关键词: 能耗, 公路隧道, 风光水储互补发电系统, 离散型自适应粒子群优化算法, 容量配置

Abstract: 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.

Key words: energy consumption, highway tunnel, complementary power generation system of wind-solar-water-energy storage, discrete adaptive particle swarm optimization algorithm, capacity configuration