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 usually involve significant errors or even unknown occuranees. 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. First

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.