planning of shared energy storage station for multiple integrated energy systems considering energy-carbon flow and carbon emission reduction," Energy, Elsevier, vol. 290(C).
    4. Tang, Liangyu & Han, Yang & Zalhaf, Amr S. & Zhou, Siyu & Yang, Ping & Wang, Congling & Huang, Tao, 2024. "Resilience enhancement of active distribution networks under extreme disaster scenarios: A comprehensive overview of fault location strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    5. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
    6. Zhou, Siyu & Han, Yang & Zalhaf, Amr S. & Lehtonen, Matti & Darwish, Mohamed M.F. & Mahmoud, Karar, 2024. "A novel stochastic multistage dispatching model of hybrid battery-electric vehicle-supercapacitor storage system to minimize three-phase unbalance," Energy, Elsevier, vol. 296(C).
    7. Zhou, Siyu & Han, Yang & Zalhaf, Amr S. & Lehtonen, Matti & Darwish, Mohamed M.F. & Mahmoud, Karar, 2024. "Risk-averse bi-level planning model for maximizing renewable energy hosting capacity via empowering seasonal hydrogen storage," Applied Energy, Elsevier, vol. 361(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Siyu & Han, Yang & Yang, Ping & Mahmoud, Karar & Lehtonen, Matti & Darwish, Mohamed M.F. & Zalhaf, Amr S., 2022. "An optimal network constraint-based joint expansion planning model for modern distribution networks with multi-types intermittent RERs," Renewable Energy, Elsevier, vol. 194(C), pages 137-151.
    2. Wang, Bangyan & Wang, Xiuli & Zhu, Zongyao & Wu, Xiong, 2023. "Siting and sizing of energy storage for renewable generation utilization with multi-stage dispatch under uncertainty: A tri-level model and decomposition approach," Applied Energy, Elsevier, vol. 344(C).
    3. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
    4. Li, Jinghua & Lu, Bo & Wang, Zhibang & Zhu, Mengshu, 2021. "Bi-level optimal planning model for energy storage systems in a virtual power plant," Renewable Energy, Elsevier, vol. 165(P2), pages 77-95.
    5. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    6. Fitsum Salehu Kebede & Jean-Christophe Olivier & Salvy Bourguet & Mohamed Machmoum, 2021. "Reliability Evaluation of Renewable Power Systems through Distribution Network Power Outage Modelling," Energies, MDPI, vol. 14(11), pages 1-25, May.
    7. Firouzmakan, Pouya & Hooshmand, Rahmat-Allah & Bornapour, Mosayeb & Khodabakhshian, Amin, 2019. "A comprehensive stochastic energy management system of micro-CHP units, renewable energy sources and storage systems in microgrids considering demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 355-368.
    8. Duan, Ditao & Poursoleiman, Roza, 2021. "Modified teaching-learning-based optimization by orthogonal learning for optimal design of an electric vehicle charging station," Utilities Policy, Elsevier, vol. 72(C).
    9. Chi, Zhexiang & Chen, Ruoran & Huang, Simin & Li, Yan-Fu & Zhou, Bin & Zhang, Wenjuan, 2020. "Multi-State System Modeling and Reliability Assessment for Groups of High-speed Train Wheels," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    10. Umme Mumtahina & Sanath Alahakoon & Peter Wolfs, 2023. "A Literature Review on the Optimal Placement of Static Synchronous Compensator (STATCOM) in Distribution Networks," Energies, MDPI, vol. 16(17), pages 1-38, August.
    11. David Borge-Diez & Enrique Rosales-Asensio & Emin Açıkkalp & Daniel Alonso-Martínez, 2023. "Analysis of Power to Gas Technologies for Energy Intensive Industries in European Union," Energies, MDPI, vol. 16(1), pages 1-22, January.
    12. Li, Jing & Lu, Tianguang & Yi, Xinning & Hao, Ran & Ai, Qian & Guo, Yu & An, Molin & Wang, Shaorui & He, Xueqian & Li, Yixiao, 2024. "Concentrated solar power for a reliable expansion of energy systems with high renewable penetration considering seasonal balance," Renewable Energy, Elsevier, vol. 226(C).
    13. Ghahramani, Mehrdad & Nazari-Heris, Morteza & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2019. "Energy and reserve management of a smart distribution system by incorporating responsive-loads /battery/wind turbines considering uncertain parameters," Energy, Elsevier, vol. 183(C), pages 205-219.
    14. Wu, Wei & Lin, Boqiang, 2018. "Application value of energy storage in power grid: A special case of China electricity market," Energy, Elsevier, vol. 165(PB), pages 1191-1199.
    15. Chen, Xiaoyuan & Jiang, Shan & Chen, Yu & Lei, Yi & Zhang, Donghui & Zhang, Mingshun & Gou, Huayu & Shen, Boyang, 2022. "A 10 MW class data center with ultra-dense high-efficiency energy distribution: Design and economic evaluation of superconducting DC busbar networks," Energy, Elsevier, vol. 250(C).
    16. Yu, Yanghao & Du, Ershun & Chen, Zhichao & Su, Yibo & Zhang, Xianfeng & Yang, Hongbin & Wang, Peng & Zhang, Ning, 2022. "Optimal portfolio of a 100% renewable energy generation base supported by concentrating solar power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    17. Hemmati, Reza & Saboori, Hedayat & Saboori, Saeid, 2016. "Stochastic risk-averse coordinated scheduling of grid integrated energy storage units in transmission constrained wind-thermal systems within a conditional value-at-risk framework," Energy, Elsevier, vol. 113(C), pages 762-775.
    18. Wang, Chunling & Liu, Chunming & Chen, Jian & Zhang, Gaoyuan, 2024. "Cooperative planning of renewable energy generation and multi-timescale flexible resources in active distribution networks," Applied Energy, Elsevier, vol. 356(C).
    19. Hossain, Eklas & Roy, Shidhartho & Mohammad, Naeem & Nawar, Nafiu & Dipta, Debopriya Roy, 2021. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters," Applied Energy, Elsevier, vol. 290(C).
    20. Laxmi Gupta & Ravi Shankar, 2022. "Adoption of Battery Management System in Utility Grid: An Empirical Study Using Structural Equation Modeling," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(4), pages 573-596, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:275:y:2023:i:c:s0360544223009052. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.