Motivation or resistance: A multidimensional analysis of quantile network spillovers between smart grids and carbon markets from a digital technology perspective

The impact of digital technologies on risk contagion mechanisms in energy systems has emerged as a critical area of research. This study explores how digital technologies reshape risk contagion pathways between smart grids and carbon markets by integrating the time-varying parameter quantile vector autoregression model and network topology analysis. The findings indicate that: (1) Digital technologies amplify the short-term extreme risk linkages between smart grids and carbon markets, with the risk distribution exhibiting an asymmetric U-shaped pattern featuring a fatter left tail. (2) Risks propagate along this pathway: smart grid and ultra-high voltage → grid equipment → the carbon market. As the quantiles increase, the risks transmitted from the smart grid weaken, while the risks absorbed by the carbon market strengthen. (3) Driven by digital technologies, the risk network structure under extreme upward markets is more complex, characterized by dynamic shifts in the risk roles of ultra-high voltage and grid equipment over both short and long terms. However, the smart grid maintains the risk transmitter. (4) Under extreme downward markets, big data and cloud computing exacerbate risk contagion, whereas the mobile internet mitigates such contagion. Under extreme upward markets, artificial intelligence reinforces risk contagion, while big data and mobile internet alleviate such contagion. The results provide a reference for preventing cross-market risk contagion.