One of the typical features of future power systems is the high penetration of photovoltaic (PV) power generation, the uncertainty of which becomes an important factor affecting the secure operation of distribution networks (DNs). A battery’s function as an energy storage device is essential in guaranteeing the DN’s reliable and secure operation. Considering the voltage regulation economy of battery energy storage system (BESS), this paper proposes a voltage control strategy of DN with PV and energy storage considering battery lifetime based on deep reinforcement learning (DRL). Firstly, a battery lifetime loss model is established using the modified throughput method, and considering the uncertainty of PV output, a coordinated voltage control strategy for PV inverter and BESS is proposed to establish an optimization model with the goal of minimizing the voltage deviation and operating costs of the DN. Secondly, a Markov decision process is created from the model, and a model-free DRL proximal policy optimization (PPO) algorithm is used for training and solving the control strategy. Finally, simulation analysis is carried out in the IEEE 33-node system, and successful regulation of the voltage within the secure range is achieved, confirming the efficacy of the approach proposed in this study.