With the transformation of global energy structure and the rapid development of microgrid technology， microgrid load forecasting and optimization scheduling have become key issues in power system operation and management. Traditional prediction and scheduling methods are often limited by the accuracy and complexity of data， and the development of artificial intelligence technology provides new ways to solve this problem. This article aims to explore the research on artificial intelligence based microgrid load forecasting and optimization scheduling， in order to provide theoretical support and practical guidance for the stable operation and optimization management of the power system.