Smart Home Powered by New Energy: Energy Management Systems (EMS) Technologies and Future Prospects
DOI:
https://doi.org/10.54097/m24n9691Keywords:
Smart home, energy management systems, renewable energy resources, artificial intelligence.Abstract
The world needs to switch to sustainable energy sources, and smart homes are emerging as a key frontier in this shift. Energy Management Systems (EMS) are essential in this situation for maximizing energy use and guaranteeing effective use of renewable resources in residential settings. Integrating new energy sources with the changing needs of contemporary households is a challenge. This analysis explores cutting-edge EMS systems designed for smart homes, highlighting its potential for utilizing renewable energy sources like solar and wind. Our thorough research shows that combining artificial intelligence with optimization techniques like particle swarm optimization opens up interesting new directions for demand-side management and dynamic energy scheduling. These developments redefine our notion of sustainable household energy management while also improving the efficiency of smart houses. In essence, the combination of EMS with smart home technologies ushers in a new era in domestic energy, paving the way for a more environmentally friendly and economically sensible future.
Downloads
References
Y. Zhu, H. Wen, G. Chu, Y. Hu, X. Li and J. Ma. High-Performance Photovoltaic Constant Power Generation Control with Rapid Maximum Power Point Estimation. IEEE Transactions on Industry Applications, 2021, 57(1): 714-729.
M. Afzal, Q. Huang, W. Amin, K. Umer, A. Raza and M. Naeem. Blockchain Enabled Distributed Demand Side Management in Community Energy System with Smart Homes. IEEE Access, 2020, 8: 37428-37439.
S. Kazmi, N. Javaid, M. J. Mughal, M. Akbar, S. H. Ahmed and N. Alrajeh. Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy. IEEE Access, 2019, 7: 24267-24281.
X. Hou, J. Wang, T. Huang, T. Wang and P. Wang. Smart Home Energy Management Optimization Method Considering Energy Storage and Electric Vehicle. IEEE Access, 2019, 7: 144010-144020.
Khan, A. A.; Minai, A.; Pachauri, R.; Malik, H. Smart home energy management systems: Concept, configurations, and scheduling strategies. Energies 2022, 15: 6249.
Davidović, B. and Labus, A.. A smart home system based on sensor technology. Facta Universitatis, Series: Electronics and Energetics. 2019, 29(3): 451-460.
Yang, C.. Design of Smart Home Control System Based on Wireless Voice Sensor. Advances in Human-Computer Interaction, 2021: 1-10.
Alves, G. H., Guimarães, G. C., & Moura, F. A. M.. Battery storage systems control strategies with intelligent algorithms in microgrids with dynamic pricing. Energies, 2023, 16(14), 5262.
Zunnurain, I., & Rahman, S.. Implementation of Advanced Demand Side Management for Microgrid Incorporating Demand Response and Home Energy Management System. Infrastructures, 2018, 3(4): 50.
M. G. M. Abdolrasol, R. Mohamed, M. A. Hannan, A. Q. Al-Shetwi, M. Mansor and F. Blaabjerg. Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling. IEEE Transactions on Power Electronics, 2021, 36(11): 12151-12157.
Y. Gao, S. Li, Y. Xiao, W. Dong, M. Fairbank and B. Lu. An Iterative Optimization and Learning-Based IoT System for Energy Management of Connected Buildings. IEEE Internet of Things Journal, 2022, 9(21): 21246-21259.
F. Foukalas and A. Tziouvaras. Edge Artificial Intelligence for Industrial Internet of Things Applications: An Industrial Edge Intelligence Solution. IEEE Industrial Electronics Magazine, 2021 15(2): 28-36.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Highlights in Science, Engineering and Technology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
