Modeling and Optimization of the "pV-Storage-Charging-Swapping" System for the Transportation at Open-pit Coal Mines

Against the backdrop of "carbon peaking and carbon neutrality"goals, the substitution of fuel vehicles with pure electric mining trucks has been accelerated to reduce carbon emissions in transportation at open-pit coal mines. However, in the absence of systematic planning and scheduling, grid loads rise, vehicle queues lengthen, and tariff-storage mismatches emerge, thereby undermining the expected benefits. Therefore, this study proposes an integrated optimization model based on Mixed-Integer Linear Programming (MILP) that incorporates "photovoltaic energy storage, charging, and battery replacement"strategies. The model integrates battery flow, time-of-use pricing, and carbon subsidies within a unified framework to facilitate comprehensive economic and environmental optimization. First, using measured data from an open-pit coal mine in Inner Mongolia, intelligent charging and swapping scheduling paired with an appropriate increase in backup battery capacity can effectively reduce peak power demands and alleviate vehicle queues without the need for photovoltaic power generation. Second, integrating photovoltaic power generation leads to a substantial shift of daytime load to local clean power sources, thereby reducing strain on the power grid and costs. Finally, when considering carbon subsidies, the optimal solution suggests enhancing the number of backup batteries to further stabilize load profiles and decrease total costs. In conclusion, the proposed integrated optimization framework of "photovoltaic energy storage, charging, and battery replacement"not only successfully mitigates peak loads and minimizes potential queues but also enhances economic benefits and emission reductions.