Optimal Scheduling of Tunnel Optical Storage System Based on Typical Day Identification

This paper addresses the temporal mismatch between energy supply and demand in highway tunnels caused by the rising share of photovoltaic (PV) power. To ensure power stability and promote local consumption of clean energy, a PV-storage integrated microgrid system is proposed. Tailored for tunnel scenarios with rigid loads and high reliability requirements, an energy scheduling mechanism—prioritizing PV usage, self-consumption, and surplus storage—is developed under restricted grid access conditions. An economic dispatch model is constructed to minimize operating costs, incorporating constraints such as PV curtailment penalties and storage behavior. To enhance modeling efficiency and representativeness, a K-means clustering method jointly considers PV output and load profiles to identify typical days. Using real tunnel load data and solving the model with YALMIP and Gurobi, the study evaluates how varying energy storage configurations impact system cost, PV utilization, and storage efficiency. Results show that reasonable storage deployment can significantly reduce total operating costs. A 75% storage allocation strikes the best balance between cost and renewable energy use, confirming the strategy’s practicality and effectiveness.