This invention discloses a
wind power forecast-driven grid
energy management method,
system, and equipment, belonging to the field of
grid optimization and dispatching technology. The method includes: acquiring power forecast distribution sequences and
confidence interval data of wind farms over multiple forecast periods; constructing an uncertain energy evolution
tensor containing temporal gradients, spatial
diffusion, and probabilistic discrete components; mapping this
tensor to the grid node topology to generate a risk seepage topology map; identifying key channels and nodes and constructing a risk seepage channel set; subsequently calculating a partitioned elasticity threshold to generate an elastic risk envelope region; and finally, combining stored grid energy to perform hierarchical
energy regulation and allocation, establishing a grid
energy management strategy. This invention solves the technical problem that the intermittency and uncertainty of
wind power easily lead to energy dispatching risks in distribution circuit systems, achieving accurate
risk identification and
dynamic control within the grid, and combining
grid energy storage to complete differentiated
energy regulation and allocation.