Under the time-varying ocean current environment, the ocean current vector appends the time dimension, and the ocean currents can be further utilized to save autonomous underwater vehicles(AUVs) energy consumption in the temporal sense. In addition, classical greedy-based path planning algorithms are not applicable because non-aftereffect no longer holds in this environment. For the above reasons, an energy-optimal path planning algorithm in the time-varying ocean current environment is proposed, which combines the selection of path parameters and bilevel optimization. Firstly, both departure time and AUV propulsion velocity can wait for favorable ocean currents in time dimension, and AUV propulsion velocity is directly related to its energy consumption. So the departure time and propulsion velocity are introduced as path parameters. On this basis, the bilevel optimization is used as a path planning algorithm to solve the problem of non-aftereffect, and the applicability is analyzed. In the proposed approach, the task of path planning is divided into two parts: path planning and path optimization. In the path planning part, the ant colony system algorithm is used to construct the passageway, then the quantum particle swarm optimization algorithm is applied to further optimize the path parameters in the passageway at the path optimization part. The proposed algorithm ensures the global optimum of the resulting path and solves the problem of discrete motion directions caused by grid-based environment. Finally, to verify the validity of proposed scheme, several simulations, which the Kongsberg/Hydroid REMUS 600s is used as the model, are executed.