With the widespread construction of highways in the mountainous regions of southwest China, the number of service areas and long-distance tunnels has surged, leading to a significant increase in electricity consumption along highways. In light of China's heightened focus on the “dual carbon” goals, the construction of photovoltaic (PV) microgrids at service areas has emerged as a crucial means of energy conservation and carbon emission reduction. Efficient utilization of photovoltaic power and ensuring power supply balance within microgrids are critical considerations for PV microgrid systems. This paper proposes a dynamic segmentation optimization model for PV microgrids to address power balance and cost-effectiveness issues in highway PV microgrid systems. The model employs an intelligent adjustment mechanism to dynamically segment PV systems based on actual grid load demand and solar output, thereby optimizing energy utilization efficiency and economic returns. Considering the intermittent and unstable nature of solar power generation, the model incorporates advanced optimization algorithms and real-time data processing to tackle challenges posed by varying weather conditions and seasons. Through case studies, this paper validates the effectiveness of the model in enhancing the utilization and economic benefits of PV microgrids under various environmental conditions. Compared to traditional static segmentation methods, the proposed model demonstrates superior performance.