Distributed State Estimation Based on the Realtime Dispatch and Control Cloud Platform

With the increasing integration of renewable energy, the inter-regional electrical connection is strengthened. Due to the large scale of power grid analysis and calculation, the traditional state estimation cannot meet the real-time requirements of the cloud platform. To this end, this paper proposes a distributed state estimation method based on parallelized stream computing, and decoupling the interconnected power grid with tie line to perform sub-region state estimation. The method divides the parallel computing sub-region based on the regulatory subregion of the actual grid and designs a regional tie line state estimation method based on the calculation speed and precision balance. After the completion of distributed parallel sub-regions and tie line state estimation, the sub-region calculations are corrected according to the sensitivity matrix coordination algorithm and the regional tie line state estimation result. The overall estimation result is then obtained through parallel normalization. Numerical tests on IEEE standard system and a large interprovincial interconnected power system have been done to verify that the proposed method can not only significantly improve the speed of state estimation calculation, but also reduce the interregional convergence correlation and the residual pollution.