Impact of time-of-use tariff policies on electric vehicle charging behavior and power system operation in Beijing

The rapid adoption of electric vehicles (EVs) creates both opportunities and challenges for urban power systems. This study evaluates EV charging impacts under time-of-use (TOU) pricing policies in the Beijing–Mengxi grid using an integrated framework that combines EV ownership forecasting, citywide charging simulation from real travel data, and an 8760-h mixed-integer programming model. Three EV adoption scenarios (baseline, accelerated, aggressive) and two TOU pricing policies (Policy A and Policy B) are examined with varying user response rates. By 2030, EV ownership in Beijing may reach 2.58 million units, equal to 14% of system load. Unmanaged charging could raise peak demand by 8.1% and widen peak-to-valley differences by 9.8%. TOU pricing mitigates these risks: Policy A reduces evening peaks, while Policy B shifts load to midday solar availability but may create secondary peaks at full response. Renewable penetration rises from 13.6% in 2018 to 46.1% in 2030, and TOU pricing lowers operating costs by 0.25–1.09 billion CNY in 2025 and up to 4.04 billion CNY in 2030. Coal plant start-up costs are significantly reduced, and loss-of-load costs in Beijing fall by 74.1% under Policy B. Emission outcomes are highly policy-sensitive. In 2025, Policy A delivers negligible reductions, while Policy B achieves102–400 tCO₂ abatement. By 2030, Policy B consistently reduces emissions by over 544 tCO₂, demonstrating the increasing synergy between demand-side flexibility and renewable integration. TOU pricing thus plays a pivotal role in supporting EV growth, reducing costs, and advancing carbon targets.