Transportation–Energy Integration in Highway Service Areas: Synergistic Effects of Photovoltaics, EV Charging, and New Business Formats via Random Forest Regression

Against the background of the acceleration of the integration of the “double carbon” target and transportation energy, the green transformation and business model innovation of highway service areas, as a high-energy-consumption traffic node, are becoming more and more urgent. However, the existing research focuses on a single technology path, and lacks a systematic quantitative evaluation of the “PV–charging–new format” coordination mechanism and its operating efficiency. Therefore, this paper proposes a collaborative framework that integrates photovoltaic power generation, new energy charging piles, and diversified new formats, and introduces a random forest regression algorithm. Based on the actual operation data of the Guangxi expressway service area, the synergistic effect and regional heterogeneity of multiple factors are systematically evaluated. The results show that a photovoltaic system can reduce the unit electricity price by 25–35%, and the investment recovery period is about 7 years. When the penetration rate of charging piles increases to 35%, the annual income can reach CNY 3.285 million, and the return on investment increases to 2.3 times when the utilization rate exceeds 80%. The new business combination can increase the average daily income by 13.3–26.7%. At the same time, the coordinated implementation of the three elements can achieve an annual net income increase of 27–32%, which is better than the linear superposition of the benefits of a single measure. In addition, the analysis of regional heterogeneity shows that the photovoltaic benefit in the western mountainous area is outstanding, the charging benefit in the coastal area is significant, and the comprehensive benefit in the central hub area is the best. This study provides a quantitative basis to support decisions on the differentiated development path of expressway service areas in the background of traffic–energy integration.