The need for higher frequency in state estimation execution covering larger supervised networks has led to the investigation of faster and numerically more stable state estimation algorithms. However, technical developments in distributed energy management systems based on fast data communication networks open up the possibility of parallel or distributed state estimation implementation. In this paper, this possibility is exploited to derive a solution methodology based on conventional WLS distributed state estimation algorithms and an intelligent ANN technique. Numerical experiments show suitable performance of the proposed method with regard to estimation accuracy, convergence robustness and computational efficiency. The above methods are demonstrated with IEEE 37 bus distributed distribution system with comparison of simulated estimated outputs.