IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v293y2021ics0306261921004153.html
   My bibliography  Save this article

Operational flexibility of active distribution networks with the potential from data centers

Author

Listed:
  • Chen, Sirui
  • Li, Peng
  • Ji, Haoran
  • Yu, Hao
  • Yan, Jinyue
  • Wu, Jianzhong
  • Wang, Chengshan

Abstract

With the development of information technology, the scale and quantity of internet data centers (IDCs) are expanding rapidly. IDCs have emerged as the major electricity consumers in active distribution networks (ADNs), which dramatically increase the electricity load and have a significant impact on the operational flexibility of ADNs. Geographically distributed IDCs can participate in the operation of ADNs with the potential for spatio-temporal load regulation. This paper proposes flexible dispatch strategies of data centers to improve the operational flexibility of ADNs. First, a data-power model of IT equipment is proposed based on piecewise linearization to describe the power consumption characteristics of data centers. The flexible dispatch strategies for the delay-tolerant workload are further proposed from two aspects of temporal transfer and spatial allocation. Then, considering the potential for spatio-temporal load regulation, the operational flexibility analysis model with data centers is formulated to adapt to the operational requirements of ADNs in complex environments. Case studies show that through the spatio-temporal regulation of workload, the energy efficiency of IDCs can be effectively improved. The flexible dispatch of IDCs can also reduce the voltage violation and feeder load imbalance of ADNs, which can facilitate providing the high-quality power supply for IDCs.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:293:y:2021:i:c:s0306261921004153
    DOI: 10.1016/j.apenergy.2021.116935
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921004153
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.116935?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. Alaperä, Ilari & Honkapuro, Samuli & Paananen, Janne, 2018. "Data centers as a source of dynamic flexibility in smart girds," Applied Energy, Elsevier, vol. 229(C), pages 69-79.
    2. Mi, Yang & Chen, Xin & Ji, Hongpeng & Ji, Liang & Fu, Yang & Wang, Chengshan & Wang, Jianhui, 2019. "The coordinated control strategy for isolated DC microgrid based on adaptive storage adjustment without communication," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    3. Qi, Qi & Long, Chao & Wu, Jianzhong & Yu, James, 2018. "Impacts of a medium voltage direct current link on the performance of electrical distribution networks," Applied Energy, Elsevier, vol. 230(C), pages 175-188.
    4. Jin, Chaoqiang & Bai, Xuelian & Yang, Chao & Mao, Wangxin & Xu, Xin, 2020. "A review of power consumption models of servers in data centers," Applied Energy, Elsevier, vol. 265(C).
    5. Li, Jian & Jurasz, Jakub & Li, Hailong & Tao, Wen-Quan & Duan, Yuanyuan & Yan, Jinyue, 2020. "A new indicator for a fair comparison on the energy performance of data centers," Applied Energy, Elsevier, vol. 276(C).
    6. Zhao, Jinli & Zhang, Mengzhen & Yu, Hao & Ji, Haoran & Song, Guanyu & Li, Peng & Wang, Chengshan & Wu, Jianzhong, 2019. "An islanding partition method of active distribution networks based on chance-constrained programming," Applied Energy, Elsevier, vol. 242(C), pages 78-91.
    7. Chen, Min & Gao, Ciwei & Song, Meng & Chen, Songsong & Li, Dezhi & Liu, Qiang, 2020. "Internet data centers participating in demand response: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    8. Wang, Wei & Abdolrashidi, Amirali & Yu, Nanpeng & Wong, Daniel, 2019. "Frequency regulation service provision in data center with computational flexibility," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    9. 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.
    10. Nicola Jones, 2018. "How to stop data centres from gobbling up the world’s electricity," Nature, Nature, vol. 561(7722), pages 163-166, September.
    11. Cheung, Howard & Wang, Shengwei & Zhuang, Chaoqun & Gu, Jiefan, 2018. "A simplified power consumption model of information technology (IT) equipment in data centers for energy system real-time dynamic simulation," Applied Energy, Elsevier, vol. 222(C), pages 329-342.
    12. Yang, Ting & Zhao, Yingjie & Pen, Haibo & Wang, Zhaoxia, 2018. "Data center holistic demand response algorithm to smooth microgrid tie-line power fluctuation," Applied Energy, Elsevier, vol. 231(C), pages 277-287.
    13. Huang, Pei & Copertaro, Benedetta & Zhang, Xingxing & Shen, Jingchun & Löfgren, Isabelle & Rönnelid, Mats & Fahlen, Jan & Andersson, Dan & Svanfeldt, Mikael, 2020. "A review of data centers as prosumers in district energy systems: Renewable energy integration and waste heat reuse for district heating," Applied Energy, Elsevier, vol. 258(C).
    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. Lv, Chaoxian & Liang, Rui & Zhang, Ge & Zhang, Xiaotong & Jin, Wei, 2023. "Energy accommodation-oriented interaction of active distribution network and central energy station considering soft open points," Energy, Elsevier, vol. 268(C).
    2. 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).
    3. 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.
    4. Cao, Yujie & Cheng, Ming & Zhang, Sufang & Mao, Hongju & Wang, Peng & Li, Chao & Feng, Yihui & Ding, Zhaohao, 2022. "Data-driven flexibility assessment for internet data center towards periodic batch workloads," Applied Energy, Elsevier, vol. 324(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. 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).
