IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i10p2830-d177010.html
   My bibliography  Save this article

Hierarchical Scheduling Scheme for AC/DC Hybrid Active Distribution Network Based on Multi-Stakeholders

Author

Listed:
  • Chang Ye

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Shihong Miao

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yaowang Li

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Chao Li

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Lixing Li

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

This paper presents a hierarchical multi-stage scheduling scheme for the AC/DC hybrid active distribution network (ADN). The load regulation center (LRC) is considered in the developed scheduling strategy, as well as the AC and DC sub-network operators. They are taken to be different stakeholders. To coordinate the interests of all stakeholders, a two-level optimization model is established. The flexible loads are dispatched by LRC in the upper-level optimization model, the objective of which is minimizing the loss of the entire distribution network. The lower-level optimization is divided into two sub-optimal models, and they are carried out to minimize the operating costs of the AC/DC sub-network operators respectively. This two-level model avoids the difficulty of solving multi-objective optimization and can clarify the role of various stakeholders in the system scheduling. To solve the model effectively, a discrete wind-driven optimization (DWDO) algorithm is proposed. Then, considering the combination of the proposed DWDO algorithm and the YALMIP toolbox, a hierarchical optimization algorithm (HOA) is developed. The HOA can obtain the overall optimization result of the system through the iterative optimization of the upper and lower levels. Finally, the simulation results verify the effectiveness of the proposed scheduling scheme.

Suggested Citation

  • Chang Ye & Shihong Miao & Yaowang Li & Chao Li & Lixing Li, 2018. "Hierarchical Scheduling Scheme for AC/DC Hybrid Active Distribution Network Based on Multi-Stakeholders," Energies, MDPI, vol. 11(10), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2830-:d:177010
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/10/2830/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/10/2830/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mahmood Hosseini Imani & Shaghayegh Zalzar & Amir Mosavi & Shahaboddin Shamshirband, 2018. "Strategic Behavior of Retailers for Risk Reduction and Profit Increment via Distributed Generators and Demand Response Programs," Energies, MDPI, vol. 11(6), pages 1-24, June.
    2. Li, Yang & Li, Yahui & Li, Guoqing & Zhao, Dongbo & Chen, Chen, 2018. "Two-stage multi-objective OPF for AC/DC grids with VSC-HVDC: Incorporating decisions analysis into optimization process," Energy, Elsevier, vol. 147(C), pages 286-296.
    3. Unamuno, Eneko & Barrena, Jon Andoni, 2015. "Hybrid ac/dc microgrids—Part I: Review and classification of topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1251-1259.
    4. Aouss Gabash & Pu Li, 2016. "On Variable Reverse Power Flow-Part I: Active-Reactive Optimal Power Flow with Reactive Power of Wind Stations," Energies, MDPI, vol. 9(3), pages 1-12, February.
    5. Qiu, Haifeng & Gu, Wei & Pan, Jing & Xu, Bin & Xu, Yinliang & Fan, Miao & Wu, Zhi, 2018. "Multi-interval-uncertainty constrained robust dispatch for AC/DC hybrid microgrids with dynamic energy storage degradation," Applied Energy, Elsevier, vol. 228(C), pages 205-214.
    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. Zhou, Yulu & Zhang, Jingrui, 2020. "Three-layer day-ahead scheduling for active distribution network by considering multiple stakeholders," Energy, Elsevier, vol. 207(C).
    2. Zhang, Jingrui & Zhou, Yulu & Li, Zhuoyun & Cai, Junfeng, 2021. "Three-level day-ahead optimal scheduling framework considering multi-stakeholders in active distribution networks: Up-to-down approach," Energy, Elsevier, vol. 219(C).
    3. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.

