This invention discloses a boundary condition
trend prediction method, device, and non-volatile storage medium. The method includes: acquiring historical
penetration rate, historical
power consumption data, and historical driving data in a target area; based on the historical
penetration rate, using a composite prediction model to predict the future
penetration rate of electric vehicles corresponding to multiple market types, obtaining penetration rate prediction results; based on the historical
power consumption data, historical driving data, and penetration rate prediction results, using an
exponential decay convergence model and a weighted regression model to predict
energy consumption prediction results; based on the penetration rate prediction results and
energy consumption prediction results, predicting the boundary condition parameters of charging facilities corresponding to multiple scenarios; and based on the boundary condition parameters of charging facilities corresponding to multiple scenarios, determining the boundary condition trend sequence. This invention solves the technical problems of single-dimensional prediction of key boundary conditions for electric vehicles participating
in vehicle-to-grid interaction, insufficient
scenario segmentation, and lack of dynamic evolution mechanisms.