IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i15p3623-d1441391.html
   My bibliography  Save this article

Collaborative Planning of Distribution Network, Data Centres and Renewable Energy in the Power Distribution IoT via Interval Optimization

Author

Listed:
  • Lei Su

    (State Grid Hubei Electric Power Research Institute, Wuhan 430074, China)

  • Wenxiang Wu

    (State Key Laboratory of Advanced Power Transmission Technology, State Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, China)

  • Wanli Feng

    (State Grid Hubei Electric Power Research Institute, Wuhan 430074, China)

  • Junda Qin

    (State Key Laboratory of Advanced Power Transmission Technology, State Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, China)

  • Yuqi Ao

    (State Grid Hubei Electric Power Research Institute, Wuhan 430074, China)

Abstract

With the development of the power distribution Internet of Things (IoT), the escalating power demand of data centers (DCs) poses a formidable challenge to the operation of distribution networks (DNs). To address this, the present study considers the operational flexibility of DCs and its impact on DNs and constructs a collaborative planning framework of DCs, renewable energy sources (RESs), and DNs. This framework employs the interval optimization method to mitigate uncertainties associated with RES output, wholesale market prices, carbon emission factors, power demand, and workloads, and the collaborative planning model is transformed into an interval optimization problem (IOP). On this basis, a novel hybrid solution method is developed to solve the IOP, where an interval order relation and interval possibility method are employed to transform the IOP into a deterministic optimization problem, and an improved integrated particle swarm optimization algorithm and gravitational search algorithm (IIPSOA-GSA) is presented to solve it. Finally, the proposed planning framework and solution algorithm are directly integrated into an actual integrated system with a distribution network and DC to verify the effectiveness of the proposed method.

Suggested Citation

  • Lei Su & Wenxiang Wu & Wanli Feng & Junda Qin & Yuqi Ao, 2024. "Collaborative Planning of Distribution Network, Data Centres and Renewable Energy in the Power Distribution IoT via Interval Optimization," Energies, MDPI, vol. 17(15), pages 1-26, July.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3623-:d:1441391
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/15/3623/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/15/3623/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zeng, Bo & Zhang, Weixiang & Hu, Pinduan & Sun, Jing & Gong, Dunwei, 2023. "Synergetic renewable generation allocation and 5G base station placement for decarbonizing development of power distribution system: A multi-objective interval evolutionary optimization approach," Applied Energy, Elsevier, vol. 351(C).
    2. Chen, Sirui & Li, Peng & Ji, Haoran & Yu, Hao & Yan, Jinyue & Wu, Jianzhong & Wang, Chengshan, 2021. "Operational flexibility of active distribution networks with the potential from data centers," Applied Energy, Elsevier, vol. 293(C).
    3. Liu, Wenyu & Yan, Yuejun & Sun, Yimeng & Mao, Hongju & Cheng, Ming & Wang, Peng & Ding, Zhaohao, 2023. "Online job scheduling scheme for low-carbon data center operation: An information and energy nexus perspective," Applied Energy, Elsevier, vol. 338(C).
    4. Wan, Tong & Tao, Yuechuan & Qiu, Jing & Lai, Shuying, 2023. "Internet data centers participating in electricity network transition considering carbon-oriented demand response," Applied Energy, Elsevier, vol. 329(C).
    5. Wang, Jiangjiang & Deng, Hongda & Liu, Yi & Guo, Zeqing & Wang, Yongzhen, 2023. "Coordinated optimal scheduling of integrated energy system for data center based on computing load shifting," Energy, Elsevier, vol. 267(C).
    6. Lian, Yicheng & Li, Yuanzheng & Zhao, Yong & Yu, Chaofan & Zhao, Tianyang & Wu, Lei, 2023. "Robust multi-objective optimization for islanded data center microgrid operations," Applied Energy, Elsevier, vol. 330(PB).
    7. Koot, Martijn & Wijnhoven, Fons, 2021. "Usage impact on data center electricity needs: A system dynamic forecasting model," Applied Energy, Elsevier, vol. 291(C).
    8. Su, Yongxin & Zhou, Yao & Tan, Mao, 2020. "An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response," Applied Energy, Elsevier, vol. 260(C).
    9. Jiang, Tao & Li, Xue & Kou, Xiao & Zhang, Rufeng & Tian, Guoda & Li, Fangxing, 2022. "Available transfer capability evaluation in electricity-dominated integrated hybrid energy systems with uncertain wind power: An interval optimization solution," Applied Energy, Elsevier, vol. 314(C).
    10. Qu, Shengli & Duan, Kaiwen & Guo, Yuxiang & Feng, Yiwei & Wang, Chuang & Xing, Ziwen, 2024. "Real-time optimization of the liquid-cooled data center based on cold plates under different ambient temperatures and thermal loads," Applied Energy, Elsevier, vol. 363(C).
    Full references (including those not matched with items on IDEAS)

