Guest Editors
Dr. V B Murali Krishna
Email: muralikrishna.cuk@gmail.com
Affiliation: Department of Electrical Engineering, National Institute of Technology Andhra Pradesh, Tadepalligudem, 534 101, India
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Research Interests: Renewable energy systems, Smart & Micro grids, Electric vehicles, Power and Energy, Electric power generation, Fault analysis, Machine Learning, Optimization, Design and controllers for electrical systems, Artificial intelligence for electrical systems.
Prof. Yu-Chen-Hu
Email: ychu@thu.edu.tw
Affiliation: Tunghai University, Taiwan
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Research Interests: Data compression, image processing, information hiding, information security, computer network, deep learning, and bioinformatics.
Dr. Nallapaneni Manoj Kumar
Email: mnallapan2@cityu.edu.hk
Affiliation: School of Energy and Environment, City University of Hong Kong
Homepage:
Research Interests: Smart grids, power conversion technologies, battery management system, energy forecasting, Techno-economics, life cycle assessment, resilience assessment, blockchain, IoT, and AI.
Summary
In the evolving energy landscape, smart grids play a pivotal role in ensuring the efficient, stable, and sustainable distribution of power, particularly with the growing integration of renewable energy and electric vehicles. However, the variability and unpredictability of renewable sources and loads challenge the grid’s stability and reliability. In response, Artificial Intelligence (AI) and Machine Learning (ML) techniques have emerged as crucial tools to optimize smart grid operations, enhance the grid’s cybersecurity, and improve overall system reliability. This special issue focuses on the role of AI and ML in addressing key challenges associated with smart grids, including dynamic load management, predictive maintenance, fault detection, and renewable energy forecasting. Additionally, the issue will explore how AI and ML can bolster cybersecurity in smart grids, safeguarding the infrastructure from cyber threats that could compromise grid stability. With the increasing digitalization of power systems, smart grids are becoming more vulnerable to cyberattacks, making AI-powered cybersecurity solutions essential for protecting both the operational integrity of the grid and its integrated renewable energy systems. Contributions to this special issue will highlight the latest research and advancements in applying AI and ML techniques to enhance grid reliability, forecast of renewable energy generation, ensure cybersecurity, manage energy storage, and facilitate the seamless integration of electric vehicles. The collection of papers will provide researchers, engineers, and policymakers with a comprehensive understanding of how AI and ML can transform smart grids into more resilient, efficient, and secure systems.
Keywords
Smart and micro grids; renewable energy systems, energy management system, power and energy, cybersecurity, data analysis, image processing, machine learning, artificial intelligence, optimization, electric vehicles
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