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Multi-time scale optimal scheduling of integrated electricity and district heating systems considering thermal comfort of users: An enhanced-interval optimization method

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  • Liu, Xinrui
  • Hou, Min
  • Sun, Siluo
  • Wang, Jiawei
  • Sun, Qiuye
  • Dong, Chaoyu

Abstract

Due to the high integration of renewable energy, renewable energy curtailment has become a key issue that needs to be solved urgently. Aiming at the areas with the characteristics of curtailed wind energy and strong thermal demand, a multi-time scale optimal scheduling model for improving the wind power integration in heating seasons was proposed. In the framework, the enhanced-interval optimization method (EIOM) was applied, by considering the uncertainties of wind power and loads in an integrated electricity and district heating system. Considering the dynamic characteristics of the heating network and the thermal inertia of building, the factors affecting users comfort are analyzed. Then the comfort model parameters based on different user types are designed. The EIOM was reformulated by decomposing into two sub-models. A test system including a 30-node electric network and two 15-node heating networks was used to apply the proposed model. The simulation proves that the EIOM can solve the impact of load uncertainty and obtain the optimal operation cost.

Suggested Citation

  • Liu, Xinrui & Hou, Min & Sun, Siluo & Wang, Jiawei & Sun, Qiuye & Dong, Chaoyu, 2022. "Multi-time scale optimal scheduling of integrated electricity and district heating systems considering thermal comfort of users: An enhanced-interval optimization method," Energy, Elsevier, vol. 254(PB).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pb:s0360544222012142
    DOI: 10.1016/j.energy.2022.124311
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    as
    1. Zhang, Debao & Liu, Junwei & Jiao, Shifei & Tian, Hao & Lou, Chengzhi & Zhou, Zhihua & Zhang, Ji & Wang, Chendong & Zuo, Jian, 2019. "Research on the configuration and operation effect of the hybrid solar-wind-battery power generation system based on NSGA-II," Energy, Elsevier, vol. 189(C).
    2. Yaser Imad Alamin & María Del Mar Castilla & José Domingo Álvarez & Antonio Ruano, 2017. "An Economic Model-Based Predictive Control to Manage the Users’ Thermal Comfort in a Building," Energies, MDPI, vol. 10(3), pages 1-18, March.
    3. Li, Peng & Wang, Zixuan & Wang, Jiahao & Yang, Weihong & Guo, Tianyu & Yin, Yunxing, 2021. "Two-stage optimal operation of integrated energy system considering multiple uncertainties and integrated demand response," Energy, Elsevier, vol. 225(C).
    4. Ehsan, Ali & Yang, Qiang, 2019. "Scenario-based investment planning of isolated multi-energy microgrids considering electricity, heating and cooling demand," Applied Energy, Elsevier, vol. 235(C), pages 1277-1288.
    5. Li, Yiming & Liu, Che & Zhang, Lizhi & Sun, Bo, 2021. "A partition optimization design method for a regional integrated energy system based on a clustering algorithm," Energy, Elsevier, vol. 219(C).
    6. Yang, Xiaohui & Chen, Zaixing & Huang, Xin & Li, Ruixin & Xu, Shaoping & Yang, Chunsheng, 2021. "Robust capacity optimization methods for integrated energy systems considering demand response and thermal comfort," Energy, Elsevier, vol. 221(C).
    7. Wei, Shangshang & Gao, Xianhua & Zhang, Yi & Li, Yiguo & Shen, Jiong & Li, Zuyi, 2021. "An improved stochastic model predictive control operation strategy of integrated energy system based on a single-layer multi-timescale framework," Energy, Elsevier, vol. 235(C).
    8. Chengyu Zeng & Yuechun Jiang & Yuqing Liu & Zuoyun Tan & Zhongnan He & Shuhong Wu, 2019. "Optimal Dispatch of Integrated Energy System Considering Energy Hub Technology and Multi-Agent Interest Balance," Energies, MDPI, vol. 12(16), pages 1-17, August.
    9. Buratti, C. & Ricciardi, P. & Vergoni, M., 2013. "HVAC systems testing and check: A simplified model to predict thermal comfort conditions in moderate environments," Applied Energy, Elsevier, vol. 104(C), pages 117-127.
    10. 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).
    11. Wu, Chenyu & Gu, Wei & Xu, Yinliang & Jiang, Ping & Lu, Shuai & Zhao, Bo, 2018. "Bi-level optimization model for integrated energy system considering the thermal comfort of heat customers," Applied Energy, Elsevier, vol. 232(C), pages 607-616.
    12. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "A robust dispatch model for integrated electricity and heat networks considering price-based integrated demand response," Energy, Elsevier, vol. 239(PA).
    13. Wang, Dan & Zhi, Yun-qiang & Jia, Hong-jie & Hou, Kai & Zhang, Shen-xi & Du, Wei & Wang, Xu-dong & Fan, Meng-hua, 2019. "Optimal scheduling strategy of district integrated heat and power system with wind power and multiple energy stations considering thermal inertia of buildings under different heating regulation modes," Applied Energy, Elsevier, vol. 240(C), pages 341-358.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Aidong Zeng & Jiawei Wang & Yaheng Wan, 2023. "Coordinated Optimal Dispatch of Electricity and Heat Integrated Energy Systems Based on Fictitious Node Method," Energies, MDPI, vol. 16(18), pages 1-24, September.
    2. Wang, Xiaojing & Han, Li & Wang, Chong & Yu, Hongbo & Yu, Xiaojiao, 2023. "A time-scale adaptive dispatching strategy considering the matching of time characteristics and dispatching periods of the integrated energy system," Energy, Elsevier, vol. 267(C).
    3. Wang, Ziqi & Hou, Sizu, 2023. "A real-time strategy for vehicle-to-station recommendation in battery swapping mode," Energy, Elsevier, vol. 272(C).
    4. Zhou, Yanting & Ma, Zhongjing & Zhang, Jinhui & Zou, Suli, 2022. "Data-driven stochastic energy management of multi energy system using deep reinforcement learning," Energy, Elsevier, vol. 261(PA).

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