INTELLIGENT ENERGY SUPPLY MANAGEMENT SYSTEM IN THE MUNICIPAL SECTOR


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Authors

Keywords:

intelligent system, energy supply management, utilities, machine learning, energy efficiency, optimization, data analysis

Abstract

The subject of this study is the methods, tools and intelligent systems for managing energy supply in the public utilities sector. The object of the study is the process of energy management in the municipal sector. The purpose of the study is to develop an intelligent energy management system in the public utilities sector. To achieve this goal, the following tasks were solved: the main problems of energy efficiency in the housing and communal services sector were analyzed and ways to solve them using modern technologies were proposed; the methodology for developing an intelligent system (SmartGrid) was chosen; the architecture of an intelligent energy management system was proposed; the algorithm of the intelligent energy saving management component was presented; to determine the electricity consumption in the system, a methodology was used that involves the collection and analysis of data from the Machine learning algorithms, such as the support vector method, neural networks, and decision trees, are used to determine the optimal mode of energy consumption. Conclusions: the use of the proposed system will reduce the cost of energy supply in the municipal sector and increase its energy efficiency, the possibility of integration with other municipal management systems.

Author Biographies

Igor NEVLUDOV, Kharkiv National University of Radio Electronics

Head of the Department of Computer-Integrated Technologies, Automation and Robotics, Doctor of Technical Sciences, Professor

Kyrylo KRUSTALOV, Kharkiv National University of Radio Electronics

Head of the Research Department, Associate Professor of the Department of Computer-Integrated Technologies, Automation and Robotics, PhD in Engineering, Associate Professor

Sofia KRUSTALOVA, Kharkiv National University of Radio Electronics

Associate Professor of the Department of Computer-Integrated Technologies, Automation and Robotics, PhD in Engineering, Associate Professor

Shakhin OMAROV, Kharkiv National University of Radio Electronics

Professor of the Department of Computer-Integrated Technologies, Automation and Robotics, Doctor of Economics, Associate Professor

References

O’Dwyer, E., Pan, I., Acha, S., & Shah, N. (2020). Smart Energy Systems for Sustainable Smart Cities: Current Developments, Trends and Future Directions. Renewable and Sustainable Energy Reviews, 131, 109993. doi: 10.1016/j.rser.2020.109993

Siano, P. (2014). Demand response and smart grids–A survey. Renewable and Sustainable Energy Reviews, 30, 461-478. doi: 10.1016/j.rser.2013.10.022

Ahmad, M. S., Mohamed, A., & Baharudin, R. (2020). Optimal scheduling and control of energy management systems for smart homes. Renewable and Sustainable Energy Reviews, 119, 109555. doi: 10.1016/j.rser.2019.109555

Tan, C. W., Wong, C. Y., & Lai, K. S. (2018). Energy management systems in smart homes: A review. Renewable and Sustainable Energy Reviews, 82, 1390-1400. doi: 10.1016/j.rser.2017.10.089

Zhang, B., Xu, Y., Li, Q., Huang, J., & Li, L. (2017). Demand response in the smart grid: A review. Renewable and Sustainable Energy Reviews, 75, 733-747. doi: 10.1016/j.rser.2016.11.034

Al-Sumaiti, A. S., & Zeineldin, H. H. (2020). Smart microgrid energy management system: A comprehensive review. Renewable and Sustainable Energy Reviews, 124, 109788. doi: 10.1016/j.rser.2020.109788

Liu, C., & Tao, X. (2017). An improved particle swarm optimization for energy management of smart buildings. Energy and Buildings, 152, 240-253. doi: 10.1016/j.enbuild.2017.08.009

Published

2023-12-18 — Updated on 2023-12-27

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How to Cite

NEVLUDOV, I., SLUSAR, A., KRUSTALOV, K., KRUSTALOVA, S., & OMAROV, S. (2023). INTELLIGENT ENERGY SUPPLY MANAGEMENT SYSTEM IN THE MUNICIPAL SECTOR. Journal of Natural Sciences and Technologies, 2(2). Retrieved from https://journalofnastech.com/index.php/pub/article/view/32 (Original work published December 18, 2023)

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