Electric vehicle (EV) charging piles serve as the critical link between operators and EV users, and their metering verification results are essential for safeguarding the legitimate rights and interests of both parties. With the ever-increasing number of charging piles, traditional on-site verification methods are becoming prohibitively costly and inefficient, making comprehensive coverage impractical. To address this issue, this paper proposes a constrained optimization-based method for estimating the metering operation error of DC charging piles. First, leveraging the topological structure of DC charging stations and the law of energy conservation, an analytical model linking station-level and pile-level metering errors is established. Considering that the AC/DC conversion efficiency within a charging pile is influenced by multiple factors, the model formulates a system of linear equations with the metering operation errors and AC/DC conversion efficiency as unknowns. Based on the type of charging piles and historical electricity consumption information, upper and lower bounds for both the metering errors and the conversion efficiency are determined. The resulting constrained optimization problem is then solved using the primal-dual interior point algorithm to obtain estimated metering errors for individual charging piles. Finally, the effectiveness of the proposed method is validated using real-world operational data from a DC charging station. This approach facilitates a paradigm shift in the metrological supervision of DC charging piles, transitioning from periodic batch testing to targeted anomaly detection.
Yu et al. (Thu,) studied this question.