The modern energy requirements and the orientation towards Renewable Energy Sources
(RES) integration promote the transition of distribution grids from passive, unidirectional …

The problem of state estimation for unobservable distribution systems is considered. A deep
learning approach to Bayesian state estimation is proposed for real-time applications. The …

This paper presents an alternative approach to pseudo measurement modeling in the
context of distribution system state estimation (DSSE). In the proposed approach, pseudo …

Nowadays, with the massive integration of distributed renewable generation, electric
vehicles... to the distribution level of the electricity grid, the traditional strategy for monitoring …

An artificial neural network (ANN) is an effective and efficient approach for solving problems,
which require fast and complicated computation. The study proposed a PMU measurement …

Distribution system state estimation (DSSE) is one of the key functions used by distribution
system operators (DSOs) for the management and control of the distribution grids. In …

While the initial aim of smart meters is to provide energy readings for billing purposes, the
availability of these measurements could open new opportunities for the management of …

This paper, after a brief theoretical background to Artificial Neural Networks (ANNs) reviews
their utilization in the field of measurements. The criteria used for choosing between the …

The growing need and interest in real-time monitoring of large distribution networks
motivated by the rapid population of renewable sources, EVs and etc. demand a …

The problem of state estimation for unobservable three-phase unbalanced distribution
systems is considered. A Bayesian approach is proposed that combines Bayesian inference …