AbstractStratified thermal energy storage (TES) tanks are widely used in thermal power plants to enhance the electric power peak load shifting capability and integrate high renewable energy shares. In this study, a data‐driven surrogate modeling and optimization study of the unequal diameter radial diffuser previously proposed by the present authors is conducted. First, based on the orthogonal experimental design, numerical experiments are performed to generate the performance database. Then, the database is used to establish the data‐driven surrogate model via the support vector machine. Subsequently, the single‐objective optimization and multiobjective optimization of an unequal diameter radial diffuser are conducted using the genetic algorithm. For the single‐objective optimization, the optimal thermocline thickness is 0.829 m when the diameter ratio of the long baffle and the tank is 0.426, the diameter ratio of the short baffle and the long baffle is 0.823, and the distance between the two baffles is 228.51 mm. For multiobjective optimization, the obtained Pareto optimal solutions are obtained. Under the premise of maintaining excellent thermal stratification, the selected Point C can reduce the steel cost by 88.1%. The research results are helpful for designing efficient and economical unequal diameter radial diffusers for TES tanks.