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A dynamic self-learning grid-responsive strategy for battery sharing economy—multi-objective optimisation and posteriori multi-criteria decision making

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  • Zhou, Yuekuan

Abstract

District building-vehicle interactive energy network with systematic energy interactions can improve techno-economic performances and enhance cleaner power penetration, whereas the battery cycling aging will be accelerated due to an increase in frequency of charging/discharging cycles. In this study, a dynamic self-learning grid-responsive strategy was proposed to improve techno-economic performances, energy flexibility, and the relative capacity (RC) of electrochemical batteries, through dynamically adjustable off-peak grid charging power. A collaborative framework on an energy district with building-integrated photovoltaics and electric vehicles has been formulated, through synergic energy interactions and integrations. Cycling aging of both static batteries in buildings and mobile vehicle batteries has been considered. In respect to intrinsic contradiction characteristics of each objective, trade-off solutions have been proposed through multi-objective optimisation. Furthermore, regarding the multiple optimal solutions along the Pareto front, a weighted Eulerian distance-based methodology was adopted to identify the ‘best of best’ solution and then assist multi-criteria decision-making. Research results show that, with the proposed dynamic self-learning grid-responsive strategy, the grid can provide a more flexible grid-to-battery charging power with a higher RC of batteries, compared to the strategy with dynamic renewable-demand signals. Through the multi-objective optimisation, the import cost can be reduced from 213.2 to 203.8 HK$/m2·a, and the RC can be improved from 0.800 to 0.999. This study also demonstrates a weighted Eulerian distance-based methodology to identify the ‘best of best’ solution to multi-criteria decision-makers. Research results are useful to promote district interactive energy networks in smart cities, with multivariant optimal design, Pareto optimal solutions, and weighted Eulerian distance-based ‘best of best’ solution.

Suggested Citation

  • Zhou, Yuekuan, 2023. "A dynamic self-learning grid-responsive strategy for battery sharing economy—multi-objective optimisation and posteriori multi-criteria decision making," Energy, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:energy:v:266:y:2023:i:c:s0360544222032832
    DOI: 10.1016/j.energy.2022.126397
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    References listed on IDEAS

