IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6387-d650752.html
   My bibliography  Save this article

A Probabilistic Conductor Size Selection Framework for Active Distribution Networks

Author

Listed:
  • Lewis Waswa

    (Department of Electrical & Electronic Engineering, Stellenbosch University, Stellenbosch 7602, South Africa)

  • Munyaradzi Justice Chihota

    (Department of Electrical & Electronic Engineering, Stellenbosch University, Stellenbosch 7602, South Africa)

  • Bernard Bekker

    (Department of Electrical & Electronic Engineering, Stellenbosch University, Stellenbosch 7602, South Africa)

Abstract

With the increasing adoption of distributed energy resources (DERs) such as wind and solar photovoltaics (PV), many distribution networks have changed from passive to active. In turn, this has led to increased technical and operational challenges such as voltage issues and thermal loading in high DER penetration scenarios. These challenges have been further increased by the uncertainties arising from DER allocation. The implication of DER allocation uncertainty in the planning process is far-reaching as it affects critical planning processes, including conductor size selection (CSS). Most reported CSS methods in the literature do not include DER allocation uncertainty modeling as they are mostly deterministic and are set out as optimization problems. The methods, therefore, lack foresight on future loading conditions and cannot be used in a CSS process for feeders with high DER penetration. This paper proposes a novel input–process–output stochastic–probabilistic CSS framework for distribution feeders with DERs. The efficacy of the proposed framework is demonstrated using a low voltage feeder design case study with varying PV penetration targets, and the performance compared to deterministic–active-based estimates from our earlier work. The proposed CSS method is well-suited to the sizing of conductors for future loading conditions considering DER allocation uncertainty and will therefore be useful to planners working on new electrification projects.

Suggested Citation

  • Lewis Waswa & Munyaradzi Justice Chihota & Bernard Bekker, 2021. "A Probabilistic Conductor Size Selection Framework for Active Distribution Networks," Energies, MDPI, vol. 14(19), pages 1-19, October.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6387-:d:650752
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6387/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/19/6387/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Chengshan & Song, Guanyu & Li, Peng & Ji, Haoran & Zhao, Jinli & Wu, Jianzhong, 2017. "Optimal siting and sizing of soft open points in active electrical distribution networks," Applied Energy, Elsevier, vol. 189(C), pages 301-309.
    2. Zhenghui Zhao & Joseph Mutale, 2019. "Optimal Conductor Size Selection in Distribution Networks with High Penetration of Distributed Generation Using Adaptive Genetic Algorithm," Energies, MDPI, vol. 12(11), pages 1-20, May.
    3. Ismael, Sherif M. & Abdel Aleem, Shady H.E. & Abdelaziz, Almoataz Y. & Zobaa, Ahmed F., 2019. "State-of-the-art of hosting capacity in modern power systems with distributed generation," Renewable Energy, Elsevier, vol. 130(C), pages 1002-1020.
    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. Yih-Der Lee & Wei-Chen Lin & Jheng-Lun Jiang & Jia-Hao Cai & Wei-Tzer Huang & Kai-Chao Yao, 2021. "Optimal Individual Phase Voltage Regulation Strategies in Active Distribution Networks with High PV Penetration Using the Sparrow Search Algorithm," Energies, MDPI, vol. 14(24), pages 1-22, December.

