IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i8p1527-d225171.html
   My bibliography  Save this article

Distributed Absorption and Half-Search Approach for Economic Dispatch Problem in Smart Grids

Author

Listed:
  • Bo Li

    (School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Panpan Zhang

    (School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Xiangjun Li

    (State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems, Energy Storage and Electrical Engineering Department, China Electric Power Research Institute, Beijing 100192, China
    Contemporary Amperex Technology Limited (Qinghai), Xining 810021, Qinghai, China)

  • Shengxian Cao

    (School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China)

Abstract

The economic dispatch problem (EDP) is a significant class of optimization issues in the power system, which works on minimizing the total cost when generating a certain amount of power. A novel distributed approach for EDP is proposed in this paper. The presented approach consists of two steps. The first step, named absorption search, is to simplify the network structure through absorption searching. A flooding-based consensus approach is applied in the first step, which can be used to achieve consensus information among nodes. After the first step, only the generation nodes are kept in the network. The data collection can be completed by local computation and communication between neighbors. The first step can be considered as the stage of gathering information. In the second step, a distributed half-search algorithm makes the nodes obtain the final optimal solution in a distributed way. The results on three case studies demonstrate that the proposed approach is highly effective for solving the EDP.

Suggested Citation

  • Bo Li & Panpan Zhang & Xiangjun Li & Shengxian Cao, 2019. "Distributed Absorption and Half-Search Approach for Economic Dispatch Problem in Smart Grids," Energies, MDPI, vol. 12(8), pages 1-21, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1527-:d:225171
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/8/1527/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/8/1527/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Azizivahed, Ali & Narimani, Hossein & Fathi, Mehdi & Naderi, Ehsan & Safarpour, Hamid Reza & Narimani, Mohammad Rasoul, 2018. "Multi-objective dynamic distribution feeder reconfiguration in automated distribution systems," Energy, Elsevier, vol. 147(C), pages 896-914.
    2. Bo Li & Yudong Wang & Jian Li & Shengxian Cao, 2018. "A Fully Distributed Approach for Economic Dispatch Problem of Smart Grid," Energies, MDPI, vol. 11(8), pages 1-21, August.
    3. Narimani, Hossein & Razavi, Seyed-Ehsan & Azizivahed, Ali & Naderi, Ehsan & Fathi, Mehdi & Ataei, Mohammad H. & Narimani, Mohammad Rasoul, 2018. "A multi-objective framework for multi-area economic emission dispatch," Energy, Elsevier, vol. 154(C), pages 126-142.
    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. Ke Jiang & Feng Wu & Xuanjun Zong & Linjun Shi & Keman Lin, 2019. "Distributed Dynamic Economic Dispatch of an Isolated AC/DC Hybrid Microgrid Based on a Finite-Step Consensus Algorithm," Energies, MDPI, vol. 12(24), pages 1-18, December.
    2. Taha Selim Ustun & S. M. Suhail Hussain, 2019. "Secure Communication Modeling for Microgrid Energy Management System: Development and Application," Energies, MDPI, vol. 13(1), pages 1-14, 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. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies," Applied Energy, Elsevier, vol. 239(C), pages 356-372.
    2. Azad-Farsani, Ehsan & Sardou, Iman Goroohi & Abedini, Saeed, 2021. "Distribution Network Reconfiguration based on LMP at DG connected busses using game theory and self-adaptive FWA," Energy, Elsevier, vol. 215(PB).
    3. Zhang, Yue & Zhang, Qi & Farnoosh, Arash & Chen, Siyuan & Li, Yan, 2019. "GIS-Based Multi-Objective Particle Swarm Optimization of charging stations for electric vehicles," Energy, Elsevier, vol. 169(C), pages 844-853.
