  This paper presents a regression-based method for estimating voltages and
voltage sensitivities for volt-var control on distribution circuits with
limited data. The estimator uses power flow results for representative load and
PV output scenarios as training data. Using linear regressions on power flow
results, the voltages at critical nodes are calculated online based on power
measurements at the feeder head and at each PV plant. The voltage sensitivity
to changes in reactive power injection by each PV plant is also found online
using regressions on power flow results. The estimator thus provides the
estimated critical voltages and their sensitivities to each possible control
action. The estimator is tested in conjunction with a volt-var optimization on
real, unbalanced rural distribution feeder. The optimal control actions and
voltage results using the estimator are compared to the optimal results
assuming full visibility of the distribution system. Results show that the
estimator can estimate voltages and sensitivities with adequate accuracy for
successful centralized volt-var control.
