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A coordinated control to improve performance for a building cluster with energy storage, electric vehicles, and energy sharing considered

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  • Huang, Pei
  • Lovati, Marco
  • Zhang, Xingxing
  • Bales, Chris

Abstract

Distributed renewable energy systems are now widely installed in many buildings, transforming the buildings into ‘electricity prosumers’. Existing studies have developed some advanced building side controls that enable renewable energy sharing and that aim to optimize building-cluster-level performance via regulating the energy storage charging/discharging. However, the flexible demand shifting ability of electric vehicles is not considered in these building side controls. For instance, the electric vehicle charging will usually start once they are plugged into charging stations. But, in such charging period the renewable generation may be insufficient to cover the EV charging load, leading to grid electricity imports. Consequently, the building-cluster-level performance is not optimized. Therefore, this study proposes a coordinated control of building prosumers for improving the cluster-level performance, by making use of energy sharing and storage capability of electricity batteries in both buildings and EVs. An EV charging/discharging model is first developed. Then, based on the predicted future 24 h electricity demand and renewable generation data, the coordinated control first considers the whole building cluster as one ‘integrated’ building and optimizes its operation as well as the EV charging/discharging using genetic algorithm. Next, the operation of individual buildings in the future 24 h is coordinated using nonlinear programming. For validation, the developed control has been tested on a real building cluster in Ludvika, Sweden. The study results show that the developed control can increase the cluster-level daily renewable self-consumption rate by 19% and meanwhile reduce the daily electricity bills by 36% compared with the conventional controls.

Suggested Citation

  • Huang, Pei & Lovati, Marco & Zhang, Xingxing & Bales, Chris, 2020. "A coordinated control to improve performance for a building cluster with energy storage, electric vehicles, and energy sharing considered," Applied Energy, Elsevier, vol. 268(C).
    • Handle: RePEc:eee:appene:v:268:y:2020:i:c:s0306261920304955
    DOI: 10.1016/j.apenergy.2020.114983
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    References listed on IDEAS

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    4. Fachrizal, Reza & Shepero, Mahmoud & Åberg, Magnus & Munkhammar, Joakim, 2022. "Optimal PV-EV sizing at solar powered workplace charging stations with smart charging schemes considering self-consumption and self-sufficiency balance," Applied Energy, Elsevier, vol. 307(C).
    5. Dan Craciunescu & Laurentiu Fara, 2023. "Investigation of the Partial Shading Effect of Photovoltaic Panels and Optimization of Their Performance Based on High-Efficiency FLC Algorithm," Energies, MDPI, vol. 16(3), pages 1-28, January.
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    7. Zezhong Li & Xiangang Peng & Yilin Xu & Fucheng Zhong & Sheng Ouyang & Kaiguo Xuan, 2023. "A Stackelberg Game-Based Model of Distribution Network-Distributed Energy Storage Systems Considering Demand Response," Mathematics, MDPI, vol. 12(1), pages 1-21, December.
    8. Long Zeng & Si-Zhe Chen & Zebin Tang & Ling Tian & Tingting Xiong, 2023. "An Electric Vehicle Charging Method Considering Multiple Power Exchange Modes’ Coordination," Sustainability, MDPI, vol. 15(13), pages 1-17, July.
    9. Song, Yuguang & Xia, Mingchao & Chen, Qifang, 2023. "The robust synchronization control scheme for flexible resources considering the stochastic and delay response process," Applied Energy, Elsevier, vol. 343(C).
    10. Gao, Hongjun & Cai, Wenhui & He, Shuaijia & Jiang, Jun & Liu, Junyong, 2023. "Multi-energy sharing optimization for a building cluster towards net-zero energy system," Applied Energy, Elsevier, vol. 350(C).
    11. Svetozarevic, B. & Baumann, C. & Muntwiler, S. & Di Natale, L. & Zeilinger, M.N. & Heer, P., 2022. "Data-driven control of room temperature and bidirectional EV charging using deep reinforcement learning: Simulations and experiments," Applied Energy, Elsevier, vol. 307(C).
    12. Huang, Pei & Han, Mengjie & Zhang, Xingxing & Hussain, Syed Asad & Jayprakash Bhagat, Rohit & Hogarehalli Kumar, Deepu, 2022. "Characterization and optimization of energy sharing performances in energy-sharing communities in Sweden, Canada and Germany," Applied Energy, Elsevier, vol. 326(C).
    13. Zhou, Yuekuan, 2022. "Energy sharing and trading on a novel spatiotemporal energy network in Guangdong-Hong Kong-Macao Greater Bay Area," Applied Energy, Elsevier, vol. 318(C).
    14. Kang, Hyuna & Jung, Seunghoon & Lee, Minhyun & Hong, Taehoon, 2022. "How to better share energy towards a carbon-neutral city? A review on application strategies of battery energy storage system in city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    15. Lin, Chun-Cheng & Wu, Yi-Fang & Liu, Wan-Yu, 2021. "Optimal sharing energy of a complex of houses through energy trading in the Internet of energy," Energy, Elsevier, vol. 220(C).

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