Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/16744
Title: Класификација на нарушувањата на напонските сигнали во електроенергетската мрежа во реално време
Other Titles: Real-time classification of voltage disturbances in the power grid
Authors: Марковска, Марија
Keywords: voltage quality, feature extraction, classification, wavelet transform, real-time implementation
Issue Date: 2020
Publisher: ФЕИТ, УКИМ, Скопје
Source: Марковска, Марија (2020). Класификација на нарушувањата на напонските сигнали во електроенергетската мрежа во реално време. Докторска дисертација. Скопје: ФЕИТ, УКИМ.
Abstract: Future’s power grids consist of an increasing number of dispersed energy generation and consumption devices, which generate large amount of data. That increases the electricity sector’s need of proper hardware and software tools that will enable integration of relevant digital technologies in order to optimize the management and maintenance of the energy system. One of the biggest challenges in this system is to continuously ensure power supply, which quality is in accordance with some predefined standardized parameters. The effects of the disturbed voltage quality can lead to large number of technical problems, such as overheating, defects and even early aging of the equipment. They may affect the everyday, secure operation of the critical infrastructure. They may also result in significant financial losses. From that reason, the quality of the power is of great importance for its consumers, especially for the industry. Its price is high and it is rising as the number of the disturbances is increasing. Hence, there is a need of continuous monitoring, detection, classification and analysis of the voltage disturbances. All that would be much more efficient if it is performed in real time. Despite the continuous progress in the science and technology, the development of a system that would provide fast detection, classification and characterization of single and combined disturbances with high accuracy, and which could efficiently handle different noise levels, in order to improve the maintenance of the devices and the stability of the power grid, is still a challenge. That challenge represents the main subject of research in this paper.
Description: Докторска дисертација одбранета во 2020 година на Факултетот за електротехника и информациски технологии во Скопје, под менторство на проф. д–р Димитар Ташковски.
URI: http://hdl.handle.net/20.500.12188/16744
Appears in Collections:UKIM 02: Dissertations from the Doctoral School / Дисертации од Докторската школа

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