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Uncertainty energy planning of net-zero energy communities with peer-to-peer energy trading and green vehicle storage considering climate changes by 2050 with machine learning methods

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  • Liu, Jia
  • Zhou, Yuekuan
  • Yang, Hongxing
  • Wu, Huijun

Abstract

This study aims to develop uncertainty energy planning of net-zero energy communities with innovative peer-to-peer energy trading management and advanced green vehicle storage considering climate changes by 2050 with transient system modelling, stochastic uncertainty sampling and data-driven machine learning predictions. The future-oriented peer-to-peer energy trading management strategy is proposed considering large renewable energy generation in determining time-of-use power periods to improve energy flexibility. The aleatory and epistemic uncertainties of key weather parameters determining renewables generation with climate changes are quantified and various machine learning regression models are used to predict dynamic solar photovoltaic and wind power generation by 2050 with weather uncertainty. The study results indicate that the ambient temperature increases with time at the uncertainty range of [0, 17.82%], the beam radiation and sky diffuse radiation decrease with time at [−24.86%, 0], and the ground reflected diffuse radiation and wind speed show an uncertain trend at [−0.72%, 0.72%]. The annual solar photovoltaic and wind power generation in 2050 is projected to be 11.69% and 0.61% lower than those of the typical meteorological year. The peer trading cost saving in 2050 considering climate changes is reduced by 2.25% and the annual equivalent carbon emissions are increased by 9.15% compared with the typical meteorological year scenario. The uncertainty design of net-zero energy communities integrated with hydrogen vehicle and battery vehicle storage considering climate changes provides significant guidance for advancing net zero carbon and realizing carbon neutrality for integrated building and transport sectors by 2050.

Suggested Citation

  • Liu, Jia & Zhou, Yuekuan & Yang, Hongxing & Wu, Huijun, 2022. "Uncertainty energy planning of net-zero energy communities with peer-to-peer energy trading and green vehicle storage considering climate changes by 2050 with machine learning methods," Applied Energy, Elsevier, vol. 321(C).
    • Handle: RePEc:eee:appene:v:321:y:2022:i:c:s0306261922007322
    DOI: 10.1016/j.apenergy.2022.119394
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    References listed on IDEAS

    as
    1. Jinyue Yan & Ying Yang & Pietro Elia Campana & Jijiang He, 2019. "City-level analysis of subsidy-free solar photovoltaic electricity price, profits and grid parity in China," Nature Energy, Nature, vol. 4(8), pages 709-717, August.
    2. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie & Jiang, Qian & Wang, Xiaoyu, 2021. "Peer-to-Peer energy trading strategy for energy balance service provider (EBSP) considering market elasticity in community microgrid," Applied Energy, Elsevier, vol. 303(C).
    3. Ahmad, Tanveer & Zhang, Dongdong & Huang, Chao, 2021. "Methodological framework for short-and medium-term energy, solar and wind power forecasting with stochastic-based machine learning approach to monetary and energy policy applications," Energy, Elsevier, vol. 231(C).
    4. Yassaghi, Hamed & Gurian, Patrick L. & Hoque, Simi, 2020. "Propagating downscaled future weather file uncertainties into building energy use," Applied Energy, Elsevier, vol. 278(C).
    5. Zhou, Yue & Wu, Jianzhong & Song, Guanyu & Long, Chao, 2020. "Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community," Applied Energy, Elsevier, vol. 278(C).
    6. D'Agostino, D. & Parker, D. & Epifani, I. & Crawley, D. & Lawrie, L., 2022. "How will future climate impact the design and performance of nearly zero energy buildings (NZEBs)?," Energy, Elsevier, vol. 240(C).
    7. Ma, Tao & Yang, Hongxing & Lu, Lin & Peng, Jinqing, 2015. "Optimal design of an autonomous solar–wind-pumped storage power supply system," Applied Energy, Elsevier, vol. 160(C), pages 728-736.
    8. Liu, Jia & Cao, Sunliang & Chen, Xi & Yang, Hongxing & Peng, Jinqing, 2021. "Energy planning of renewable applications in high-rise residential buildings integrating battery and hydrogen vehicle storage," Applied Energy, Elsevier, vol. 281(C).
    9. Liu, Jia & Zhou, Yuekuan & Yang, Hongxing & Wu, Huijun, 2022. "Net-zero energy management and optimization of commercial building sectors with hybrid renewable energy systems integrated with energy storage of pumped hydro and hydrogen taxis," Applied Energy, Elsevier, vol. 321(C).
    10. 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).
    11. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2020. "Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters’ uncertainties," Renewable Energy, Elsevier, vol. 151(C), pages 403-418.
    12. Golombek, Rolf & Lind, Arne & Ringkjøb, Hans-Kristian & Seljom, Pernille, 2022. "The role of transmission and energy storage in European decarbonization towards 2050," Energy, Elsevier, vol. 239(PC).
    13. 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).
    14. Domínguez, R. & Carrión, M. & Oggioni, G., 2020. "Planning and operating a renewable-dominated European power system under uncertainty," Applied Energy, Elsevier, vol. 258(C).
    15. 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).
    16. Liu, Jia & Chen, Xi & Yang, Hongxing & Shan, Kui, 2021. "Hybrid renewable energy applications in zero-energy buildings and communities integrating battery and hydrogen vehicle storage," Applied Energy, Elsevier, vol. 290(C).
    17. Liu, Jia & Chen, Xi & Yang, Hongxing & Li, Yutong, 2020. "Energy storage and management system design optimization for a photovoltaic integrated low-energy building," Energy, Elsevier, vol. 190(C).
    18. Li, Sihui & Peng, Jinqing & Zou, Bin & Li, Bojia & Lu, Chujie & Cao, Jingyu & Luo, Yimo & Ma, Tao, 2021. "Zero energy potential of photovoltaic direct-driven air conditioners with considering the load flexibility of air conditioners," Applied Energy, Elsevier, vol. 304(C).
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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