To address the challenges of sustainable development in high-energy consumption and carbon-intensive operations in open-pit mining, this paper proposes an economic operation collaborative optimization framework for integrated photovoltaic-energy storage-charging battery swapping stations of electric mining truck fleet. By constructing a high-resolution dynamic load model, the spatiotemporal characteristics of battery swapping events and the impact of state of charge segmented charging behavior on power demand are precisely depicted. The framework integrates a mixed-integer nonlinear programming (MINLP) model to coordinate photovoltaic output, energy storage scheduling, and interaction with the power grid, aiming to maximize renewable energy utilization and minimize grid electricity purchase costs. Given the non-convexity and combinatorial complexity of the model, a custom solution algorithm based on adaptive large neighborhood search (ALNS) is designed to ensure both feasibility and computational efficiency. A case study based on real data from an open-pit mine in Inner Mongolia, China, demonstrates that the proposed algorithm can reduce the grid electricity purchase costs by 5.3% and increase the load share of photovoltaic and energy storage to 32.1% and 23.1%, respectively, validating the effectiveness of the model in optimizing energy scheduling and economic benefits. This study provides theoretical support and practical solutions for the collaborative optimization of integrated energy systems in open-pit mining operations.