  Data driven transmission line fault location methods have the potential to
more accurately locate faults by extracting fault information from available
data. However, most of the data driven fault location methods in the literature
are not validated by field data for the following reasons. On one hand, the
available field data during faults are very limited for one specific
transmission line, and using field data for training is close to impossible. On
the other hand, if simulation data are utilized for training, the mismatch
between the simulation system and the practical system will cause fault
location errors. To this end, this paper proposes a physics-informed
data-driven fault location method. The data from a practical fault event are
first analyzed to extract the ranges of system and fault parameters such as
equivalent source impedances, loading conditions, fault inception angles (FIA)
and fault resistances. Afterwards, the simulation system is constructed with
the ranges of parameters, to generate data for training. This procedure merges
the gap between simulation and practical power systems, and at the same time
considers the uncertainty of system and fault parameters in practice. The
proposed data-driven method does not require system parameters, only requires
instantaneous voltage and current measurements at the local terminal, with a
low sampling rate of several kHz and a short fault time window of half a cycle
before and after the fault occurs. Numerical experiments and field data
experiments clearly validate the advantages of the proposed method over
existing data driven methods.
