Comparison of the performances of Distribution State Estimation algorithms: Classical Newton approach and PSO approach

Existing electricity distribution management systems (DMS) have been designed using operational and algorithmic procedures that are highly centralised. As more of the distribution network becomes active, accurately estimating the state of the system becomes essential and therefore DMS must include functions to achieve the required near to real-time state estimation. The objective of this paper is to evaluate and to compare the performances obtained with two different solutions developed by EDF R&D for the Distribution State Estimator (DSE) algorithm for MV networks: classical optimization resolution approach using a Newton resolution algorithm on one side and a Particle Swarm Optimization algorithm on the other side. The performances of these solutions are evaluated in terms of precisions obtained for the estimates related to the primary and secondary variables and of computation times.