为降低公路隧道的电力运营成本，探究可再生能源互补发电系统在公路隧道的应用前景，研究合适的容量配置求解方法。建立利用风、光、水和储能设备的互补发电系统为公路隧道提供电力资源。以特长公路隧道（总长7.1 km）为估算模型，采用改进后的粒子群优化算法，即离散型自适应粒子群优化算法，以全生命周期的建设成本和设备维护成本最小为目标函数，以缺电负荷率(LPSP)和储能电池的状态为约束，对风力发电设备、光伏发电设备、水力发电设备和储能设备的最优容量配置进行求解。结果表明： 1）对比标准粒子群算法，离散型自适应粒子群优化算法的总投入成本更少，寻优能力更强； 2）对比该隧道1年的用电成本，前期投入将在5年内回本； 3）在风光水储互补发电系统的设备全生命使用周期的20年内，该隧道可节省1 920.39万元电费。

To lower the electricity operational costs of highway tunnels, the application prospects of renewable energy complementary power generation systems in highway tunnels are explored, and suitable methods for solving capacity configuration are examined. Furthermore, a complementary power generation system using wind, solar, water, and energy storage devices to supply power to highway tunnels is established. Using a particularly-long highway tunnel (total length of 7.1 km) as the estimation model, an improved particle swarm optimization algorithm, namely the discrete adaptive particle swarm optimization algorithm, is employed. This algorithm is used for solving the optimal capacity configuration of wind power, photovoltaic power, hydro power, and energy storage devices, taking the minimal construction and equipment maintenance costs over the entire lifecycle as the objective function and the power shortage load rate and the state of the energy storage battery as constraints. The results indicate the following: (1) Compared to the standard particle swarm algorithm, the discrete adaptive particle swarm optimization algorithm has lower total investment costs and stronger optimization capabilities. (2) Compared to the tunnel′s annual electricity costs, the initial investment will be recouped within 5 years. (3) Over the 20-year full lifecycle of the equipment in the wind-solar-water-energy storage complementary power generation system, the tunnel can save 19.203 9 million yuan in terms of electricity costs.