Considering the uncertainty on the network parameters in the optimal planning of measurement systems for Distribution State Estimation

This paper proposes an optimization algorithm based on the techniques of the dynamic programming and suitable to choose the optimal number and position of the measurement devices in distribution state estimation procedures used in modern electric distribution network. The goal is to guarantee at the same time the minimum cost and the accuracy required to the measured data needed to operate management and control issues, such as energy dispatching and protection coordination. Both the uncertainty introduced by the measurement devices and the tolerance in the knowledge of the network parameters (line impedances) are taken into account in the proposed approach. Random changes of the loads are considered to establish adequate reference conditions for the tests. Tests relevant to a real size distribution network are presented to show the validity of the proposed approach. The results emphasize how the influence of the tolerance on the network parameters can be dramatically minimized by suitably choosing the algorithm to be implemented to solve the distribution state estimation problem.