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The energy constraint of sensor nodes is the key factor that restrict the life of wireless sensor networks. So an effective method of dynamic power management (DPM) that based on grey model is proposed to make economical use of energy. Historical data collected of sensor node is used to predict the future value in this method, while the parameters are adjusted automatically in the process of prediction to realize the adaptive prediction. Compared with the algorithm of wavelet and AR, the accuracy of prediction is improved. The basic idea is to decide the working pattern of the entire sensor networks by the node of Sink, and in the next period sensor nodes do not send back data if their observed values are not out of threshold. To reduce energy consumption of the entire sensor networks by shortening the working hours and reducing transmitted messages between the nodes. Theory analysis and experiment result show that the method of this paper is effective not only in the predictive accuracy but also in the energy efficiency.