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    1. 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.
    2. Zhou, Yuekuan, 2022. "A regression learner-based approach for battery cycling ageing prediction―advances in energy management strategy and techno-economic analysis," Energy, Elsevier, vol. 256(C).
    3. Quddus, Md Abdul & Shahvari, Omid & Marufuzzaman, Mohammad & Usher, John M. & Jaradat, Raed, 2018. "A collaborative energy sharing optimization model among electric vehicle charging stations, commercial buildings, and power grid," Applied Energy, Elsevier, vol. 229(C), pages 841-857.
    4. Barone, G. & Buonomano, A. & Calise, F. & Forzano, C. & Palombo, A., 2019. "Building to vehicle to building concept toward a novel zero energy paradigm: Modelling and case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 625-648.
    5. Buonomano, Annamaria, 2020. "Building to Vehicle to Building concept: A comprehensive parametric and sensitivity analysis for decision making aims," Applied Energy, Elsevier, vol. 261(C).
    6. Zheng, Siqian & Jin, Xin & Huang, Gongsheng & Lai, Alvin CK., 2022. "Coordination of commercial prosumers with distributed demand-side flexibility in energy sharing and management system," Energy, Elsevier, vol. 248(C).
    7. Lyu, Cheng & Jia, Youwei & Xu, Zhao, 2021. "Fully decentralized peer-to-peer energy sharing framework for smart buildings with local battery system and aggregated electric vehicles," Applied Energy, Elsevier, vol. 299(C).
    8. Liu, Jia & Yang, Hongxing & Zhou, Yuekuan, 2021. "Peer-to-peer trading optimizations on net-zero energy communities with energy storage of hydrogen and battery vehicles," Applied Energy, Elsevier, vol. 302(C).
    9. Shen, Rendong & Zhong, Shengyuan & Wen, Xin & An, Qingsong & Zheng, Ruifan & Li, Yang & Zhao, Jun, 2022. "Multi-agent deep reinforcement learning optimization framework for building energy system with renewable energy," Applied Energy, Elsevier, vol. 312(C).
    10. Borge-Diez, David & Icaza, Daniel & Açıkkalp, Emin & Amaris, Hortensia, 2021. "Combined vehicle to building (V2B) and vehicle to home (V2H) strategy to increase electric vehicle market share," Energy, Elsevier, vol. 237(C).
    11. Kobashi, Takuro & Choi, Younghun & Hirano, Yujiro & Yamagata, Yoshiki & Say, Kelvin, 2022. "Rapid rise of decarbonization potentials of photovoltaics plus electric vehicles in residential houses over commercial districts," Applied Energy, Elsevier, vol. 306(PB).
    12. Zhou, Yuekuan, 2023. "Sustainable energy sharing districts with electrochemical battery degradation in design, planning, operation and multi-objective optimisation," Renewable Energy, Elsevier, vol. 202(C), pages 1324-1341.
    13. 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).
    14. 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).
    15. Han, Xuejiao & Garrison, Jared & Hug, Gabriela, 2022. "Techno-economic analysis of PV-battery systems in Switzerland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    16. Barone, Giovanni & Buonomano, Annamaria & Forzano, Cesare & Giuzio, Giovanni Francesco & Palombo, Adolfo & Russo, Giuseppe, 2022. "Energy virtual networks based on electric vehicles for sustainable buildings: System modelling for comparative energy and economic analyses," Energy, Elsevier, vol. 242(C).
    17. Bartolini, Andrea & Comodi, Gabriele & Salvi, Danilo & Østergaard, Poul Alberg, 2020. "Renewables self-consumption potential in districts with high penetration of electric vehicles," Energy, Elsevier, vol. 213(C).
    18. Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Bianchi, Francesco & Domenghini, Piergiovanni & Cotana, Franco & Wang, Jinwen, 2022. "A techno-economic analysis of a solar PV and DC battery storage system for a community energy sharing," Energy, Elsevier, vol. 244(PB).
    19. Zheng, Siqian & Huang, Gongsheng & Lai, Alvin CK., 2021. "Techno-economic performance analysis of synergistic energy sharing strategies for grid-connected prosumers with distributed battery storages," Renewable Energy, Elsevier, vol. 178(C), pages 1261-1278.
    20. Murray, Portia & Carmeliet, Jan & Orehounig, Kristina, 2020. "Multi-Objective Optimisation of Power-to-Mobility in Decentralised Multi-Energy Systems," Energy, Elsevier, vol. 205(C).
    21. Zhou, Yuekuan, 2022. "Incentivising multi-stakeholders’ proactivity and market vitality for spatiotemporal microgrids in Guangzhou-Shenzhen-Hong Kong Bay Area," Applied Energy, Elsevier, vol. 328(C).
    22. Yang, Wenjun & Guo, Jia & Vartosh, Aris, 2022. "Optimal economic-emission planning of multi-energy systems integrated electric vehicles with modified group search optimization," Applied Energy, Elsevier, vol. 311(C).
    23. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M., 2021. "An energy paradigm transition framework from negative towards positive district energy sharing networks—Battery cycling aging, advanced battery management strategies, flexible vehicles-to-buildings in," Applied Energy, Elsevier, vol. 288(C).
    24. Liu, Jia & Yang, Hongxing & Zhou, Yuekuan, 2021. "Peer-to-peer energy trading of net-zero energy communities with renewable energy systems integrating hydrogen vehicle storage," Applied Energy, Elsevier, vol. 298(C).
    25. Mayyas, Ahmad & Chadly, Assia & Amer, Saed Talib & Azar, Elie, 2022. "Economics of the Li-ion batteries and reversible fuel cells as energy storage systems when coupled with dynamic electricity pricing schemes," Energy, Elsevier, vol. 239(PA).
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