  For active distribution networks (ADNs) integrated with massive
inverter-based energy resources, it is impractical to maintain the accurate
model and deploy measurements at all nodes due to the large-scale of ADNs.
Thus, current models of ADNs are usually involving significant errors or even
unknown. Moreover, ADNs are usually partially observable since only a few
measurements are available at pilot nodes or nodes with significant users. To
provide a practical Volt/Var control (VVC) strategy for such networks, a
data-driven VVC method is proposed in this paper. Firstly, the system response
policy, approximating the relationship between the control variables and states
of monitoring nodes, is estimated by a recursive regression closed-form
solution. Then, based on real-time measurements and the newly updated system
response policy, a VVC strategy with convergence guarantee is realized. Since
the recursive regression solution is embedded in the control stage, a
data-driven closed-loop VVC framework is established. The effectiveness of the
proposed method is validated in an unbalanced distribution system considering
nonlinear loads where not only the rapid and self-adaptive voltage regulation
is realized but also system-wide optimization is achieved.
