Key points are not available for this paper at this time.
There are many operational and technical obstacles in the way of the shift to a decentralized, sustainable smart grid. In the face of growing renewable energy integration, distributed resources, and cyber threats, traditional grid management techniques are ill-suited to handle the real-time optimization, predictive analytics, and autonomous control necessary for dependable and efficient electricity delivery. This study thoroughly analyzes how artificial intelligence (AI) approaches can be used to address the main problems that smart grid systems face. The paper looks at how cutting-edge AI techniques, such as multi-agent systems, deep learning, machine learning, and optimization algorithms, can be used in important smart grid applications.
Elkholy et al. (Mon,) studied this question.