    7. 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).
    8. Xiao, Qian & Mu, Yunfei & Jia, Hongjie & Jin, Yu & Yu, Xiaodan & Teodorescu, Remus & Guerrero, Josep M., 2022. "Novel modular multilevel converter-based five-terminal MV/LV hybrid AC/DC microgrids with improved operation capability under unbalanced power distribution," Applied Energy, Elsevier, vol. 306(PB).
    9. Liu, Xiaoou, 2024. "Research on collaborative scheduling of internet data center and regional integrated energy system based on electricity-heat-water coupling," Energy, Elsevier, vol. 292(C).
    10. Cao, Yujie & Zhang, Sufang, 2023. "Facilitating the provision of load flexibility to the power system by data centers: A hybrid research method applied to China," Utilities Policy, Elsevier, vol. 84(C).
    11. 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).
    12. Zare Ghaleh Seyyedi, Abbas & Akbari, Ehsan & Mahmoudi Rashid, Sara & Nejati, Seyed Ashkan & Gitizadeh, Mohsen, 2024. "Application of robust optimized spatiotemporal load management of data centers for renewable curtailment mitigation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    13. 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).
    14. 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).
    15. 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).
    16. Ye, Guisen & Gao, Feng & Fang, Jingyang, 2022. "A mission-driven two-step virtual machine commitment for energy saving of modern data centers through UPS and server coordinated optimizations," Applied Energy, Elsevier, vol. 322(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. Ye, Guisen & Gao, Feng & Fang, Jingyang, 2022. "A mission-driven two-step virtual machine commitment for energy saving of modern data centers through UPS and server coordinated optimizations," Applied Energy, Elsevier, vol. 322(C).
    2. 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).
    3. 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).
    4. 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).
    5. Manaserh, Yaman M. & Tradat, Mohammad I. & Bani-Hani, Dana & Alfallah, Aseel & Sammakia, Bahgat G. & Nemati, Kourosh & Seymour, Mark J., 2022. "Machine learning assisted development of IT equipment compact models for data centers energy planning," Applied Energy, Elsevier, vol. 305(C).
    6. Jerez Monsalves, Juan & Bergaentzlé, Claire & Keles, Dogan, 2023. "Impacts of flexible-cooling and waste-heat recovery from data centres on energy systems: A Danish case study," Energy, Elsevier, vol. 281(C).
    7. Li, Weiwei & Qian, Tong & Zhang, Yin & Shen, Yueqing & Wu, Chenghu & Tang, Wenhu, 2023. "Distributionally robust chance-constrained planning for regional integrated electricity–heat systems with data centers considering wind power uncertainty," Applied Energy, Elsevier, vol. 336(C).
    8. Andreea Valeria Vesa & Tudor Cioara & Ionut Anghel & Marcel Antal & Claudia Pop & Bogdan Iancu & Ioan Salomie & Vasile Teodor Dadarlat, 2020. "Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs," Sustainability, MDPI, vol. 12(4), pages 1-23, February.
    9. Isazadeh, Amin & Ziviani, Davide & Claridge, David E., 2023. "Global trends, performance metrics, and energy reduction measures in datacom facilities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
    10. Gupta, Rohit & Asgari, Sahar & Moazamigoodarzi, Hosein & Down, Douglas G. & Puri, Ishwar K., 2021. "Energy, exergy and computing efficiency based data center workload and cooling management," Applied Energy, Elsevier, vol. 299(C).
    11. Liu, Xiaoou, 2024. "Research on collaborative scheduling of internet data center and regional integrated energy system based on electricity-heat-water coupling," Energy, Elsevier, vol. 292(C).
    12. Silva, C.A. & Vilaça, R. & Pereira, A. & Bessa, R.J., 2024. "A review on the decarbonization of high-performance computing centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    13. 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).
    14. Al Kez, Dlzar & Foley, Aoife M. & Ahmed, Faraedoon W. & O'Malley, Mark & Muyeen, S.M., 2021. "Potential of data centers for fast frequency response services in synchronously isolated power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    15. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    16. Hyvönen, Johannes & Mori, Taro & Saunavaara, Juha & Hiltunen, Pauli & Pärssinen, Matti & Syri, Sanna, 2024. "Potential of solar photovoltaics and waste heat utilization in cold climate data centers. Case study: Finland and northern Japan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
    17. Ieva Pakere & Kirils Goncarovs & Armands Grāvelsiņš & Marita Agate Zirne, 2024. "Dynamic Modelling of Data Center Waste Heat Potential Integration in District Heating in Latvia," Energies, MDPI, vol. 17(2), pages 1-13, January.
    18. Li, Jian & Jurasz, Jakub & Li, Hailong & Tao, Wen-Quan & Duan, Yuanyuan & Yan, Jinyue, 2020. "A new indicator for a fair comparison on the energy performance of data centers," Applied Energy, Elsevier, vol. 276(C).
    19. Cao, Yujie & Cao, Fang & Wang, Yajing & Wang, Jianxiao & Wu, Lei & Ding, Zhaohao, 2024. "Managing data center cluster as non-wire alternative: A case in balancing market," Applied Energy, Elsevier, vol. 360(C).
    20. Fan, Chengliang & Hinkelman, Kathryn & Fu, Yangyang & Zuo, Wangda & Huang, Sen & Shi, Chengnan & Mamaghani, Nasim & Faulkner, Cary & Zhou, Xiaoqing, 2021. "Open-source Modelica models for the control performance simulation of chiller plants with water-side economizer," Applied Energy, Elsevier, vol. 299(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:eee:appene:v:293:y:2021:i:c:s0306261921004153. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.