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Optimisation and analysis of system integration between electric vehicles and UK decentralised energy schemes

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  • Chakrabarti, Auyon
  • Proeglhoef, Rafael
  • Turu, Gonzalo Bustos
  • Lambert, Romain
  • Mariaud, Arthur
  • Acha, Salvador
  • Markides, Christos N.
  • Shah, Nilay

Abstract

Although district heat network schemes provide a pragmatic solution for reducing the environmental impact of urban energy systems, there are additional benefits that could arise from servicing electric vehicles. Using the electricity generated on-site to power electric vehicles can make district heating networks more economically feasible, while also increasing environmental benefits. This paper explores the potential integration of electric vehicle charging into large-scale district heating networks with the aim of increasing the value of the generated electricity and thereby improving the financial feasibility of such systems. A modelling approach is presented composed of a diverse range of distributed technologies that considers residential and commercial electric vehicle charging demands via agent-based modelling. An existing district heating network system in London was taken as a case study. The energy system was modelled as a mixed integer linear program and optimised for either profit maximisation or carbon dioxide emissions minimisation. Commercial electric vehicles provided the best alternative to increase revenue streams by about 11% against the current system configuration with emissions effectively unchanged. The research indicates that district heating network systems need to carefully analyse opportunities for transport electrification in order to improve the integration, and sustainability, of urban energy systems.

Suggested Citation

  • Chakrabarti, Auyon & Proeglhoef, Rafael & Turu, Gonzalo Bustos & Lambert, Romain & Mariaud, Arthur & Acha, Salvador & Markides, Christos N. & Shah, Nilay, 2019. "Optimisation and analysis of system integration between electric vehicles and UK decentralised energy schemes," Energy, Elsevier, vol. 176(C), pages 805-815.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:805-815
    DOI: 10.1016/j.energy.2019.03.184
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    2. Gonzalo Bustos-Turu & Koen H. van Dam & Salvador Acha & Nilay Shah, 2023. "An Agent-Based Decision Support Framework for a Prospective Analysis of Transport and Heat Electrification in Urban Areas," Energies, MDPI, vol. 16(17), pages 1-26, August.
    3. Zhang, Yuanjian & Chu, Liang & Fu, Zicheng & Xu, Nan & Guo, Chong & Zhao, Di & Ou, Yang & Xu, Lei, 2020. "Energy management strategy for plug-in hybrid electric vehicle integrated with vehicle-environment cooperation control," Energy, Elsevier, vol. 197(C).
    4. Jalil-Vega, Francisca & García Kerdan, Iván & Hawkes, Adam D., 2020. "Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities," Applied Energy, Elsevier, vol. 262(C).
    5. Ruiqiu Yao & Yukun Hu & Liz Varga, 2023. "Applications of Agent-Based Methods in Multi-Energy Systems—A Systematic Literature Review," Energies, MDPI, vol. 16(5), pages 1-36, March.
    6. Tao, Ye & Huang, Miaohua & Chen, Yupu & Yang, Lan, 2020. "Orderly charging strategy of battery electric vehicle driven by real-world driving data," Energy, Elsevier, vol. 193(C).
    7. Karol Tucki & Olga Orynycz & Antoni Świć & Mateusz Mitoraj-Wojtanek, 2019. "The Development of Electromobility in Poland and EU States as a Tool for Management of CO 2 Emissions," Energies, MDPI, vol. 12(15), pages 1-22, July.
    8. Acha, Salvador & Le Brun, Niccolo & Damaskou, Maria & Fubara, Tekena Craig & Mulgundmath, Vinay & Markides, Christos N. & Shah, Nilay, 2020. "Fuel cells as combined heat and power systems in commercial buildings: A case study in the food-retail sector," Energy, Elsevier, vol. 206(C).
    9. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M. & Lund, Peter D., 2019. "Energy integration and interaction between buildings and vehicles: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    10. Zhang, Zhihui & Jing, Rui & Lin, Jian & Wang, Xiaonan & van Dam, Koen H. & Wang, Meng & Meng, Chao & Xie, Shan & Zhao, Yingru, 2020. "Combining agent-based residential demand modeling with design optimization for integrated energy systems planning and operation," Applied Energy, Elsevier, vol. 263(C).

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