TY - GEN
T1 - Artificial intelligence in solar energy integration for the smart grid
T2 - 7th International Conference on Image, Video Processing, and Artificial Intelligence, IVPAI 2025
AU - Rahman, Md Nafeez
AU - Islam, Md Maidul
AU - Vavilov, Viacheslav
AU - Singh, Jai Govind
AU - Rahman, Mohammad Mominur
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2025/8/29
Y1 - 2025/8/29
N2 - The integration of solar energy into smart grids is a crucial step toward sustainable energy management. However, challenges such as variability in solar power generation, inefficiencies in energy distribution, and the need for real-time optimization persist. Artificial Intelligence (AI) has emerged as a transformative solution, enhancing forecasting accuracy, optimizing grid operations, and improving demand-side management. To address these challenges, this paper explores AIdriven methodologies, including deep learning techniques, hybrid models, and Internet of Things (IoT) enabled monitoring systems. AI applications in energy storage, predictive maintenance, and decentralized energy trading are discussed. By leveraging AI, smart grids can become more adaptive, resilient, and efficient in managing renewable energy resources. The research article suggests the most potential areas of study in upcoming times based on current progress, future trends in the market, and sustainable growth opportunities.
AB - The integration of solar energy into smart grids is a crucial step toward sustainable energy management. However, challenges such as variability in solar power generation, inefficiencies in energy distribution, and the need for real-time optimization persist. Artificial Intelligence (AI) has emerged as a transformative solution, enhancing forecasting accuracy, optimizing grid operations, and improving demand-side management. To address these challenges, this paper explores AIdriven methodologies, including deep learning techniques, hybrid models, and Internet of Things (IoT) enabled monitoring systems. AI applications in energy storage, predictive maintenance, and decentralized energy trading are discussed. By leveraging AI, smart grids can become more adaptive, resilient, and efficient in managing renewable energy resources. The research article suggests the most potential areas of study in upcoming times based on current progress, future trends in the market, and sustainable growth opportunities.
KW - Artificial intelligence
KW - Energy optimization
KW - Machine learning
KW - Smart grid
KW - Solar energy integration
UR - https://www.scopus.com/pages/publications/105026955769
U2 - 10.1117/12.3074842
DO - 10.1117/12.3074842
M3 - Conference contribution
AN - SCOPUS:105026955769
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Seventh International Conference on Image, Video Processing, and Artificial Intelligence, IVPAI 2025
A2 - Su, Ruidan
PB - SPIE
Y2 - 18 May 2025 through 20 May 2025
ER -