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A novel energy supply and demand matching model in park integrated energy system

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  • Liu, Zhiyuan
  • Yu, Hang
  • Liu, Rui

Abstract

The study of supply and demand match increasingly becomes an enormous challenge in park integrated energy system (PIES) because it has a comprehensive relationship between multiple energy sources and multiple energy demand. This paper proposes a new type of supply and demand matching to accomplish the economic optimality of match under the same criteria, considering supply and demand changing simultaneously. The quantitative indexes of supply and demand energy conversion technologies (ECTs) is established considering the economic and technical characteristics of full life cycle comprehensively, which are defined as supplied technical cost level and demand technical cost level. Then, the novel energy supply and demand matching model is established. The loop iteration algorithm of the new matching model is established based on linear programming model. Numerical study is introduced based on the data of the cooling, heating and electrical load in a typical day. The results show that the priority order of each ECT is different when the output of all ECTs increasing gradually. The investment payback period is only 1.94 years. The new supply and demand matching model can reduce carbon emissions by 80,555 tons.

Suggested Citation

  • Liu, Zhiyuan & Yu, Hang & Liu, Rui, 2019. "A novel energy supply and demand matching model in park integrated energy system," Energy, Elsevier, vol. 176(C), pages 1007-1019.
  • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:1007-1019
    DOI: 10.1016/j.energy.2019.04.049
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    3. Qin, Chao & Yan, Qingyou & He, Gang, 2019. "Integrated energy systems planning with electricity, heat and gas using particle swarm optimization," Energy, Elsevier, vol. 188(C).
    4. Wang, Meng & Yu, Hang & Yang, Yikun & Lin, Xiaoyu & Guo, Haijin & Li, Chaoen & Zhou, Yue & Jing, Rui, 2021. "Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization," Applied Energy, Elsevier, vol. 302(C).

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