The proliferation of large-scale electric vehicle charging stations has made power quality issues increasingly prominent. While conventional unidirectional charging stations already present complex harmonic interactions, the development of vehicle-to-grid technology has introduced more complex harmonic coupling in bidirectional charging stations. To improve the accuracy of harmonic power flow analysis, this paper proposes a hybrid mechanism–data-driven dynamic harmonic coupling matrix model (DHCMM) for power quality assessment in bidirectional charging stations. A DHCMM-based harmonic power flow calculation process is further developed to evaluate the harmonic impact on power distribution networks following station integration. The proposed method is validated using field measurement data from an actual bidirectional charging station with tests covering typical charging, discharging, and dynamic transition scenarios. Results show that the DHCMM provides accurate harmonic modeling with both the total harmonic current distortion estimation error and the voltage fluctuation estimation error within 5%. The validated model is applied to an IEEE 33-bus distribution system. A comparison of the results reveals that the power quality impact of such stations extends beyond the point of connection to neighboring nodes, while the proposed DHCMM outperforms mechanism-based models including the static harmonic coupling matrix model and the Norton harmonic equivalent model as well as data-driven models such as the backpropagation neural network and least squares support vector machines.
Huang et al. (Mon,) studied this question.