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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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    as
    1. Liu, Mingxi & Shi, Yang & Fang, Fang, 2014. "Combined cooling, heating and power systems: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 1-22.
    2. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
    3. Huang, Zishuo & Yu, Hang & Peng, Zhenwei & Feng, Yifu, 2017. "Planning community energy system in the industry 4.0 era: Achievements, challenges and a potential solution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 710-721.
    4. Wei, Sun & Yanfeng, Xu, 2017. "Research on China's energy supply and demand using an improved Grey-Markov chain model based on wavelet transform," Energy, Elsevier, vol. 118(C), pages 969-984.
    5. Gao, Penghui & Dai, Yanjun & Tong, YenWah & Dong, Pengwei, 2015. "Energy matching and optimization analysis of waste to energy CCHP (combined cooling, heating and power) system with exergy and energy level," Energy, Elsevier, vol. 79(C), pages 522-535.
    6. Moslehi, Salim & Reddy, T. Agami, 2018. "Sustainability of integrated energy systems: A performance-based resilience assessment methodology," Applied Energy, Elsevier, vol. 228(C), pages 487-498.
    7. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    8. Pfeifer, Antun & Dobravec, Viktorija & Pavlinek, Luka & Krajačić, Goran & Duić, Neven, 2018. "Integration of renewable energy and demand response technologies in interconnected energy systems," Energy, Elsevier, vol. 161(C), pages 447-455.
    9. Wang, Chengshan & Lv, Chaoxian & Li, Peng & Song, Guanyu & Li, Shuquan & Xu, Xiandong & Wu, Jianzhong, 2018. "Modeling and optimal operation of community integrated energy systems: A case study from China," Applied Energy, Elsevier, vol. 230(C), pages 1242-1254.
    10. Cao, Sunliang & Hasan, Ala & Sirén, Kai, 2014. "Matching analysis for on-site hybrid renewable energy systems of office buildings with extended indices," Applied Energy, Elsevier, vol. 113(C), pages 230-247.
    11. Yousefi, Shaghayegh & Moghaddam, Mohsen Parsa & Majd, Vahid Johari, 2011. "Optimal real time pricing in an agent-based retail market using a comprehensive demand response model," Energy, Elsevier, vol. 36(9), pages 5716-5727.
    12. Si, Fangyuan & Wang, Jinkuan & Han, Yinghua & Zhao, Qiang & Han, Peng & Li, Yan, 2018. "Cost-efficient multi-energy management with flexible complementarity strategy for energy internet," Applied Energy, Elsevier, vol. 231(C), pages 803-815.
    13. Möller, Bernd & Wiechers, Eva & Persson, Urban & Grundahl, Lars & Connolly, David, 2018. "Heat Roadmap Europe: Identifying local heat demand and supply areas with a European thermal atlas," Energy, Elsevier, vol. 158(C), pages 281-292.
    14. Noor, Sana & Yang, Wentao & Guo, Miao & van Dam, Koen H. & Wang, Xiaonan, 2018. "Energy Demand Side Management within micro-grid networks enhanced by blockchain," Applied Energy, Elsevier, vol. 228(C), pages 1385-1398.
    15. Liu, Jiahong & Mei, Chao & Wang, Hao & Shao, Weiwei & Xiang, Chenyao, 2018. "Powering an island system by renewable energy—A feasibility analysis in the Maldives," Applied Energy, Elsevier, vol. 227(C), pages 18-27.
    16. Bahl, Björn & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "Optimization-based identification and quantification of demand-side management potential for distributed energy supply systems," Energy, Elsevier, vol. 135(C), pages 889-899.
    17. Ruan, Yingjun & Liu, Qingrong & Li, Zhengwei & Wu, Jiazheng, 2016. "Optimization and analysis of Building Combined Cooling, Heating and Power (BCHP) plants with chilled ice thermal storage system," Applied Energy, Elsevier, vol. 179(C), pages 738-754.
    18. Qu, Kaiping & Yu, Tao & Huang, Linni & Yang, Bo & Zhang, Xiaoshun, 2018. "Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market," Energy, Elsevier, vol. 149(C), pages 779-791.
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    Cited by:

    1. Zhou, Kaile & Chu, Yibo & Hu, Rong, 2023. "Energy supply-demand interaction model integrating uncertainty forecasting and peer-to-peer energy trading," Energy, Elsevier, vol. 285(C).
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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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