    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. Alexandra Blanch-Fortuna & David Zambrano-Prada & Oswaldo López-Santos & Abdelali El Aroudi & Luis Vázquez-Seisdedos & Luis Martinez-Salamero, 2024. "Hierarchical Control of Power Distribution in the Hybrid Energy Storage System of an Ultrafast Charging Station for Electric Vehicles," Energies, MDPI, vol. 17(6), pages 1-20, March.
    2. Mohagheghi, Erfan & Gabash, Aouss & Alramlawi, Mansour & Li, Pu, 2018. "Real-time optimal power flow with reactive power dispatch of wind stations using a reconciliation algorithm," Renewable Energy, Elsevier, vol. 126(C), pages 509-523.
    3. Aouss Gabash & Pu Li, 2016. "On Variable Reverse Power Flow-Part II: An Electricity Market Model Considering Wind Station Size and Location," Energies, MDPI, vol. 9(4), pages 1-13, March.
    4. Li, Yang & Wang, Jinlong & Zhao, Dongbo & Li, Guoqing & Chen, Chen, 2018. "A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making," Energy, Elsevier, vol. 162(C), pages 237-254.
    5. Seok-Ju Lee & Hae-Jin Sung & Minwon Park & DuYean Won & Jaeun Yoo & Hyung Suk Yang, 2019. "Analysis of the Temperature Characteristics of Three-Phase Coaxial Superconducting Power Cable according to a Liquid Nitrogen Circulation Method for Real-Grid Application in Korea," Energies, MDPI, vol. 12(9), pages 1-11, May.
    6. Bustos, Cristian & Watts, David, 2017. "Novel methodology for microgrids in isolated communities: Electricity cost-coverage trade-off with 3-stage technology mix, dispatch & configuration optimizations," Applied Energy, Elsevier, vol. 195(C), pages 204-221.
    7. Donghui Wang & Chunming Liu, 2019. "Combination Optimization Configuration Method of Capacitance and Resistance Devices for Suppressing DC Bias in Transformers," Energies, MDPI, vol. 12(9), pages 1-13, May.
    8. Vitor Monteiro & Julio S. Martins & João Carlos Aparício Fernandes & Joao L. Afonso, 2021. "Review of a Disruptive Vision of Future Power Grids: A New Path Based on Hybrid AC/DC Grids and Solid-State Transformers," Sustainability, MDPI, vol. 13(16), pages 1-25, August.
    9. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    10. Houssem Rafik Al-Hana Bouchekara & Mohammad Shoaib Shahriar & Muhammad Sharjeel Javaid & Yusuf Abubakar Sha’aban & Makbul Anwari Muhammad Ramli, 2021. "Multi-Objective Optimization of a Hybrid Nanogrid/Microgrid: Application to Desert Camps in Hafr Al-Batin," Energies, MDPI, vol. 14(5), pages 1-24, February.
    11. 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.
    12. Saeed Nosratabadi & Amir Mosavi & Shahaboddin Shamshirband & Edmundas Kazimieras Zavadskas & Andry Rakotonirainy & Kwok Wing Chau, 2019. "Sustainable Business Models: A Review," Sustainability, MDPI, vol. 11(6), pages 1-30, March.
    13. Henrique Pires Corrêa & Rafael Ribeiro de Carvalho Vaz & Flávio Henrique Teles Vieira & Sérgio Granato de Araújo, 2019. "Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation," Energies, MDPI, vol. 12(11), pages 1-26, May.
    14. Zheng, Lingwei & Zhou, Xingqiu & Qiu, Qi & Yang, Lan, 2020. "Day-ahead optimal dispatch of an integrated energy system considering time-frequency characteristics of renewable energy source output," Energy, Elsevier, vol. 209(C).
    15. Simon Pezzutto & Giulio Quaglini & Andrea Zambito & Antonio Novelli & Philippe Riviere & Lukas Kranzl & Eric Wilczynski, 2022. "Potential Evolution of the Cooling Market in the EU27+UK: An Outlook until 2030," Sustainability, MDPI, vol. 14(8), pages 1-25, April.
    16. Arcos-Aviles, Diego & Pascual, Julio & Guinjoan, Francesc & Marroyo, Luis & Sanchis, Pablo & Marietta, Martin P., 2017. "Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting," Applied Energy, Elsevier, vol. 205(C), pages 69-84.
    17. David Sebastian Stock & Francesco Sala & Alberto Berizzi & Lutz Hofmann, 2018. "Optimal Control of Wind Farms for Coordinated TSO-DSO Reactive Power Management," Energies, MDPI, vol. 11(1), pages 1-25, January.
    18. Sen Guo & Wenyue Zhang & Xiao Gao, 2020. "Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method," Sustainability, MDPI, vol. 12(5), pages 1-21, March.
    19. Barelli, L. & Bidini, G. & Pelosi, D. & Ciupageanu, D.A. & Cardelli, E. & Castellini, S. & Lăzăroiu, G., 2020. "Comparative analysis of AC and DC bus configurations for flywheel-battery HESS integration in residential micro-grids," Energy, Elsevier, vol. 204(C).
    20. Nosratabadi, Saeed & Mosavi, Amir & Shamshirband, Shahaboddin & Zavadskas, Edmundas Kazimieras & Rakotonirainy, Andry & Chau, Kwok Wing, 2020. "Sustainable Business Models: A Review," OSF Preprints u4xw3, Center for Open Science.

    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:11:y:2018:i:10:p:2830-:d:177010. 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.