Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Nigar R. Aslanova
Azerbaijan State University of Economics (UNEC)
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Development of methods for managing energy consumption and energy efficiency in a common system Nigar R. Aslanova; Esmira J. Abdullayeva; Aleksandr V. Beloglazov
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1306-1313

Abstract

The work aims to analyze and examine renewable energy sources (RES) to develop interconnected energy efficiency and energy consumption management system by integrating the software-defined machine-to-machine (M2M) communication. The article’s objectives include analysis of using RES as alternative raw materials for electricity production, the study of intelligent technologies for integrating RES into monitoring and control systems, research of devices and methods for monitoring energy production and consumption, analysis of sensor application for automation of control systems in the energy sector, a study of data transmission and information processing rates. The study results showed that the data transfer rate was delayed by 6 seconds to process 1,000 MB of information. It has been proven that wind energy can be used most efficiently within a 12-hour daily cycle, in contrast to tidal energy and solar energy. It is shown that due to the cyclical nature of obtaining energy from renewable sources, they do not fully provide energy to a large city, on the basis of which it is necessary to additionally use other energy sources. Three different types of power generation facilities were examined and compared. Wind farms were found to have the highest potential for electricity generation, amounting to 1,600-1,700 kW.
Co-Authors Aleksandr V. Beloglazov Esmira J. Abdullayeva