OVERVOLTAGE DURING ARC SINGLE-PHASE EARTH FAILURES IN 35 KV ELECTRICAL NETWORKS

The results of the study of overvoltages during arc single-phase earth faults of intermittent nature in the 35 kV electric network with isolated neutral are presented. Computer simulations of transients in the electrical network have obtained the maximum multiplicities of overvoltages at the point of occurrence of single-phase arc earth faults, which exceed theoretically expected according to known theories of the occurrence and development of overvoltages. The change of the overvoltage level on the 35 kV busbars of the network substations, electrically connected to the place of occurrence of the single-phase earth fault, and the influence of the cable line on the overvoltage multiplicity are shown. Ref. 12, fig. 3, table.

METHODS OF SEARCHING FOR ANOMALIES IN THE DATA PROVIDED BY MODE PARAMETERS MEASUREMENTS OF THE ELECTRIC NETWORK

The materials of the article are an overview of the problems of development of electric power systems in the context of data collection and processing of mode parameters and analytical review of methods of search and detection of anomalies in data of synchronized vector measurements of mode parameters of electric network. The classification of anomalies, problems that arise during their search, classification of methods of search and detection of anomalies, as well as modern methods of finding anomalies in the data of synchronized vector measurements of power systems are considered.

An Automated Approach for Electric Network Frequency Estimation in Static and Non-Static Digital Video Recordings

Electric Network Frequency (ENF) is embedded in multimedia recordings if the recordings are captured with a device connected to power mains or placed near the power mains. It is exploited as a tool for multimedia authentication. ENF fluctuates stochastically around its nominal frequency at 50/60 Hz. In indoor environments, luminance variations captured by video recordings can also be exploited for ENF estimation. However, the various textures and different levels of shadow and luminance hinder ENF estimation in static and non-static video, making it a non-trivial problem. To address this problem, a novel automated approach is proposed for ENF estimation in static and non-static digital video recordings. The proposed approach is based on the exploitation of areas with similar characteristics in each video frame. These areas, called superpixels, have a mean intensity that exceeds a specific threshold. The performance of the proposed approach is tested on various videos of real-life scenarios that resemble surveillance from security cameras. These videos are of escalating difficulty and span recordings from static ones to recordings, which exhibit continuous motion. The maximum correlation coefficient is employed to measure the accuracy of ENF estimation against the ground truth signal. Experimental results show that the proposed approach improves ENF estimation against the state-of-the-art, yielding statistically significant accuracy improvements.