The characteristics of the runoff hydropower station are to generate power completely according to the natural runoff, and the output and power generation change with the change of the natural flow. The cluster power prediction of the runoff hydropower station is conducive to improving the safety of the power grid operation and improving the utilization rate of hydropower. This paper analyzes the operation characteristics of runoff hydropower stations, summarizes the prediction direction of mainstream runoff hydropower, analyzes the characteristics of the hydrological prediction model represented by the Xin'an River model, and puts forward a study on the power prediction technology of runoff small hydropower cluster based on fusion modeling. Based on the detailed analysis of watershed runoff characteristics, a prediction model based on multi-watershed observation characteristics is proposed, which combines the traditional hydrological model with the LSTM model to form a combined prediction model suitable for runoff hydropower. The method is universal and innovative.

Energy shortage and environmental pollution have become the world's difficult problems, and the development of clean energy has become an inevitable choice. Solving the high proportion of clean energy consumption will become a major issue in the energy field. Various types of energy sources such as hydropower-wind power-photovoltaic power have coupling characteristics in certain geographical areas, and making good use of these coupling properties can better solve its joint prediction problem. This paper first introduces a brief situation of the development of these fields, proposes the main popular computing methods in this field, and conducts targeted analysis for the mainstream methods such as joint prediction, artificial intelligence and clustering algorithm, and finally puts forward the work value and conclusion of multi-energy coupling prediction.