Abstract: The intelligent scheduling decision support system has important technical significance for distribution network scheduling. This study designed and implemented an intelligent scheduling decision support system based on the "cloud edge end" collaborative architecture to improve the reliability and efficiency of distribution network scheduling in a certain region of Zhejiang Province. The system integrates big data, cloud computing, and artificial intelligence technologies. After the implementation of the system, the accuracy of load forecasting reached within 2.5%, the fault location time was shortened to 2 minutes, the load fluctuation was reduced by 15%, and the energy consumption was reduced by 12%.