State estimation of active distribution system based on the factor graph analysis and belief propagation algorithm

With the growing penetration of distributed energy resources, the operating characteristics of distribution system are becoming more and more complex. High accuracy estimation method is crucial for safe and effective grid operation. In this paper, a novel state estimation approach in consideration of the output uncertainties of distributed generators is proposed based on the factor graph analysis and belief propagation algorithm. Firstly, measurement functions of state estimation are linearized using simple variable substitutions, and the output uncertainty of distributed generators is modeled as a Gaussian mixture model. Then, the distribution grid is regarded as a factor graph through defining measurement functions as factor functions. Belief propagation algorithm is used to conduct statistical inference. Finally, an IEEE-33 bus simulation system is utilized to evaluate the effectiveness of the proposed method. The results show that compared with conventional methods, such as the branch current method and weighted least squares, BP algorithm not only can improve the estimation accuracy, but also has an obvious advantage in iteration times.