Guest Editor(s)
Assoc. Prof. Muhammad Mokhzaini Azizan
Email: mokhzainiazizan@usim.edu.my
Affiliation: Department of Engineering, Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia, MALAYSIA
Homepage:
Research Interests: power, renewable energy, applications of AI
Dr. Zaidoon Waleed Jawal AL-Shammari
Email: dr.zaidoon.waleed@gmail.com
Affiliation: Electronic Department, Babylon Technical Institute, Al-Furat Al-Awsat Technical University, Babil, Iraq
Homepage:
Research Interests: renewable energy, hybrid system, smart grid, artificial intelligence
Prof. Dr. Sudhanshu Maurya
Email: sudhanshumaurya.set@mriu.edu.in
Affiliation: Department of Computer Science and Engineering, School of Engineering and Technology, Manav Rachna International Institute of Research and Studies (Deemed University), Faridabad, India
Homepage:
Research Interests: artificial intelligence, security, internet of everything, cloud computing
Summary
Next Generation Smart Energy Engineering: Advancements on Digital Twins, Artificial Intelligence and Sustainable Energy Systems explores emerging technologies driving the digital transformation of modern energy systems. It highlights the integration of digital twins, artificial intelligence, IoT, and data analytics to enhance renewable energy integration, smart grids, energy storage, and intelligent energy management. The publication addresses innovations that improve system efficiency, reliability, resilience, and sustainability while supporting decarbonization and the global energy transition. Combining theoretical advances with practical applications, it provides valuable insights for researchers, engineers, industry practitioners, and policymakers shaping the future of sustainable and intelligent energy infrastructures.
This Special Issue aims seek advance knowledge on smart energy engineering through digital twins, artificial intelligence, and sustainable technologies for resilient, intelligent energy systems.
We invite high quality, impactful contributions addressing the following areas:
· Digital Twin Technologies for Smart Energy Systems
· Artificial Intelligence and Machine Learning in Energy Engineering
· Intelligent Renewable Energy Integration
· Smart Grids and Future Energy Networks
· Predictive Analytics and Data Driven Energy Management
· Sustainable Energy Systems and Energy Transition Strategies
· Emerging Technologies for Next-Generation Smart Energy Engineering
Keywords
artificial intelligence, digital twin technology, energy digitalization, energy transition, machine learning for energy, predictive analytics, renewable energy integration, smart energy systems, sustainable energy engineering
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