Abstract: In the context of energy transition and green development, the cost optimization of microgrids in highway service areas has become a crucial issue for the green transformation of transportation energy systems. This study aims to minimize the full life-cycle cost of microgrids in service areas by developing an optimization model for multi-energy power supply systems that integrate photovoltaic,diesel,energy storage, and grid interaction. Addressing the limitations of traditional optimization methods in handling high-dimensional nonlinear problems, a microgrid investment planning method based on dynamic inertia weighted particle swarm optimization algorithm (DIW-PSO) is innovatively proposed. By establishing a comprehensive cost model that includes equipment investment and operation & maintenance management, the collaborative optimization of system capacity configuration and operation strategies has been achieved. Case study results indicate that the proposed optimization scheme can reduce the average daily full life-cycle cost of the microgrid by 7%, increase the comprehensive energy utilization efficiency by 10.9%, and decrease the required capacity of the photovoltaic system by 10.8%,providing scientific decision support for the planning and design of microgrids in highway service areas.

    Key words: highway service area; microgrid; cost optimization; dynamic inertia weighted particle swarm optimization algorithm; full life-cycle cost