This invention belongs to the field of power
system optimization and
energy storage operation technology, specifically involving a multi-dimensional collaborative
community-shared
energy storage optimization scheduling method. It includes: establishing a dual-constraint scheduling model for a
community-shared
energy storage system based on relative diversity factors, combining a hard upper limit on total subscriptions with a
soft data-driven threshold based on relative diversity factors, and using the non-overlapping nature of user loads to define the boundary of overlapping demand; constructing a two-layer optimization scheduling architecture of outer-layer price setting and inner-layer capacity allocation, introducing a piecewise linear proxy model to achieve fair capacity allocation with the goal of maximizing the minimum user benefit-cost ratio; and establishing an evaluation method that maps user differences to expected shortage costs. This invention provides a multi-dimensional collaborative
community-shared energy storage optimization scheduling method that integrates user diversity constraints, supply-demand benefit balance, and risk closed-
loop control, filling a gap in existing technology and promoting the large-scale application of shared energy storage in community scenarios.