State estimation for large-scale power systems based on hybrid CPU-GPU platform

The acceleration of state estimation has a significant beneficial effect on monitoring, dispatching and stability of power system. The increasing scale of power system brings more and more pressure to the state estimation of power system. The graphic processing unit (GPU) which features the massive concurrent threads and excellent floating point performance brings a new chance to the area of state estimation of power system. In this paper, a state estimation method which bridges merits of GPU and central processing unit (CPU) is introduced. Case studies demonstrate that the proposed state estimation method offers a significant improvement in terms of efficiency over other existing method.