Consider a stochastic wireless device-to-device (D2D) caching network with nodes that are harvesting energy from external sources at random times. Each node is equipped with a cache memory, where the node prefetches maximum distance separable (MDS) coded packets of the files from a given library. When a node requests a file from this library, neighbouring nodes are asked to send the relevant missing subfiles over noisy channels. This work presents different selection strategies to determine which neighbouring nodes should transmit which missing subfiles. The strategies can roughly be divided into three categories: sequential strategies where transmission stops when the requesting node has correctly decoded enough subfiles; coordinated strategies where the requesting node is informed about the other nodes' cache contents and centrally decides which node should send which file; and adaptive strategies where the requesting node sequentially decides on which files should be sent in function of the subfiles that it previously decoded correctly. Our numerical simulations show that at moderate energy levels or when there are many file requests, sequential strategies perform significantly worse than coordinated or adaptive strategies. On the other hand, at high energy levels sequential strategies (or even completely decentralized strategies) perform as well or even better. These latter strategies should thus be prefered as they come with less synchronization overhead and delay. The same applies for environments with only few transmission errors (i.e., in high quality channels).