Regular Article

Modeling techno-economic multi-objectives of smart homes considering energy optimization and demand management

¹ Department of MIS, Dhofar University, Salalah, Oman
² Biomedical Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, Hillah 51001, Babil, Iraq
³ Erbil Polytechnic University, Erbil Technical Engineering College, Information System Engineering Department, Erbil, Iraq
⁴ Department of Mathematics and Information Technologies, Tashkent State Pedagogical University, Bunyodkor Avenue, 27, Tashkent 100070, Uzbekistan
⁵ Department of Chemistry and Biochemistry, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India
⁶ Symbiosis Institute of Business Management (SIBM), Symbiosis International (Deemed University) (SIU), Kothur Mandal, Mamidipally, Mahabubnagar, Hyderabad, Telangana, India
⁷ Chandigarh Pharmacy College, Chandigarh Group of Colleges, Jhanjeri, Mohali 140307, Punjab, India
⁸ Department of Medicine, National Institute of Medical Sciences, NIMS University Rajasthan, Jaipur, India
⁹ Technical College, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq
⁹ Mechanical Engineering, Faculty of Engineering, South Valley University, Egypt
¹⁰ Department of Electrical Engineering, Islamic Azad University, Branch of Central Tehran, Tehran, Iran

^* Corresponding author: mahmud.en.ac@gmail.com

Received: 30 April 2024
Accepted: 18 July 2024

Abstract

The research suggests an approach that prioritizes customer needs and aims to reduce energy expenses while safeguarding customer privacy. Furthermore, it is recommended that smart homes incorporate a home energy management system to optimize appliance energy consumption. Conversely, the introduction of demand-side management addresses the energy management challenges faced by smart households. The main goal of this approach is to decrease energy usage and electricity costs for customers. Moreover, it enhances user satisfaction while waiting at common intervals. The primary emphasis of this study is on a smart residence furnished with energy management technology and smart home gadgets capable of supplying electricity to the grid. These objectives are considered distinct aspects in the multi-objective optimization issue stemming from this approach. The study utilizes the grasshopper optimization algorithm (GOA) to optimize battery and home appliance scheduling in smart homes with flexible devices. The goal is to reduce the overall cost of microgrid systems through demand-side management implementation. This comparison highlights the superiority of the proposed method in optimizing energy consumption and reducing carbon emissions in a variety of scenarios. By achieving lower energy costs and carbon emissions while maintaining a comfortable indoor environment, the proposed method proves to be a highly effective and sustainable solution for energy management in buildings. These simulation results provide strong evidence of the method’s potential to significantly impact energy efficiency and environmental sustainability in real-world applications. Furthermore, the consistent minimization of the discomfort index showcases the method’s ability to prioritize occupant comfort while still achieving significant energy savings and emissions reductions. Overall, the comparison with other algorithms solidifies the effectiveness and practicality of the proposed method in addressing the complex challenges of energy management and sustainability in smart homes.