Recent Developments in Energy Efficiency Technologies for Intelligent Industrial Systems
DOI:
https://doi.org/10.54518/jaei.2.2.2024.1296Keywords:
Artificial Intelligence, Energy Efficiency, Energy Management System, Industrial Applications, Smart IndustryAbstract
Energy efficiency has become a strategic priority in modern industrial systems due to increasing energy demand, environmental concerns, and global sustainability goals. This systematic literature review examines recent studies published over the last fove years to identify technological developments, research trends, industrial applications, implementation challenges, and future opportunities related to energy efficiency technologies. The reviewed literature indicates that advanced technologies, including the Industrial Internet of Things (IIoT), artificial intelligence (AI), machine learning, digital twins, smart sensors, cloud computing, and energy management systems, have significantly improved industrial energy performance through real-time monitoring, predictive maintenance, process optimization, and intelligent decision-making. Furthermore, the integration of renewable energy sources and advanced automation systems contributes to reducing energy consumption, operational costs, and greenhouse gas emissions while enhancing industrial productivity. Despite these advancements, challenges remain regarding high implementation costs, interoperability, cybersecurity, workforce competency, and technology integration. Future research should prioritize intelligent energy management, digital industrial transformation, and sustainable manufacturing practices to achieve higher levels of industrial energy efficiency and environmental sustainability.
References
Blesl, M., & Kessler, A. (2020). Energy efficiency in industry. Springer.
Bogdanov, D., Gulagi, A., Fasihi, M., & Breyer, C. (2021). Full energy sector transition towards 100% renewable energy supply: Integrating power, heat, transport and industry sectors including desalination. Applied Energy, 283, 116273.
Gani, A. (2021). Fossil fuel energy and environmental performance in an extended STIRPAT model. Journal of Cleaner Production, 297, 126526.
He, Y., Liao, N., & Lin, K. (2021). Can China's industrial sector achieve energy conservation and emission reduction goals dominated by energy efficiency enhancement? A multi-objective optimization approach. Energy Policy, 149, 112108.
Jose, R., Panigrahi, S. K., Patil, R. A., Fernando, Y., & Ramakrishna, S. (2020). Artificial intelligence-driven circular economy as a key enabler for sustainable energy management. Materials Circular Economy, 2(1), 8.
Kabeyi, M. J. B., & Olanrewaju, O. A. (2022). Sustainable energy transition for renewable and low carbon grid electricity generation and supply. Frontiers in Energy research, 9, 743114.
Klanjsek, P., Pajnkihar, M., Marcun Varda, N., & Povalej Brzan, P. (2019). Screening and assessment tools for early detection of malnutrition in hospitalised children: a systematic review of validation studies. BMJ open, 9(5), e025444.
Liu, L., Song, W., & Liu, Y. (2023). Leveraging digital capabilities toward a circular economy: Reinforcing sustainable supply chain management with Industry 4.0 technologies. Computers & Industrial Engineering, 178, 109113.
Lăzăroiu, G., Andronie, M., Iatagan, M., Geamănu, M., Ștefănescu, R., & Dijmărescu, I. (2022). Deep learning-assisted smart process planning, robotic wireless sensor networks, and geospatial big data management algorithms in the internet of manufacturing things. ISPRS International Journal of Geo-Information, 11(5), 277.
Lin, B., & Teng, Y. (2023). Digital revolution: Does industrial chain digitalization lead the energy-saving wave?. Sustainable Energy Technologies and Assessments, 60, 103516.
Michaelides, E. E. (2019). Fossil fuel substitution with renewables for electricity generation–effects on sustainability goals. European Journal of Sustainable Development Research, 4(1), em0111.
Martini, B., Bellisario, D., & Coletti, P. (2024). Human-centered and sustainable artificial intelligence in industry 5.0: Challenges and perspectives. Sustainability, 16(13), 5448.
Peng, H., Li, S., Shangguan, L., Fan, Y., & Zhang, H. (2023). Analysis of wind turbine equipment failure and intelligent operation and maintenance research. Sustainability, 15(10), 8333.
Stadnicka, D., Sęp, J., Amadio, R., Mazzei, D., Tyrovolas, M., Stylios, C., ... & Navarro, J. (2022). Industrial needs in the fields of artificial intelligence, internet of things and edge computing. Sensors, 22(12), 4501.
Saeed, S., Altamimi, S. A., Alkayyal, N. A., Alshehri, E., & Alabbad, D. A. (2023). Digital transformation and cybersecurity challenges for businesses resilience: Issues and recommendations. Sensors, 23(15), 6666.
Tao, F., Qi, Q., Wang, L., & Nee, A. Y. C. (2019). Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparison. Engineering, 5(4), 653-661.
Wang, G., Nixon, M., & Boudreaux, M. (2019). Toward cloud-assisted industrial IoT platform for large-scale continuous condition monitoring. Proceedings of the IEEE, 107(6), 1193-1205.
Wang, Y., Kang, X., & Chen, Z. (2022). A survey of digital twin techniques in smart manufacturing and management of energy applications. Green Energy and Intelligent Transportation, 1(2), 100014.
