Guest Editors
Dr. Baseem Khan
Email: baseem.khan04@ieee.org
Affiliation: Center for Research on Microgrids, Huanjiang Laboratory, Zhuji, 311800, China
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Research Interests: renewable energy systems, smart grids, power systems, and the application of optimization and artificial intelligence techniques in energy networks
Dr. Muhammad Zain Yousaf
Email: zain.yousaf@zju.edu.cn
Affiliation: Center for Research on Microgrids, Huanjiang Laboratory, Zhuji, 311800, China
Homepage:
Research Interests: electrical engineering – power system, renewable energy, space microgrid and AI
Summary
The integration of artificial intelligence (AI) and advanced energy modeling techniques has the potential to transform energy systems globally. As the world transitions to renewable energy, the need for innovative approaches to modeling energy production, storage, and consumption becomes critical. This special issue will explore the latest advancements in energy modeling, with a focus on AI-enhanced methods for optimizing the design, operation, and control of energy systems. The use of AI techniques, including machine learning, optimization algorithms, and deep learning, is enabling the development of more efficient, adaptive, and resilient energy models. These models not only improve the predictability of energy systems but also enhance decision-making in real-time operations. Topics of interest include energy storage optimization, hybrid renewable energy systems, microgrid design, and resilience in the face of natural and man-made disruptions. Through this special issue, we aim to bring together cutting-edge research on the application of AI in energy modeling, addressing both theoretical advancements and practical implementation challenges.
Topics of interest include, but are not limited to:
· Advanced AI algorithms for energy optimization and scheduling
· AI-based approaches for microgrid and hybrid energy system modeling
· Energy storage and battery management using AI techniques
· Machine learning models for load forecasting and demand response
· Smart grid design and control using AI-based models
· Resilience of energy systems under multi-hazard scenarios
· AI applications in the design of sustainable and adaptive energy infrastructure
· Real-time data analytics and AI for energy systems monitoring
· Deep learning techniques for predictive modeling in energy systems
· Energy modeling for lunar and deep-space applications (e.g., lunar microgrids)
Keywords
energy modeling, artificial intelligence, machine learning, microgrid, hybrid energy systems, optimization, renewable energy, energy storage, resilience, space microgrids, deep-space power systems
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