Research on distributed energy management system based on artificial intelligence

The reliability and stability of the power system are crucial to social life and economic development as an essential infrastructure of modern society. However, power system failures can lead to serious consequences such as power supply interruptions and equipment damage, making timely and accurate power load forecasting particularly important. Traditional power load forecasting techniques based on rules and statistics have limitations that make it difficult to meet the complex and real-time requirements of the power system. This paper will explore and discuss artificial intelligence-based power load forecasting for the power system, comparing it with traditional methods while focusing on the application of reinforcement learning, big data technology, and abnormal flow identification technology in order to provide new ideas and methods for improving the reliability and stability of the power system.