Overview of the Application of Artificial Intelligence in Intelligent Grid Dispatch Optimization

With the global energy transition and the large-scale integration of renewable energy into the grid, the volatility and uncertainty of the power system have increased significantly, making traditional dispatch methods unable to meet these demands. Against this backdrop, artificial intelligence, with its advantages of autonomous learning, rapid iteration, and global optimization, has become a key driver of innovation in smart grid dispatch systems.This article systematically reviews the application of artificial intelligence (AI) in smart grid dispatching, categorizing it into three phases: introduction, growth, and maturity. It also categorizes and organizes research on support vector machines, genetic algorithms, deep learning methods, and multi-agent systems. It then argues that while AI demonstrates significant potential in smart grid dispatching, it still faces numerous challenges. It also points out that future efforts should focus on developing interpretable AI models, strengthening privacy protection, and fostering cross-disciplinary and cross-domain collaboration to promote the large-scale application of AI in smart grid dispatching.In general, artificial intelligence has brought new opportunities for the development of smart grid dispatching and has played a significant role in the realization of new power systems and the "dual carbon" strategic goals.