Abstract: With the rapid development of current smart grid technology, the composition and operation mode of power systems are becoming more and more complex, and higher demand for the robustness and real-time performance of the state estimation is also generated. An adaptive robust state estimation based on dynamic partitioning and multiple estimation criteria is proposed. It screens out the suspicious measurement by fuzzy c-means clustering, and then realizes the dynamic partition of the system according to the location of suspicious measurement. Considering the characteristics and adaptability of different estimators, different estimation criteria are adaptively selected for the suspicious and normal measurement regions to ensure the estimation accuracy and the calculation efficiency at the same time. In order to ensure the consistency of the boundary bus information and the power flow of the tie line, the boundary coordination information is introduced as equality constraints and solved by alternating direction method of multipliers. Numerical simulations in IEEE systems show that the proposed method has ideal estimation accuracy and robustness,and its estimation efficiency is significantly improved compared with weighted least absolute value estimation.