As Moore’s law has slowed down, we need to explore opportunities to save energy and power in parallel applications, especially during data movement. This is particularly true within the partitioned global address space (PGAS) model, where there is great potential for energy savings across distributed data accesses on large exascale computing systems. This paper explores the potential of message aggregation strategies within PGAS models, specifically focusing on OpenSHMEM, to improve energy efficiency on the CPU and memory of a node. Using the conveyor library, which aggregates small messages for network-efficient communication, we compare its performance gains in execution times against the energy reductions achieved. We compare applications from the bale effort as implemented through either atomic, get, and put or conveyor approaches on the Frontier supercomputer. Our preliminary results show significant improvements in both performance and energy consumption. These findings suggest that message aggregation can play an important role in addressing the challenges of PGAS energy consumption in modern HPC systems.