The invention relates to the technical field of power
system fault prediction, and discloses a grid division-based power distribution network fault short-term, medium-term and long-term prediction method, which comprises the following steps of: based on a
geographic distribution range of a power distribution network, carrying out region division, extracting a current change value and a
voltage fluctuation value, classifying
power load characteristics and combining meteorological parameters, and obtaining grid multi-dimensional
time sequence characteristic data. According to the invention, by dividing the
geographic area of the distribution
power grid and improving the multi-
source data association analysis capability, the accurate capture of regional fault characteristics is realized, and through the point-by-point comparison detection of current fluctuation and meteorological change in a short time, the fault early warning and
data association mining are strengthened, the
time range is middle, and the
equipment state and environment change rule analysis is enhanced. Through cross-time-scale combination of a meteorological cycle and equipment operation characteristics, abnormal trigger factors are determined, dynamic weighted analysis of a high-
risk area is carried out, grid prediction and
risk assessment are optimized, and the fault early warning capability and the
system reliability guarantee are comprehensively improved.