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Collaborative energy management of interconnected regional integrated energy systems considering spatio-temporal characteristics

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  • Zhao, Wanbing
  • Chang, Weiguang
  • Yang, Qiang

Abstract

Multi-regional integrated energy systems (MRIES), which encompass renewable distributed generation (RDG) and electric vehicles (EV) dispersed across multiple regions, are pivotal for promoting low-carbon energy supplies, offering both economic and environmental benefits. However, the complexity introduced by diverse energy conversions and spatiotemporal coupling in MRIES poses significant challenges for energy management. This paper introduces a novel low-carbon energy management framework (EMF) for multi-regional IES, based on spatiotemporal correlations and considering three-dimensional (3D) integrated demand-side response (IDR). The proposed framework employs a novel Cross-Gated Spatio-Temporal Graph Convolutional Network (CGSTG) to achieve high-precision joint power forecasting separately for the RDG and multi-type loads. In the day-ahead stage, 3D IDR involving flexible loads, e.g., EVs, is considered with multi-regional IES sharing electricity and heat. By engaging in IDR across the temporal (horizontal), spatial (depth), and energy conversion (vertical) dimensions, each IES can enhance its coordinated scheduling capability and operational economy. During the intra-day stage, rolling optimization is performed based on the model predictive control (MPC) framework, incorporating a ladder-type carbon trading mechanism (CTM). Comparative experiments demonstrate that the proposed method can effectively reduce operational costs and carbon emissions with significant improvement of coordinated scheduling capability, leading to economic and environmental benefits of MRIES.

Suggested Citation

  • Zhao, Wanbing & Chang, Weiguang & Yang, Qiang, 2024. "Collaborative energy management of interconnected regional integrated energy systems considering spatio-temporal characteristics," Renewable Energy, Elsevier, vol. 235(C).
    • Handle: RePEc:eee:renene:v:235:y:2024:i:c:s0960148124014319
    DOI: 10.1016/j.renene.2024.121363
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    References listed on IDEAS

    as
    1. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    2. Wang, Rutian & Wen, Xiangyun & Wang, Xiuyun & Fu, Yanbo & Zhang, Yu, 2022. "Low carbon optimal operation of integrated energy system based on carbon capture technology, LCA carbon emissions and ladder-type carbon trading," Applied Energy, Elsevier, vol. 311(C).
    3. Dong, Haiyan & Fu, Yanbo & Jia, Qingquan & Zhang, Tie & Meng, Dequn, 2023. "Low carbon optimization of integrated energy microgrid based on life cycle analysis method and multi time scale energy storage," Renewable Energy, Elsevier, vol. 206(C), pages 60-71.
    4. Han, Shuang & Qiao, Yan-hui & Yan, Jie & Liu, Yong-qian & Li, Li & Wang, Zheng, 2019. "Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network," Applied Energy, Elsevier, vol. 239(C), pages 181-191.
    5. Chengqing, Yu & Guangxi, Yan & Chengming, Yu & Yu, Zhang & Xiwei, Mi, 2023. "A multi-factor driven spatiotemporal wind power prediction model based on ensemble deep graph attention reinforcement learning networks," Energy, Elsevier, vol. 263(PE).
    6. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    7. Zhang, Gang & Wen, Jiaxing & Xie, Tuo & Zhang, Kaoshe & Jia, Rong, 2023. "Bi-layer economic scheduling for integrated energy system based on source-load coordinated carbon reduction," Energy, Elsevier, vol. 280(C).
    8. Zhang, Yagang & Pan, Zhiya & Wang, Hui & Wang, Jingchao & Zhao, Zheng & Wang, Fei, 2023. "Achieving wind power and photovoltaic power prediction: An intelligent prediction system based on a deep learning approach," Energy, Elsevier, vol. 283(C).
    9. Lyu, Xiangmei & Liu, Tianqi & Liu, Xuan & He, Chuan & Nan, Lu & Zeng, Hong, 2023. "Low-carbon robust economic dispatch of park-level integrated energy system considering price-based demand response and vehicle-to-grid," Energy, Elsevier, vol. 263(PB).
    10. Zhang, Zhaoyan & Jiang, Ping & Liu, Zhibin & Fu, Lei & Wang, Peiguang, 2023. "Capacity optimal configuration and collaborative planning of multi-region integrated energy system," Energy, Elsevier, vol. 278(PB).
    11. Zhao, Yuehao & Li, Zhiyi & Ju, Ping & Zhou, Yue, 2023. "Two-stage data-driven dispatch for integrated power and natural gas systems by using stochastic model predictive control," Applied Energy, Elsevier, vol. 343(C).
    12. Zhou, Yanting & Ma, Zhongjing & Shi, Xingyu & Zou, Suli, 2024. "Multi-agent optimal scheduling for integrated energy system considering the global carbon emission constraint," Energy, Elsevier, vol. 288(C).
    13. Dey, Bishwajit & Misra, Srikant & Garcia Marquez, Fausto Pedro, 2023. "Microgrid system energy management with demand response program for clean and economical operation," Applied Energy, Elsevier, vol. 334(C).
    14. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    15. Zhong, Xiaoqing & Zhong, Weifeng & Liu, Yi & Yang, Chao & Xie, Shengli, 2022. "Optimal energy management for multi-energy multi-microgrid networks considering carbon emission limitations," Energy, Elsevier, vol. 246(C).
    16. Yuan, Guanxiu & Gao, Yan & Ye, Bei, 2021. "Optimal dispatching strategy and real-time pricing for multi-regional integrated energy systems based on demand response," Renewable Energy, Elsevier, vol. 179(C), pages 1424-1446.
    17. Xiaohan Liu & Patrick Plötz & Sonia Yeh & Zhengke Liu & Xiaoyue Cathy Liu & Xiaolei Ma, 2024. "Transforming public transport depots into profitable energy hubs," Nature Energy, Nature, vol. 9(10), pages 1206-1219, October.
    18. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    19. Wang, Yongli & Ma, Yuze & Song, Fuhao & Ma, Yang & Qi, Chengyuan & Huang, Feifei & Xing, Juntai & Zhang, Fuwei, 2020. "Economic and efficient multi-objective operation optimization of integrated energy system considering electro-thermal demand response," Energy, Elsevier, vol. 205(C).
    20. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Lin, Zhongwei & Fang, Fang & Chen, Qun, 2021. "Optimal operation of integrated electricity and heat system: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    21. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    22. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization," Energy, Elsevier, vol. 244(PA).
    23. Massidda, Luca & Marrocu, Marino, 2023. "Total and thermal load forecasting in residential communities through probabilistic methods and causal machine learning," Applied Energy, Elsevier, vol. 351(C).
    24. Wang, Liying & Lin, Jialin & Dong, Houqi & Wang, Yuqing & Zeng, Ming, 2023. "Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system," Energy, Elsevier, vol. 270(C).
    25. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
    26. Putz, Dominik & Gumhalter, Michael & Auer, Hans, 2021. "A novel approach to multi-horizon wind power forecasting based on deep neural architecture," Renewable Energy, Elsevier, vol. 178(C), pages 494-505.
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