Concerning the problem of high energy consumption caused by data collision and cluster selection process in dynamic clustering target tracking of Wireless Sensor Network (WSN), a dynamic clustering method based on energy optimization for WSN was proposed. Firstly, a time division election transmission model was proposed, which avoided data collision actively to reduce energy consumption of nodes in a dynamic cluster. Secondly, based on energy information and tracking quality, the energy-balanced farthest node scheduling strategy was proposed, which optimized custer head node scheduling. Finally, according to the weighted centroid localization algorithm, the target tracking task was completed. Under the environment of random deployment of nodes, the experimental results show that, the average tracking accuracy of the proposed method for non-linear moving objects was 0.65 m, which is equivalent to that of Dynamic Cluster Member Selection method for multi-target tracking (DCMS), and improved by 45.8% compared to Distributed Event Localization and Tracking Algorithm (DELTA). Compared with DCMS and DELTA, the proposed algorithm can effectively reduce energy consumption of the dynamic tracking clusters by 61.1% and prolong the network lifetime.