V2G auxiliary frequency regulation control strategy based on state-of-charge change and user requirements

• In the context of EV participating in primary frequency regulation, a control strategy is proposed to dynamically adjust the unit regulation power coefficient based on the S-shaped variation of SOC. The selection of frequency regulation depth is guided by the SOC range, enabling automatic adaptation and seamless modulation of frequency regulation output. • In order to address the demand for users and grid frequency regulation, we propose the utilization of a frequency regulation capability coefficient β to optimize the factors involved in frequency regulation. By considering user charging plans and frequency regulation requirements, constraints are imposed on EVs' frequency regulation output to prevent excessive participation that may lead to their withdrawal from frequency regulation, thus ensuring maximum utilization of EVs' contribution to frequency regulation. • The control strategy proposed in this article for EV frequency control incorporates multiple factors, including the SOC, frequency deviation, and user demand, thereby achieving a relatively stable power output during the period of frequency adjustment. Large-scale grid-connected electric vehicles (EVs) can act as distributed energy storage units to provide frequency regulation (FR) services. Current EV frequency control relies mainly on grid frequency deviation and user charging profiles but ignores dynamic changes in state of charge (SOC) and regulation characteristics, leading to inefficient FR and unmet charging demands. To address this, this paper proposes a dynamic SOC-based adjustment of unit power and FR capability coefficients, enabling coordinated grid frequency stabilization while meeting charging requirements. Simulations verify the strategy: When SOC is within the optimal FR range, it increases FR output by 2.5 kW over conventional methods. Near full charge or discharge limits, FR power drops near zero, allowing safe exit from regulation. For example, with a 3-hour charging time, the FR participation factor reaches 0.7, yielding 3 kW output. The results show enhanced FR capability while flexibly balancing grid frequency, SOC levels, and user charging needs for optimized control.