    4. Li, J.Y. & Chen, J.J. & Wang, Y.X. & Chen, W.G., 2024. "Combining multi-step reconfiguration with many-objective reduction as iterative bi-level scheduling for stochastic distribution network," Energy, Elsevier, vol. 290(C).
    5. Mostafa Abdo & Salah Kamel & Mohamed Ebeed & Juan Yu & Francisco Jurado, 2018. "Solving Non-Smooth Optimal Power Flow Problems Using a Developed Grey Wolf Optimizer," Energies, MDPI, vol. 11(7), pages 1-16, June.
    6. Basu, M., 2023. "Multi-county combined heat and power dynamic economic emission dispatch incorporating electric vehicle parking lot," Energy, Elsevier, vol. 275(C).
    7. Hossein Lotfi & Mohammad Hasan Nikkhah, 2023. "Presenting a Novel Evolutionary Method for Reserve Constrained Multi-Area Economic/Emission Dispatch Problem," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    8. Hossein Lotfi, 2022. "A Multiobjective Evolutionary Approach for Solving the Multi-Area Dynamic Economic Emission Dispatch Problem Considering Reliability Concerns," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
    9. Meng, Anbo & Zeng, Cong & Xu, Xuancong & Ding, Weifeng & Liu, Shiyun & Chen, De & Yin, Hao, 2022. "Decentralized power economic dispatch by distributed crisscross optimization in multi-agent system," Energy, Elsevier, vol. 246(C).
    10. Li Han & Rongchang Zhang & Xuesong Wang & Yu Dong, 2018. "Multi-Time Scale Rolling Economic Dispatch for Wind/Storage Power System Based on Forecast Error Feature Extraction," Energies, MDPI, vol. 11(8), pages 1-27, August.
    11. Narimani, Hossein & Razavi, Seyed-Ehsan & Azizivahed, Ali & Naderi, Ehsan & Fathi, Mehdi & Ataei, Mohammad H. & Narimani, Mohammad Rasoul, 2018. "A multi-objective framework for multi-area economic emission dispatch," Energy, Elsevier, vol. 154(C), pages 126-142.
    12. Wang, Hong-Jiang & Pan, Jeng-Shyang & Nguyen, Trong-The & Weng, Shaowei, 2022. "Distribution network reconfiguration with distributed generation based on parallel slime mould algorithm," Energy, Elsevier, vol. 244(PB).
    13. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun & Wu, Jiahui & Fan, Xiaochao & Xu, Qidan, 2020. "Dynamic environmental economic dispatch of hybrid renewable energy systems based on tradable green certificates," Energy, Elsevier, vol. 193(C).
    14. Sharifian, Yeganeh & Abdi, Hamdi, 2024. "Multi-area economic dispatch problem: Methods, uncertainties, and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    15. Yue Cao & Tao Li & Tianyu He & Yuwei Wei & Ming Li & Fengqi Si, 2022. "Multiobjective Load Dispatch for Coal-Fired Power Plants under Renewable-Energy Accommodation Based on a Nondominated-Sorting Grey Wolf Optimizer Algorithm," Energies, MDPI, vol. 15(8), pages 1-19, April.
    16. Yang, Wenqiang & Zhu, Xinxin & Xiao, Qinge & Yang, Zhile, 2023. "Enhanced multi-objective marine predator algorithm for dynamic economic-grid fluctuation dispatch with plug-in electric vehicles," Energy, Elsevier, vol. 282(C).
    17. Lin, Zhenjia & Chen, Haoyong & Wu, Qiuwei & Li, Weiwei & Li, Mengshi & Ji, Tianyao, 2020. "Mean-tracking model based stochastic economic dispatch for power systems with high penetration of wind power," Energy, Elsevier, vol. 193(C).
    18. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    19. Wang, Xuebin & Chang, Jianxia & Meng, Xuejiao & Wang, Yimin, 2018. "Short-term hydro-thermal-wind-photovoltaic complementary operation of interconnected power systems," Applied Energy, Elsevier, vol. 229(C), pages 945-962.
    20. Tolabi, H.B. & Ara, A. Lashkar & Hosseini, R., 2020. "A new thief and police algorithm and its application in simultaneous reconfiguration with optimal allocation of capacitor and distributed generation units," Energy, Elsevier, vol. 203(C).

    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:12:y:2019:i:8:p:1527-:d:225171. 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.