Evaluating Load-Price Correlation: Case Study from a Park-Level Charging

This study aims to analyze the correlation between the charging load at electric vehicle charging stations and pricing policies to clarify the impact of price factors on user charging behavior. Employing Random Forest Regression and Ridge Regression models, the study models and analyzes the relationship between charging load and time-of-use electricity prices, as well as service fees. Descriptive statistical analysis was conducted to thoroughly examine the characteristics of the data, followed by the application of T-tests and the 3σ principle to process outliers, ensuring the accuracy of the analysis. The model outcomes revealed the differential effects of time-of-use electricity prices on charging load across various periods and the sensitivity of charging behavior to service fee adjustments. The findings indicate that during peak periods, the suppressive effect of electricity prices on charging demand is limited, while adjustments to service fees can effectively guide user charging behavior. This research provides data support and strategic recommendations for pricing strategies and load management at charging stations, offering practical guidance for optimizing the operation of charging stations.