The emergence of locally produced renewable energies induces the appearance of a new generation of local energy players, which are at the same time producers and consumers. In case of time dependent solar energy production, it raises the question of synchronizing production and consumption. We deal here with this issue, in the context of an experimental Solar Hydrogen (H2) production platform. More precisely, we try here to simultaneously schedule a H2 fueled vehicle which follows a pre-computed route while being compelled to periodically refuel, and the H2 production micro-plant which is required to produce related energy under time dependent production costs and productivity rates, both processes being subject to storage capacity constraints. In order to do it, we design a global dynamic programming (DP) algorithm for the resulting NP-Hard problem. This DP algorithm involves a 2D time space which links energy consumption by the vehicle and its production by the micro-plant. Since the number of states induced by this DP algorithm becomes an issue as soon as the size of the problem increases, we first propose a theoretical Polynomial Time Approximation Scheme (PTAS), next design several practical pruning devices and finally perform numerical tests in order to check their efficiency.