Wireless sensor networks (WSNs) are widely deployed in many fields nowadays. However, the limited energy storage ability of sensor nodes causes great detrimental effect on the performance of the WSNs. Energy harvesting has been proved as one of the promising ways to replenish the energy constrained sensors for prolonging WSNs lifetime. Another exacerbated problem introduced by non-uniform energy distribution and nonoptimal energy management in WSNs also causes great challenge to WSNs. For realizing the efficient energy utilization and improving the performance of energy harvesting enabled WSNs, two transmission management schemes, Markov decision based packets aggregation allocation (MDPA) and partial Kalman filter with best-match aggregation (PKBPA), are proposed respectively in this paper. MDPA focuses on the node's own energy capabilities to decide the packets number for aggregation, while PKBPA decides the number of packets to be aggregated and transmitted based on the estimated energy state information of the node and its next hop. Simulation results show that the PKBPA scheme outperforms other schemes, especially when the energy is insufficient for the packets transmission.