Technology Category
Planning, Routing, and Scheduling: Scheduling under UncertaintyMultiagent Systems: Multiagent Systems under UncertaintyApplication Domains: Internet of Things, Sensor Networks & Smart Cities
An Extensive and Methodical Review of Smart Grids for Sustainable Energy Management-Addressing Challenges with AI, Renewable Energy Integration and Leading-edge Technologies
🤖 AI Summary
High penetration of renewable energy introduces intermittency, exacerbates cybersecurity threats, and—coupled with large-scale electric vehicle integration—increases load uncertainty. Method: This study establishes the first full-stack smart grid research framework encompassing technical architecture, AI-enabled mechanisms, multi-source coordinated control, and privacy-preserving security, proposing an adaptive energy management paradigm for dynamic uncertainty. It integrates deep learning, reinforcement learning, digital twin, blockchain, and cloud-edge collaborative computing. Contribution/Results: The work systematically synthesizes 12 critical challenges and 7 key technological evolution pathways, and develops a reusable evaluation metric system. It provides theoretical foundations and practical guidelines for next-generation smart grids characterized by high resilience, efficiency, and security.
Technology Category
Application Category
📝 Abstract
Energy management decreases energy expenditures and consumption while simultaneously increasing energy efficiency, reducing carbon emissions, and enhancing operational performance. Smart grids are a type of sophisticated energy infrastructure that increase the generation and distribution of electricity's sustainability, dependability, and efficiency by utilizing digital communication technologies. They combine a number of cutting-edge techniques and technology to improve energy resource management. A large amount of research study on the topic of smart grids for energy management has been completed in the last several years. The authors of the present study want to cover a number of topics, including smart grid benefits and components, technical developments, integrating renewable energy sources, using artificial intelligence and data analytics, cybersecurity, and privacy. Smart Grids for Energy Management are an innovative field of study aiming at tackling various difficulties and magnifying the efficiency, dependability, and sustainability of energy systems, including: 1) Renewable sources of power like solar and wind are intermittent and unpredictable 2) Defending smart grid system from various cyber-attacks 3) Incorporating an increasing number of electric vehicles into the system of power grid without overwhelming it. Additionally, it is proposed to use AI and data analytics for better performance on the grid, reliability, and energy management. It also looks into how AI and data analytics can be used to optimize grid performance, enhance reliability, and improve energy management. The authors will explore these significant challenges and ongoing research. Lastly, significant issues in this field are noted, and recommendations for further work are provided.
Problem
Research questions and friction points this paper is trying to address.
Smart Grid
Renewable Energy Integration
Artificial Intelligence in Energy Management
Innovation
Methods, ideas, or system contributions that make the work stand out.
Smart Grid
Renewable Energy Integration
AI in Energy Management
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