China’s urban EV ultra-fast charging distorts regulated price signals and elevates risk to grid stability
Qìng Yu, Pengjun Zhao, Jiaxing Li, Han Wang, Jie Yan, Haoran Zhang · 2025 · 11 citationsRead the paper
The wide adoption of electric vehicles is driving the rapid deployment of ultra-fast charging stations, particularly in China. This study uses simulations based on extensive real-world charging data from major Chinese cities and finds that deploying 2000 ultra-fast charging stations in a city may increase the peak-to-valley differences of the public charging load by up to 31.61% daily relative to baseline cases. While integrating energy storage systems can help smooth short-term load volatility, it may simultaneously exacerbate short-term demand surges, particularly during the transition from high- to low-price periods. Under an unregulated scenario, large-scale deployment of ultra-fast charging stations with energy storage could raise peak loads by over 70−85% by 2030 and multiply them by up to 7.5 times by 2050. These findings underscore that a comprehensive rethinking of grid management strategies and market frameworks will be essential to ensure urban energy resilience in an era of rapid electric vehicle expansion. Ultra-fast charging for electric vehicles poses challenges to power grid stability. Here, the authors show that under time-of-use pricing in China, they create sharp demand peaks, and on-site energy storage can worsen the risk.
What the full text shows
Theory or simulation- Deploying 2,000 ultra-fast charging stations (UFCS) in a city increases daily peak-to-valley differences of public charging load. — up to 31.61% increase vs. baseline (Simulated urban environments in major Chinese cities)
- Unregulated arbitrage-driven energy storage systems (ESS) combined with UFCS significantly increase peak loads by 2030. — 70-85% increase (Unregulated market scenario, 1,000 UFCS stations)
- Unregulated ESS combined with UFCS could multiply peak loads by 2050. — up to 7.5 times higher than without ESS (Full deployment scenario by 2050)
- Standard planning reserve margins become insufficient as UFCS deployment scales. — 15% Capacity Reserve (CR) insufficient at 1,000 stations; 25% CR insufficient beyond 1,500 stations (2030 simulation case)
- Setup
- Dataset of 769,225 charging orders from 1,702 stations across Beijing, Shanghai, and Guangzhou over a 31-day period (Jan-Feb 2024).
- How
- The study used a data-driven simulation model based on real-world charging records to project grid loads under various UFCS deployment scales. It employed a three-stage piecewise charging profile (CC-CV) to estimate power demand and tested three ESS operational scenarios: unregulated, capacity charge, and demand response.
- Limitations
- Based on simulations and core assumptions rather than real-time large-scale UFCS deployment · Assumes technological and policy conditions remain constant except for UFCS and TOU pricing
Summarized by Gemma 4 from the open-access full text · 8 Oct 2026. Read it