Due to the demand for the mass distributed computing and efficient data transmission, grid systems start to integrate with P2P technology to support high-performance distributed computing. However, the workload on P2P grid computing systems could be highly variable and its unstable behavior could intensely affect the system performance. In general, the high variability of the workload leads to wrong load balancing decisions made by out-of-date resource status and the wrong decisions are difficult to be corrected during execution. This study proposes a dynamic adaptive load balancing strategy to dynamically balance the workload across grid sites. This load balancing strategy can not only deal with the workload variability, but also improve the resource utilization in P2P grid systems. This prototype is implemented on the sites of the Taiwan UniGrid. The experimental results show that the proposed algorithm performs well and could efficiently distribute the workload for execution.