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In this paper, we consider an energy harvesting device-to-device (D2D) communication system, where D2D transmitter can use mode A to directly communicate with D2D receiver or use mode B as a relay to assist cellular communication while communicating with D2D receiver by adopting non-orthogonal multiple access technology. Firstly, the outage probability expression in two modes is derived, and the communication mode is determined according to outage performance. Then, assuming that the full system information is available, the channel allocation and relay selection are completed by Kuhn–Munkres algorithm, and the offline power allocation of D2D users is realized by reinforcement learning. Next, the offline optimization results are taken as the training data set to train the neural network, and the optimal model of the transmission power is obtained. Considering the transmission power constraint, the online power allocation optimization algorithm is further proposed. Numerical results demonstrate the accuracy of derived outage probability, and the proposed resource allocation algorithm can improve the performance of hybrid system. [ABSTRACT FROM AUTHOR]