IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v240y2022ics0360544221030395.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221030395
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2021.122790?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Zhao Luo & Jinghui Wang & Ni Xiao & Linyan Yang & Weijie Zhao & Jialu Geng & Tao Lu & Mengshun Luo & Chenming Dong, 2022. "Low Carbon Economic Dispatch Optimization of Regional Integrated Energy Systems Considering Heating Network and P2G," Energies, MDPI, vol. 15(15), pages 1-14, July.
    3. Siddique, Muhammad Bilal & Bergaentzlé, Claire & Gunkel, Philipp Andreas, 2022. "Fine-tuning energy efficiency subsidies allocation for maximum savings in residential buildings," Energy, Elsevier, vol. 258(C).
    4. Yang, Weijia & Huang, Yuping & Zhao, Daiqing, 2023. "A coupled hydraulic–thermal dynamic model for the steam network in a heat–electricity integrated energy system," Energy, Elsevier, vol. 263(PC).
    5. Wang, Jiangjiang & Huo, Shuojie & Yan, Rujing & Cui, Zhiheng, 2022. "Leveraging heat accumulation of district heating network to improve performances of integrated energy system under source-load uncertainties," Energy, Elsevier, vol. 252(C).
    6. Jakubek, Dariusz & Ocłoń, Paweł & Nowak-Ocłoń, Marzena & Sułowicz, Maciej & Varbanov, Petar Sabev & Klemeš, Jiří Jaromír, 2023. "Mathematical modelling and model validation of the heat losses in district heating networks," Energy, Elsevier, vol. 267(C).
    7. Zhang, Zhaoyan & Jiang, Ping & Liu, Zhibin & Fu, Lei & Wang, Peiguang, 2023. "Capacity optimal configuration and collaborative planning of multi-region integrated energy system," Energy, Elsevier, vol. 278(PB).
    8. Qin, Yuxiao & Liu, Pei & Li, Zheng, 2022. "Multi-timescale hierarchical scheduling of an integrated energy system considering system inertia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Zhang, Zhaoyan & Jiang, Ping & Liu, Zhibin & Fu, Lei & Wang, Peiguang, 2023. "Capacity optimal configuration and collaborative planning of multi-region integrated energy system," Energy, Elsevier, vol. 278(PB).
    3. Chunxia Gao & Zhaoyan Zhang & Peiguang Wang, 2023. "Day-Ahead Scheduling Strategy Optimization of Electric–Thermal Integrated Energy System to Improve the Proportion of New Energy," Energies, MDPI, vol. 16(9), pages 1-30, April.
    4. Zhibin Liu & Feng Guo & Jiaqi Liu & Xinyan Lin & Ao Li & Zhaoyan Zhang & Zhiheng Liu, 2023. "A Compound Coordinated Optimal Operation Strategy of Day-Ahead-Rolling-Realtime in Integrated Energy System," Energies, MDPI, vol. 16(1), pages 1-19, January.
    5. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    6. Bravo, Ruben & Ortiz, Carlos & Chacartegui, Ricardo & Friedrich, Daniel, 2021. "Multi-objective optimisation and guidelines for the design of dispatchable hybrid solar power plants with thermochemical energy storage," Applied Energy, Elsevier, vol. 282(PB).
    7. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
    8. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    9. Scheller, Fabian & Burkhardt, Robert & Schwarzeit, Robert & McKenna, Russell & Bruckner, Thomas, 2020. "Competition between simultaneous demand-side flexibility options: the case of community electricity storage systems," Applied Energy, Elsevier, vol. 269(C).
    10. Fabian Scheller & Robert Burkhardt & Robert Schwarzeit & Russell McKenna & Thomas Bruckner, 2020. "Competition between simultaneous demand-side flexibility options: The case of community electricity storage systems," Papers 2011.05809, arXiv.org.
    11. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    12. Hoffmann, Maximilian & Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron & Kotzur, Leander & Stolten, Detlef, 2021. "Typical periods or typical time steps? A multi-model analysis to determine the optimal temporal aggregation for energy system models," Applied Energy, Elsevier, vol. 304(C).
    13. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    14. Wang, Hai & Wang, Haiying & Haijian, Zhou & Zhu, Tong, 2017. "Optimization modeling for smart operation of multi-source district heating with distributed variable-speed pumps," Energy, Elsevier, vol. 138(C), pages 1247-1262.
    15. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    16. Comodi, Gabriele & Bartolini, Andrea & Carducci, Francesco & Nagaranjan, Balamurugan & Romagnoli, Alessandro, 2019. "Achieving low carbon local energy communities in hot climates by exploiting networks synergies in multi energy systems," Applied Energy, Elsevier, vol. 256(C).
    17. Keck, Felix & Lenzen, Manfred, 2021. "Drivers and benefits of shared demand-side battery storage – an Australian case study," Energy Policy, Elsevier, vol. 149(C).
    18. Diana Enescu & Gianfranco Chicco & Radu Porumb & George Seritan, 2020. "Thermal Energy Storage for Grid Applications: Current Status and Emerging Trends," Energies, MDPI, vol. 13(2), pages 1-21, January.
    19. Schweiger, Gerald & Larsson, Per-Ola & Magnusson, Fredrik & Lauenburg, Patrick & Velut, Stéphane, 2017. "District heating and cooling systems – Framework for Modelica-based simulation and dynamic optimization," Energy, Elsevier, vol. 137(C), pages 566-578.
    20. Norbu, Sonam & Couraud, Benoit & Robu, Valentin & Andoni, Merlinda & Flynn, David, 2021. "Modelling the redistribution of benefits from joint investments in community energy projects," Applied Energy, Elsevier, vol. 287(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:240:y:2022:i:c:s0360544221030395. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.