Abstract: Due to the randomness and volatility of renewable energy generation, the integration of large renewable energy bases such as "deserts, gobi, wastelands" leads to complex and variable power flow in the power grid, increasing the probability of line blockage, which poses new challenges to transmission network planning. Dynamic thermal rating (DTR) technology can evaluate the current carrying capacity of transmission lines based on weather conditions and equipment status, effectively tapping into the flexibility of the power grid. In addition, the bidirectional rapid regulation of energy storage can also alleviate the transmission pressure and have a certain transmission substitution effect. Therefore, this paper proposes a collaborative robust planning model for transmission network and energy storage that incorporates the DTR system configuration. To fully explore the synergistic effect of transmission line DTR system and energy storage, the typical daily operation simulation is embedded in the planning model. Using typical daily meteorological data from multiple regions, the dynamic transmission capacity of power lines is assessed through the DTR evaluation method. Additionally, the uncertainty in renewable energy output is addressed using robust optimization techniques, allowing for better utilization of energy storage's flexible regulation capabilities. An improved column and constraint generation (C&CG) algorithm is proposed for solving the robust planning model, and an imprecise C&CG iteration method is used to accelerate the solution. The analysis of the northwest power grid indicates that by co-planning transmission networks and energy storage while considering DTR, the number of planned lines can be reduced from 29 to 10. This approach also enhances the efficiency of line utilization. Furthermore, it decreases the system's operating costs by 9.6% and increases the renewable energy accommodation rate from 87.7% to 95.1%