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Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss

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  • Li, Weiwei
  • Qian, Tong
  • Zhao, Wei
  • Huang, Wenwei
  • Zhang, Yin
  • Xie, Xuehua
  • Tang, Wenhu

Abstract

Recently, waste heat recovery has enabled data centers to serve as energy prosumers with flexible features that play essential roles in the coordination operation of integrated electricity–heat systems (IEHSs). The energy hub, as a critical component of IEHSs, provides a promising opportunity to improve energy efficiency. In this paper, the decentralized coordination optimization for IEHSs with data centers is explored to protect the confidential information of different entities. First, a novel data center based energy hub (DCEH) model is developed, where energy conversion, consumption and storage present high flexibility. Especially, in addition to heat recovery, several other controllable operational characteristics of a single data center are considered, involving servers, workloads and indoor temperature. Then, the coordination optimization model of IEHSs with DCEH (IEHSs-DCEH) is constructed by incorporating energy consumption cost and carbon emission, where the energy networks of IEHSs are considered. Moreover, a learning-aided relaxed alternating direction method of multipliers (LR-ADMM) algorithm is proposed to solve the dispatching model of IEHSs-DCEH considering communication packet loss. The proposed LR-ADMM algorithm embeds a momentum extrapolation based prediction technique, which can obtain the predicted value of missing boundary information without adding computational burden, even in continuous packet losses. Simulation results demonstrate that the developed coordination dispatching model can achieve higher economic and environmental benefits than the reference one that ignores data centers’ flexibility. Additionally, the proposed LR-ADMM algorithm with proper prediction factors exhibits a faster convergence rate and robustness hedging against packet losses compared to the ADMM and relaxed ADMM approaches.

Suggested Citation

  • Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).
    • Handle: RePEc:eee:appene:v:350:y:2023:i:c:s0306261923009509
    DOI: 10.1016/j.apenergy.2023.121586
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    References listed on IDEAS

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    1. Huang, Qionghai & Shao, Shuangquan & Zhang, Hainan & Tian, Changqing, 2019. "Development and composition of a data center heat recovery system and evaluation of annual operation performance," Energy, Elsevier, vol. 189(C).
    2. Liu, Xuezhi & Wu, Jianzhong & Jenkins, Nick & Bagdanavicius, Audrius, 2016. "Combined analysis of electricity and heat networks," Applied Energy, Elsevier, vol. 162(C), pages 1238-1250.
    3. Wahlroos, Mikko & Pärssinen, Matti & Manner, Jukka & Syri, Sanna, 2017. "Utilizing data center waste heat in district heating – Impacts on energy efficiency and prospects for low-temperature district heating networks," Energy, Elsevier, vol. 140(P1), pages 1228-1238.
    4. Zhong, Xiaoqing & Zhong, Weifeng & Liu, Yi & Yang, Chao & Xie, Shengli, 2023. "A communication-efficient coalition graph game-based framework for electricity and carbon trading in networked energy hubs," Applied Energy, Elsevier, vol. 329(C).
    5. 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).
    6. Zhang, Tong & Li, Zhigang & Wu, Q.H. & Zhou, Xiaoxin, 2019. "Decentralized state estimation of combined heat and power systems using the asynchronous alternating direction method of multipliers," Applied Energy, Elsevier, vol. 248(C), pages 600-613.
    7. Qian, Tong & Chen, Xingyu & Xin, Yanli & Tang, Wenhu & Wang, Lixiao, 2022. "Resilient decentralized optimization of chance constrained electricity-gas systems over lossy communication networks," Energy, Elsevier, vol. 239(PB).
    8. Skalyga, Mikhail & Amelin, Mikael & Wu, Qiuwei & Söder, Lennart, 2023. "Distributionally robust day-ahead combined heat and power plants scheduling with Wasserstein Metric," Energy, Elsevier, vol. 269(C).
    9. Fan, Wei & Ju, Liwei & Tan, Zhongfu & Li, Xiangguang & Zhang, Amin & Li, Xudong & Wang, Yueping, 2023. "Two-stage distributionally robust optimization model of integrated energy system group considering energy sharing and carbon transfer," Applied Energy, Elsevier, vol. 331(C).
    10. Najafi, Arsalan & Homaee, Omid & Jasiński, Michał & Pourakbari-Kasmaei, Mahdi & Lehtonen, Matti & Leonowicz, Zbigniew, 2023. "Participation of hydrogen-rich energy hubs in day-ahead and regulation markets: A hybrid stochastic-robust model," Applied Energy, Elsevier, vol. 339(C).
    11. Zheng, J.H. & Xiao, Wenting & Wu, C.Q. & Li, Zhigang & Wang, L.X. & Wu, Q.H., 2023. "A gradient descent direction based-cumulants method for probabilistic energy flow analysis of individual-based integrated energy systems," Energy, Elsevier, vol. 265(C).
    12. Han, Ouzhu & Ding, Tao & Mu, Chenggang & Jia, Wenhao & Ma, Zhoujun, 2023. "Waste heat reutilization and integrated demand response for decentralized optimization of data centers," Energy, Elsevier, vol. 264(C).
    13. Maurer, Jona & Tschuch, Nicolai & Krebs, Stefan & Bhattacharya, Kankar & Cañizares, Claudio & Hohmann, Sören, 2023. "Toward transactive control of coupled electric power and district heating networks," Applied Energy, Elsevier, vol. 332(C).
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