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A copula-based whole system model to understand the environmental and economic impacts of grid-scale energy storage

Author

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  • He, Fan
  • Leach, Matthew
  • Short, Michael
  • Fan, Yurui
  • Liu, Lirong

Abstract

Energy storage is important in future power systems. However, the role of grid-scale energy storage in the power system and in the whole socio-economic system is unclear. A copula-based whole system model is developed to explore the economic and environmental effects of grid-scale energy storage, thus supporting the decision-making at micro and macro levels. A power system optimisation model is linked with an input-output model, and the copula function is embedded in the model to reflect the multiple and interactive uncertainties from electricity demand, emission constraints, and sector disaggregation. We conducted case studies on China and the UK in 2025 considering different storage technologies (Pumped hydro, Battery, Flywheels storage) to show the differences related with power systems and economic structures. We find that increasing energy storage capacity leads to increase in renewable generation capacity (solar generation in China and wind generation in the UK). Thus, it can reduce their total economy-wide carbon emissions. Uncertainty in sector disaggregation will have a large impact on carbon emissions in some extreme cases, especially in those sectors closely linked to the power sector and with high emission intensity.

Suggested Citation

  • He, Fan & Leach, Matthew & Short, Michael & Fan, Yurui & Liu, Lirong, 2025. "A copula-based whole system model to understand the environmental and economic impacts of grid-scale energy storage," Applied Energy, Elsevier, vol. 379(C).
    • Handle: RePEc:eee:appene:v:379:y:2025:i:c:s0306261924023183
    DOI: 10.1016/j.apenergy.2024.124935
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    References listed on IDEAS

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    2. Hu, Chao & Zhang, Jian & Wu, Tong & Liu, Yi & Xu, Minjie & Chen, Sheng, 2025. "Transient analysis of hydropower station with pressure-regulating valves considering effects of hysteresis and buffering," Energy, Elsevier, vol. 337(C).
    3. Liao, Huchang & Li, Xiaofang, 2025. "A multi-criterion decision making method for renewable energy storage technology selection with incomplete evaluation information," Technological Forecasting and Social Change, Elsevier, vol. 215(C).
    4. Li, Xinyuan & Ren, Kang & Zheng, Xiazhong, 2025. "Exploring the sensitivity of capacity configuration for multi-energy complementary system across multi-temporal scales," Energy, Elsevier, vol. 326(C).

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