The invention discloses a power distribution network co-jump
risk identification and early warning method based on multi-
source data fusion, and the method comprises the steps: collecting operation data in real time from a plurality of heterogeneous
data source systems of a power distribution network; preprocessing the collected multi-
source data to form a standardized data sequence with a unified time scale; extracting a multi-dimensional feature index based on the standardized data sequence; constructing a same-hop
risk identification model based on
machine learning, fusing the multi-dimensional feature indexes, calculating to obtain a comprehensive same-hop
risk probability value, and delimiting a
risk level according to a numerical value interval; when the
risk level reaches or exceeds a preset intermediate
risk threshold value, load flow calculation and protection
logic simulation are carried out, and a potential
cascading failure development path is predicted; and generating early warning information according to the
risk level and the predicted fault path, and pushing the early warning information to a power distribution network dispatching
system. Through deep combination of multi-
source data fusion and a
machine learning technology, leap-type improvement of the same jump
risk identification and early warning capability of the power distribution network is realized.