    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. Ricardo de Oliveira & Leonardo Willer de Oliveira & Edimar José de Oliveira, 2023. "Optimization Approach for Planning Soft Open Points in a MV-Distribution System to Maximize the Hosting Capacity," Energies, MDPI, vol. 16(3), pages 1-22, January.
    2. Ibrahim Mohamed Diaaeldin & Shady H. E. Abdel Aleem & Ahmed El-Rafei & Almoataz Y. Abdelaziz & Ahmed F. Zobaa, 2020. "Enhancement of Hosting Capacity with Soft Open Points and Distribution System Reconfiguration: Multi-Objective Bilevel Stochastic Optimization," Energies, MDPI, vol. 13(20), pages 1-20, October.
    3. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.
    4. Enrico Dalla Maria & Mattia Secchi & David Macii, 2021. "A Flexible Top-Down Data-Driven Stochastic Model for Synthetic Load Profiles Generation," Energies, MDPI, vol. 15(1), pages 1-20, December.
    5. Chunyi Wang & Fengzhang Luo & Zheng Jiao & Xiaolei Zhang & Zhipeng Lu & Yanshuo Wang & Ren Zhao & Yang Yang, 2022. "An Enhanced Second-Order Cone Programming-Based Evaluation Method on Maximum Hosting Capacity of Solar Energy in Distribution Systems with Integrated Energy," Energies, MDPI, vol. 15(23), pages 1-19, November.
    6. Zhang, Shizhong & Pei, Wei & Xiao, Hao & Yang, Yanhong & Ye, Hua & Kong, Li, 2020. "Enhancing the survival time of multiple islanding microgrids through composable modular energy router after natural disasters," Applied Energy, Elsevier, vol. 270(C).
    7. Md Tariqul Islam & M. J. Hossain, 2023. "Artificial Intelligence for Hosting Capacity Analysis: A Systematic Literature Review," Energies, MDPI, vol. 16(4), pages 1-33, February.
    8. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Martin Calasan & Mihailo Micev & Ziad M. Ali & Saad Mekhilef & Hussain Bassi & Hatem Sindi & Shady H. E. Abdel Aleem, 2022. "Estimation of Parameters of Different Equivalent Circuit Models of Solar Cells and Various Photovoltaic Modules Using Hybrid Variants of Honey Badger Algorithm and Artificial Gorilla Troops Optimizer," Mathematics, MDPI, vol. 10(7), pages 1-31, March.
    9. Ramitha Dissanayake & Akila Wijethunge & Janaka Wijayakulasooriya & Janaka Ekanayake, 2022. "Optimizing PV-Hosting Capacity with the Integrated Employment of Dynamic Line Rating and Voltage Regulation," Energies, MDPI, vol. 15(22), pages 1-19, November.
    10. Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Yu, Hao & Wu, Jianzhong, 2019. "Quantified analysis method for operational flexibility of active distribution networks with high penetration of distributed generators," Applied Energy, Elsevier, vol. 239(C), pages 706-714.
    11. Yao, Hongmin & Qin, Wenping & Jing, Xiang & Zhu, Zhilong & Wang, Ke & Han, Xiaoqing & Wang, Peng, 2022. "Possibilistic evaluation of photovoltaic hosting capacity on distribution networks under uncertain environment," Applied Energy, Elsevier, vol. 324(C).
    12. C. Birk Jones & Matthew Lave & Matthew J. Reno & Rachid Darbali-Zamora & Adam Summers & Shamina Hossain-McKenzie, 2020. "Volt-Var Curve Reactive Power Control Requirements and Risks for Feeders with Distributed Roof-Top Photovoltaic Systems," Energies, MDPI, vol. 13(17), pages 1-17, August.
    13. Grzegorz Hołdyński & Zbigniew Skibko & Wojciech Walendziuk, 2024. "Power and Energy Losses in Medium-Voltage Power Grids as a Function of Current Asymmetry—An Example from Poland," Energies, MDPI, vol. 17(15), pages 1-18, July.
    14. Irina I. Picioroaga & Andrei M. Tudose & Dorian O. Sidea & Constantin Bulac, 2022. "Supply Restoration in Active Distribution Networks Based on Soft Open Points with Embedded DC Microgrids," Mathematics, MDPI, vol. 10(2), pages 1-21, January.
    15. Ahmed I. Omar & Ziad M. Ali & Mostafa Al-Gabalawy & Shady H. E. Abdel Aleem & Mujahed Al-Dhaifallah, 2020. "Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources," Mathematics, MDPI, vol. 8(7), pages 1-37, July.
    16. Costa, Vinicius Braga Ferreira da & Bonatto, Benedito Donizeti, 2023. "Cutting-edge public policy proposal to maximize the long-term benefits of distributed energy resources," Renewable Energy, Elsevier, vol. 203(C), pages 357-372.
    17. Ibrahim Mohamed Diaaeldin & Mahmoud A. Attia & Amr K. Khamees & Othman A. M. Omar & Ahmed O. Badr, 2023. "A Novel Multiobjective Formulation for Optimal Wind Speed Modeling via a Mixture Probability Density Function," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    18. Li, Yang & Yang, Zhen & Li, Guoqing & Mu, Yunfei & Zhao, Dongbo & Chen, Chen & Shen, Bo, 2018. "Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: A bi-level programming approach via real-time pricing," Applied Energy, Elsevier, vol. 232(C), pages 54-68.
    19. Andrei M. Tudose & Dorian O. Sidea & Irina I. Picioroaga & Nicolae Anton & Constantin Bulac, 2023. "Increasing Distributed Generation Hosting Capacity Based on a Sequential Optimization Approach Using an Improved Salp Swarm Algorithm," Mathematics, MDPI, vol. 12(1), pages 1-22, December.
    20. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Saad Mekhilef & Mostafa H. Mostafa & Ziad M. Ali & Shady H. E. Abdel Aleem, 2020. "Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration," Sustainability, MDPI, vol. 12(23), pages 1-25, 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:gam:jeners:v:14:y:2021:i:19:p:6387-:d:650752. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.