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Time-Scale Economic Dispatch of Electricity-Heat Integrated System Based on Users’ Thermal Comfort

Author

Listed:
  • Xin-Rui Liu

    (Department of Electrical Engineering, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

  • Si-Luo Sun

    (Department of Electrical Engineering, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

  • Qiu-Ye Sun

    (Department of Electrical Engineering, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

  • Wei-Yang Zhong

    (Department of Electrical Engineering, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

Abstract

The electricity-heat integrated system can realize the cascade utilization of energy and the coordination and complementarity between multiple energy sources. In this paper, considering the thermal comfort of users, taking into account the difference in dynamic characteristics of electric and heating networks and the response of users’ demands, a dispatch model is constructed. In this model, taking into account the difference in the time scale of electric and thermal dispatching, optimization of the system can be improved by properly extending the thermal balance cycle of the combined heat and power (CHP) unit. Based on the time-of-use electricity prices and heat prices to obtain the optimal energy purchase cost, a user demand response strategy is adopted. Therefore, a minimum economic cost on the energy supply side and a minimum energy purchase cost on the demand side are considered as a bilevel optimization strategy for the operation of the system. Finally, using an IEEE 30 nodes power network and a 31 nodes heating network to form an electricity-heat integrated system, the simulation results show that the optimal thermal balance cycle can maximize the economic benefits on the premise of meeting the users’ thermal comfort and the demand response can effectively realize the wind curtailment and improve the system economy.

Suggested Citation

  • Xin-Rui Liu & Si-Luo Sun & Qiu-Ye Sun & Wei-Yang Zhong, 2020. "Time-Scale Economic Dispatch of Electricity-Heat Integrated System Based on Users’ Thermal Comfort," Energies, MDPI, vol. 13(20), pages 1-27, October.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5505-:d:432039
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    References listed on IDEAS

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    1. Lynch, Muireann Á. & Nolan, Sheila & Devine, Mel T. & O’Malley, Mark, 2019. "The impacts of demand response participation in capacity markets," Applied Energy, Elsevier, vol. 250(C), pages 444-451.
    2. Yu, Dayang & Liang, Jun & Han, Xueshan & Zhao, Jianguo, 2011. "Profiling the regional wind power fluctuation in China," Energy Policy, Elsevier, vol. 39(1), pages 299-306, January.
    3. Fragaki, Aikaterini & Andersen, Anders N., 2011. "Conditions for aggregation of CHP plants in the UK electricity market and exploration of plant size," Applied Energy, Elsevier, vol. 88(11), pages 3930-3940.
    4. Moghaddam, M. Parsa & Abdollahi, A. & Rashidinejad, M., 2011. "Flexible demand response programs modeling in competitive electricity markets," Applied Energy, Elsevier, vol. 88(9), pages 3257-3269.
    5. Wang, Jianhui & Bloyd, Cary N. & Hu, Zhaoguang & Tan, Zhongfu, 2010. "Demand response in China," Energy, Elsevier, vol. 35(4), pages 1592-1597.
    6. Duquette, Jean & Rowe, Andrew & Wild, Peter, 2016. "Thermal performance of a steady state physical pipe model for simulating district heating grids with variable flow," Applied Energy, Elsevier, vol. 178(C), pages 383-393.
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    Cited by:

    1. Kröger, David & Peper, Jan & Rehtanz, Christian, 2023. "Electricity market modeling considering a high penetration of flexible heating systems and electric vehicles," Applied Energy, Elsevier, vol. 331(C).
    2. da Fonseca, André L.A. & Chvatal, Karin M.S. & Fernandes, Ricardo A.S., 2021. "Thermal comfort maintenance in demand response programs: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).

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