Research on Investment Estimation of Pumped Storage Power Station Based on GA-BP Neural Network

Aiming at the problems of insufficient data and information in the preliminary planning and site selection stage of pumped storage power stations, and the technical and economic difficulties of multiple schemes, through the analysis on a large number of historical data, various factors affecting the site selection of pumped storage power projects are comprehensively considered. With the total project investment and optimal unit power cost as the selection criterion, the BP neural network model and the modified genetic algorithm are established for the investment prediction of the site selection of pumped storage power stations in the early stage. It is helpful to provide a basis to improve the benefits of pumped storage power station construction.