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Energy management of ultra-short-term optimal scheduling of integrated energy system considering the characteristics of heating network

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  • Zhang, Zhaoyan
  • Wang, Peiguang
  • Jiang, Ping
  • Liu, Zhiheng
  • Fu, Lei

Abstract

In view of the differences in transmission delay and transmission loss between heating network and power-grid in the integrated energy system, an ultra-short-term optimal scheduling energy management considering the characteristics of heating network is proposed in this pape. Based on graph theory, a heating network model suitable for system optimal scheduling is established. Considering the transient characteristics of the thermal medium temperature, the theoretical basis for judging the transient and steady-state heat transfer characteristics of the pipeline according to the scheduling period and the length of the pipeline is derived. The optimal operating state and daily operating cost of the equipment under three scenarios (considering the transient heat transfer characteristics of the heating network, considering the steady-state heat transfer characteristics of the heating network, and not considering the heat transfer characteristics of the heating network) are respectively compared. The calculation example analysis and verification show that the heat storage characteristics caused by the complex topology and transmission delay of the heat network change the matching of the supply and demand of the thermal power of the system, and the thermal power of the supply and demand side is no longer matched in real time. The ultra-short-term optimal scheduling energy management considering the transient heat transfer characteristics of the heating network has the regulation potential of the IES electric-thermal economic optimal operation under the excitation of time-of-use electricity price, and effectively makes use of the complementary characteristics of the electric and thermal systems to reduce the operation cost of the integrated energy system.

Suggested Citation

  • Zhang, Zhaoyan & Wang, Peiguang & Jiang, Ping & Liu, Zhiheng & Fu, Lei, 2022. "Energy management of ultra-short-term optimal scheduling of integrated energy system considering the characteristics of heating network," Energy, Elsevier, vol. 240(C).
  • Handle: RePEc:eee:energy:v:240:y:2022:i:c:s0360544221030395
    DOI: 10.1016/j.energy.2021.122790
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    References listed on IDEAS

    as
    1. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    2. Renaldi, Renaldi & Friedrich, Daniel, 2017. "Multiple time grids in operational optimisation of energy systems with short- and long-term thermal energy storage," Energy, Elsevier, vol. 133(C), pages 784-795.
    3. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    4. Sarid, A. & Tzur, M., 2018. "The multi-scale generation and transmission expansion model," Energy, Elsevier, vol. 148(C), pages 977-991.
    5. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    6. O. Schmidt & A. Hawkes & A. Gambhir & I. Staffell, 2017. "The future cost of electrical energy storage based on experience rates," Nature Energy, Nature, vol. 2(8), pages 1-8, August.
    7. Sawle, Yashwant & Gupta, S.C. & Bohre, Aashish Kumar, 2018. "Review of hybrid renewable energy systems with comparative analysis of off-grid hybrid system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2217-2235.
    8. Penkovskii, Andrey & Stennikov, Valery & Mednikova, Ekaterina & Postnikov, Ivan, 2018. "Search for a market equilibrium of Cournot-Nash in the competitive heat market," Energy, Elsevier, vol. 161(C), pages 193-201.
    9. Alva, Guruprasad & Lin, Yaxue & Fang, Guiyin, 2018. "An overview of thermal energy storage systems," Energy, Elsevier, vol. 144(C), pages 341-378.
    10. van der Stelt, Sander & AlSkaif, Tarek & van Sark, Wilfried, 2018. "Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances," Applied Energy, Elsevier, vol. 209(C), pages 266-276.
    11. Koirala, Binod Prasad & van Oost, Ellen & van der Windt, Henny, 2018. "Community energy storage: A responsible innovation towards a sustainable energy system?," Applied Energy, Elsevier, vol. 231(C), pages 570-585.
    12. Jinil Han & Jongyoon Park & Kyungsik Lee, 2017. "Optimal Scheduling for Electric Vehicle Charging under Variable Maximum Charging Power," Energies, MDPI, vol. 10(7), pages 1-15, July.
    13. Mehrjerdi, Hasan, 2020. "Peer-to-peer home energy management incorporating hydrogen storage system and solar generating units," Renewable Energy, Elsevier, vol. 156(C), pages 183-192.
    14. Mandelli, Stefano & Barbieri, Jacopo & Mereu, Riccardo & Colombo, Emanuela, 2016. "Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1621-1646.
    15. Wang, Peiguang & Zhang, Zhaoyan & Fu, Lei & Ran, Ning, 2021. "Optimal design of home energy management strategy based on refined load model," Energy, Elsevier, vol. 218(C).
    16. Vesterlund, Mattias & Toffolo, Andrea & Dahl, Jan, 2017. "Optimization of multi-source complex district heating network, a case study," Energy, Elsevier, vol. 126(C), pages 53-63.
    17. Ortiz, C. & Romano, M.C. & Valverde, J.M. & Binotti, M. & Chacartegui, R., 2018. "Process integration of Calcium-Looping thermochemical energy storage system in concentrating solar power plants," Energy, Elsevier, vol. 155(C), pages 535-551.
    18. Jiang, X.S. & Jing, Z.X. & Li, Y.Z. & Wu, Q.H. & Tang, W.H., 2014. "Modelling and operation optimization of an integrated energy based direct district water-heating system," Energy, Elsevier, vol. 64(C), pages 375-388.
    19. Vignarooban, K. & Xu, Xinhai & Arvay, A. & Hsu, K. & Kannan, A.M., 2015. "Heat transfer fluids for concentrating solar power systems – A review," Applied Energy, Elsevier, vol. 146(C), pages 383-396.
    20. 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.
    21. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies," Applied Energy, Elsevier, vol. 239(C), pages 356-372.
    22. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    23. Starke, Allan R. & Cardemil, José M. & Escobar, Rodrigo & Colle, Sergio, 2018. "Multi-objective optimization of hybrid CSP+PV system using genetic algorithm," Energy, Elsevier, vol. 147(C), pages 490-503.
    24. Renaldi, Renaldi & Friedrich, Daniel, 2019. "Techno-economic analysis of a solar district heating system with seasonal thermal storage in the UK," Applied Energy, Elsevier, vol. 236(C), pages 388-400.
    25. Teichgraeber, Holger & Brandt, Adam R., 2019. "Clustering methods to find representative periods for the optimization of energy systems: An initial framework and comparison," Applied Energy, Elsevier, vol. 239(C), pages 1283-1293.
    26. Abdon, Andreas & Zhang, Xiaojin & Parra, David & Patel, Martin K. & Bauer, Christian & Worlitschek, Jörg, 2017. "Techno-economic and environmental assessment of stationary electricity storage technologies for different time scales," Energy, Elsevier, vol. 139(C), pages 1173-1187.
    27. Hemmati, Reza & Mehrjerdi, Hasan & Bornapour, Mosayeb, 2020. "Hybrid hydrogen-battery storage to smooth solar energy volatility and energy arbitrage considering uncertain electrical-thermal loads," Renewable Energy, Elsevier, vol. 154(C), pages 1180-1187.
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