Abstract: Ultra-short term forecasting has wide applications in various fields. Accurate prediction of power load in the ultra-short term is of great significance for real-time scheduling and resource allocation in the power sector. Effective power scheduling enhances the consumer experience while avoiding resource wastage. With the increasing diversification of power consumption structure in our country， accurately predicting power load has become a challenging task. This article introduces the application scenarios of ultra-short term power load forecasting， as well as the current difficulties and challenges faced. From a technical perspective， the mainstream methods for ultra-short term power load forecasting are categorized into traditional forecasting methods， intelligent forecasting methods， and combination forecasting methods. Each category is further divided and classified based on implementation approaches. Furthermore， the principles of some representative models within each category are explained. Finally， the advantages and limitations of these three types of methods are compared and summarized. A table is provided to intuitively demonstrate the characteristics of some mentioned models. Reasonable suggestions for future research directions in ultra-short term power load forecasting are also proposed.

Key words:  , ultra-short term forecasting； electric load forecasting； traditional forecasting； ensemble forecasting