    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. Xiao, Jiang-Wen & Yang, Yan-Bing & Cui, Shichang & Wang, Yan-Wu, 2023. "Cooperative online schedule of interconnected data center microgrids with shared energy storage," Energy, Elsevier, vol. 285(C).
    2. Han, Ouzhu & Ding, Tao & Yang, Miao & Jia, Wenhao & He, Xinran & Ma, Zhoujun, 2024. "A novel 4-level joint optimal dispatch for demand response of data centers with district autonomy realization," Applied Energy, Elsevier, vol. 358(C).
    3. Wang, Kaifeng & Ye, Lin & Yang, Shihui & Deng, Zhanfeng & Song, Jieying & Li, Zhuo & Zhao, Yongning, 2023. "A hierarchical dispatch strategy of hybrid energy storage system in internet data center with model predictive control," Applied Energy, Elsevier, vol. 331(C).
    4. Ji, Haoran & Chen, Sirui & Yu, Hao & Li, Peng & Yan, Jinyue & Song, Jieying & Wang, Chengshan, 2022. "Robust operation for minimizing power consumption of data centers with flexible substation integration," Energy, Elsevier, vol. 248(C).
    5. Chen, Boyu & Che, Yanbo & Zheng, Zhihao & Zhao, Shuaijun, 2023. "Multi-objective robust optimal bidding strategy for a data center operator based on bi-level optimization," Energy, Elsevier, vol. 269(C).
    6. Yuyang Zhao & Yifan Wei & Shuaiqi Zhang & Yingjun Guo & Hexu Sun, 2024. "Multi-Objective Robust Optimization of Integrated Energy System with Hydrogen Energy Storage," Energies, MDPI, vol. 17(5), pages 1-20, February.
    7. Wang, Zhiying & Wang, Yang & Ji, Haoran & Hasanien, Hany M. & Zhao, Jinli & Yu, Lei & He, Jiafeng & Yu, Hao & Li, Peng, 2024. "Distributionally robust planning for data center park considering operational economy and reliability," Energy, Elsevier, vol. 290(C).
    8. Chen, Xiaoyuan & Jiang, Shan & Chen, Yu & Zou, Zhice & Shen, Boyang & Lei, Yi & Zhang, Donghui & Zhang, Mingshun & Gou, Huayu, 2022. "Energy-saving superconducting power delivery from renewable energy source to a 100-MW-class data center," Applied Energy, Elsevier, vol. 310(C).
    9. An, Su & Wang, Honglei & Leng, Xiaoxia, 2022. "Optimal operation of multi-micro energy grids under distribution network in Southwest China," Applied Energy, Elsevier, vol. 309(C).
    10. Liu, Wenyu & Yan, Yuejun & Sun, Yimeng & Mao, Hongju & Cheng, Ming & Wang, Peng & Ding, Zhaohao, 2023. "Online job scheduling scheme for low-carbon data center operation: An information and energy nexus perspective," Applied Energy, Elsevier, vol. 338(C).
    11. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    12. Tsoumalis, Georgios I. & Bampos, Zafeirios N. & Biskas, Pandelis N. & Keranidis, Stratos D. & Symeonidis, Polychronis A. & Voulgarakis, Dimitrios K., 2022. "A novel system for providing explicit demand response from domestic natural gas boilers," Applied Energy, Elsevier, vol. 317(C).
    13. Bao, Minglei & Hui, Hengyu & Ding, Yi & Sun, Xiaocong & Zheng, Chenghang & Gao, Xiang, 2023. "An efficient framework for exploiting operational flexibility of load energy hubs in risk management of integrated electricity-gas systems," Applied Energy, Elsevier, vol. 338(C).
    14. Babasola Osibo & Simisola Adamo, 2023. "Data Centers and Green Energy: Paving the Way for a Sustainable Digital Future," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 12(11), pages 15-30, November.
    15. Du, Juntao & Shen, Zhiyang & Song, Malin & Zhang, Linda, 2023. "Nexus between digital transformation and energy technology innovation: An empirical test of A-share listed enterprises," Energy Economics, Elsevier, vol. 120(C).
    16. Mahtab Kaffash & Glenn Ceusters & Geert Deconinck, 2021. "Interval Optimization to Schedule a Multi-Energy System with Data-Driven PV Uncertainty Representation," Energies, MDPI, vol. 14(10), pages 1-20, May.
    17. Seyfi, Mohammad & Mehdinejad, Mehdi & Mohammadi-Ivatloo, Behnam & Shayanfar, Heidarali, 2022. "Deep learning-based scheduling of virtual energy hubs with plug-in hybrid compressed natural gas-electric vehicles," Applied Energy, Elsevier, vol. 321(C).
    18. Yang, Xiaohui & Wang, Xiaopeng & Deng, Yeheng & Mei, Linghao & Deng, Fuwei & Zhang, Zhonglian, 2023. "Integrated energy system scheduling model based on non-complete interval multi-objective fuzzy optimization," Renewable Energy, Elsevier, vol. 218(C).
    19. 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).
    20. Cho, Jinkyun, 2024. "Optimal supply air temperature with respect to data center operational stability and energy efficiency in a row-based cooling system under fault conditions," Energy, Elsevier, vol. 288(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:17:y:2024:i:15:p:3623-:d:1441391. 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.