Effect of smart meter measurements data on distribution state estimation

Smart distribution grids with renewable energy based generators and demand response resources (DRR) requires accurate state estimators for real time control. Distribution grid state estimators are normally based on accumulated smart meter measurements. However, increase of measurements in the physical grid can enforce significant stress not only on the communication infrastructure but also in the control algorithms. This paper aims to propose a methodology to analyze needed real time smart meter data from low voltage distribution grids and their applicability in distribution state estimation. Different scenarios are created to observe the algorithm performance and effects on the estimation quality. The CIGRE benchmark network for low voltage distribution grids is used for simulation and analysis. This work also investigates the necessity of proper load modelling to reduce the stress due to huge amount of measurement data by utilizing them smartly via state estimation.