Wireless powered communication networks are becoming an effective solution for improving self sustainability of mobile devices. In this context, a hybrid access point transfers energy to a group of nodes, which use the harvested energy to perform computation or transmission tasks. While the availability of the wireless energy transfer mechanism opens up new frontiers, an appropriate choice of the network parameters (e.g., transmission powers, transmission duration, amount of transferred energy, etc.) is required in order to achieve high performance. In this work, we study the throughput optimization problem in a system composed of an access point which recharges the batteries of two devices at different distances. In the literature, the main focus so far has been on slot-oriented optimization, in which all the harvested energy is used in the same slot in which it is harvested. However, this approach is strongly sub-optimal because it does not exploit the possibility to store the energy and use it at a later time. Thus, instead of considering the slot-oriented case, we address the long-term maximization. This assumption greatly increases the optimization complexity, requiring to consider, e.g., the channel state realizations, its statistics and the batteries evolution. Our objective is to find the best scheduling scheme, both for the energy transferred by the access point and for the data sent by the two nodes. We discuss how to perform the maximization with optimal as well as approximate techniques and show that the slot-oriented policies proposed so far are strongly sub-optimal in the long run.