In order to maintain a balance between the generation and load during
service restoration, it is important to have mathematical models that
can predict the load that will be present at Various locations of the
system. A regression approach supported by voluminous feeder load meas
urement data collected during large-scale rotating interruptions is pr
esented in this paper. Regression models are proposed to estimate the
feeder and substation cold load pickups after scheduled outages.