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Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization

Author

Listed:
  • Wang, Meng
  • Yu, Hang
  • Yang, Yikun
  • Lin, Xiaoyu
  • Guo, Haijin
  • Li, Chaoen
  • Zhou, Yue
  • Jing, Rui
Abstract
Integrated energy systems (IES) can help achieve greater energy efficiency, and then ultimately promote a climate-neutral economy by utilizing local renewable resources. Demand-side energy-saving measures can reduce operational costs associated with energy usage. Most existing IES models, however, focus on supply-side optimization, while the demand-side energy-saving potential and its impacts on whole-system performance are still not clear. The increasing carbon tax makes it even more important to understand the interactions between supply and demand sides to achieve a sustainable system with a minimal carbon charge. Hence, this study proposes a co-optimization model to simultaneously optimize the supply and demand sides of an IES considering the impact of the carbon tax. A selection tree is developed to describe various demand-side envelope upgrading technologies, and a binary tree is established by generating a set of supply-side scenarios with corresponding probabilities. Based on these results, an improved two-stage stochastic programming model is proposed. The robustness of the modeling results was further validated by a simulation–optimization-based uncertainty analysis addressing price uncertainties. A case study in Shanghai indicates that the proposed co-optimization model achieves more cost-efficient solutions than supply-side-only optimization considering carbon tax. Introducing carbon tax can reduce the installed capacity of fuel-based energy technologies by up to 24% and greatly accelerate the penetration of renewables. The increasing carbon tax also promotes the adoption of more advanced energy-saving technologies. Uncertainty analysis reveals acceptable robustness of the optimal demand-side scheme and supply-side configuration with a deviation of less than 5% and a coefficient of variation of 7%. Overall, the observations of the proposed model and case study provide valuable insights for IES design considering an emerging charge of carbon tax.

Suggested Citation

  • Wang, Meng & Yu, Hang & Yang, Yikun & Lin, Xiaoyu & Guo, Haijin & Li, Chaoen & Zhou, Yue & Jing, Rui, 2021. "Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization," Applied Energy, Elsevier, vol. 302(C).
    • Handle: RePEc:eee:appene:v:302:y:2021:i:c:s0306261921009557
    DOI: 10.1016/j.apenergy.2021.117579
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    2. Lyu, Xiangmei & Liu, Tianqi & Liu, Xuan & He, Chuan & Nan, Lu & Zeng, Hong, 2023. "Low-carbon robust economic dispatch of park-level integrated energy system considering price-based demand response and vehicle-to-grid," Energy, Elsevier, vol. 263(PB).
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    5. Wang, Meng & Yu, Hang & Liu, Yupeng & Lin, Jianyi & Zhong, Xianzhun & Tang, Yin & Guo, Haijin & Jing, Rui, 2024. "Unlock city-scale energy saving and peak load shaving potential of green roofs by GIS-informed urban building energy modelling," Applied Energy, Elsevier, vol. 366(C).
    6. Jing, Rui & Hua, Weiqi & Lin, Jian & Lin, Jianyi & Zhao, Yingru & Zhou, Yue & Wu, Jianzhong, 2022. "Cost-efficient decarbonization of local energy systems by whole-system based design optimization," Applied Energy, Elsevier, vol. 326(C).
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