A Novel Energy Management System to Optimize the Energy Consumption in a Smart Building

Document Type : Research paper

Authors

1 Associate Professor of the Department of “Automation and Robotics”, JSC Almaty Technological University, Republic of Kazakhstan.

2 Ahl Al Bayt University / Kerbala / Iraq

3 Al-Manara College For Medical Sciences (maysan), Iraq.

4 Medical technical college, Al-Farahidi University, Baghdad , Iraq

5 AL-Nisour University College, Baghdad, Iraq

6 Department of Optical Techniques, Al-Zahrawi University College, Karbala, Iraq

7 Kazan state power engineering university, Kazan, Russia

Abstract

Over the last few decades, the majority of industrialized and developed countries have placed a strong emphasis on reducing the amount of wasted energy. In this study, electrical energy consumption is optimized by monitoring power consumption caused by residents' activities at various times of the day and storing this data in a database. An optimization algorithm was used in this study to smarten up the management of energy consumption in the building based on inhabitants' activities. The Genetic Algorithm (GA) was used to optimize the energy consumption in a smart building compared to a traditional building. Furthermore, the algorithm will enable the creation of a smart building that requires no human intervention by presenting a model based on the energy efficiency management system for the automatic operation of household equipment based on the presence of the resident scenario. The main benefit of implementing smart grid technology in the studied building was the ability to manage and monitor the energy supply and demand process. The results showed that the proposed management system in the smart building consumes less energy and power than conventional buildings. The smart building reduces energy consumption for outlets, lighting, cooling, and heating by 38%, 28%, 34%, and 33%, respectively.

Keywords

Main Subjects

References

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Journal of Operation and Automation in Power Engineering
Volume 11, Special Issue
Sustainable Power Systems, Energy Management, and Global Warming
December 2023
Pages 28-32

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History

  • Receive Date: 27 June 2023
  • Revise Date: 02 August 2023
  • Accept Date: 27 August 2023
  • First Publish Date: 27 August 2023

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