Abstract

Abstract

Abstract
This work proposes an innovative method based on autoencoders to perform state estimation in distribution grids, which has as main advantage the fact of being independent of the network parameters and topology. The method was tested in a real low voltage grid (incorporating smart grid features), under different scenarios of smart meter deployment. Simulations were performed in order to understand the necessary requirements for an accurate distribution grid state estimator and to evaluate the performance of a state estimator based on autoencoders.

Abstract
This paper presents a model for breaker status identification and power system topology estimation based on a mosaic of local auto-associative neural networks. The approach extracts information from values of the analog electric variables and allows the recovery of missing sensor signals or the correction of erroneous data about breaker status. The results are confirmed by extensive tests conducted on an IEEE benchmark network.

Abstract
This work presents a methodology for selecting the most relevant measurements for real-time power system monitoring. A genetic algorithm is employed to find the meter plan, composed of relevant, real-time measurements and pseudo-measurements that present the best compromise between investment costs and state estimation performance. This is achieved by minimizing both the number of real-time measurements in the power network and the degradation of the estimated states. Performance measures based on the Information Theory are investigated. Simulation results illustrate the performance of the proposed method.

Abstract
To enable the use of smart metering historical information of energy measurements in real time network operation, in this paper is proposed the generation of pseudo-measurements, which can be combined with real-time SCADA measurements and feed an online state estimation procedure. Hence increasing the network operator's situational awareness. The goal is to obtain a better representation of the network operation points, voltage values, than the one that is possible to obtain with the direct use of smart metering data, which is based on average values, by increasing the amount of available real time data points.