Prediction and Optimization Analysis of Hydropower Generation Efficiency Based on AHP Algorithm

Within the increasing demand for energy in the world today, new energy has become one of the most important energy sources in the world. Hydropower new energy is a clean and renewable energy. However, many factors, such as water power, meteorology and equipment status, will affect the power generation efficiency of new energy. The historical data of power generation efficiency of the power station are sorted out to ensure the quality of the data. The efficiency of hydropower generation is graded, including water quantity, water level, power generation efficiency and other influencing factors, and each factor is weighted. The weight of each factor is calculated by analytic hierarchy process. This paper compares the power generation and energy consumption of two different types of hydropower stations, and compares the differences in resource utilization between traditional hydropower stations and reconstructed hydropower stations under the same conditions. When the water flow of the traditional hydropower station is 100 cubic meters per second, the power generation is 50,000 kWh, the resource consumption is 1,000,000 cubic meters of water, and the resource utilization rate is 5.0%. After renovation, when the water flow rate of the hydropower station is 100 cubic meters per second, the power generation is 65,000 kWh, the resource consumption is 950,000 cubic meters of water, and the resource utilization rate is 6.8%. Therefore, it is of great significance to carry out the research on the prediction and optimization of hydropower new energy generation efficiency for improving the energy utilization rate and reducing energy consumption in China.