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For active distribution networks (ADNs) integrated with massiveinverter-based energy resources, it is impractical to maintain the accuratemodel and deploy measurements at all nodes due to the large-scale of ADNs.Thus, current models of ADNs are usually involving significant errors or evenunknown. Moreover, ADNs are usually partially observable since only a fewmeasurements are available at pilot nodes or nodes with significant users. Toprovide a practical Volt/Var control (VVC) strategy for such networks, adata-driven VVC method is proposed in this paper. Firstly, the system responsepolicy, approximating the relationship between the control variables and statesof monitoring nodes, is estimated by a recursive regression closed-formsolution. Then, based on real-time measurements and the newly updated systemresponse policy, a VVC strategy with convergence guarantee is realized. Sincethe recursive regression solution is embedded in the control stage, adata-driven closed-loop VVC framework is established. The effectiveness of theproposed method is validated in an unbalanced distribution system consideringnonlinear loads where not only the rapid and self-adaptive voltage regulationis realized but also system-wide optimization is achieved.

Data-driven Inverter-based Volt/VAr Control for Partially Observable Distribution Networks