Dynamic PV Hosting Capacity Enhancement of Distribution System Under High Uncertainties Using Volt Var Control

Abstract

The increasing demand for power generation and decarbonization goals has involved the advancement and rapid growth in photovoltaic (PV) integration. Despite many advantages, excessive integration of large-scale PV into electrical networks can cause a variety of problems. Accounting for the uncertainty and variability of load demand and PV generation is essential for reliable planning and operation of PV-rich distribution systems. This paper presents a probabilistic, dynamic hosting capacity (HC) evaluation and enhancement framework that explicitly accounts for uncertainties in PV generation and load demand. Day-ahead uncertainty is modelled using machine-learning–based quantile forecasting, and realistic time-coupled variability is propagated through scenario generation via a calibration-based residual bootstrap, producing multiple joint 24-hour PV–load trajectories. These scenarios are simulated on IEEE 33-bus distribution system to compute dynamic HC considering operational constraints, and a probabilistic acceptance criterion is used to obtain a robust HC profile. To enhance HC, smart-inverter Volt/Var control is integrated at PV buses based on local voltage measurements, providing local reactive power support subject to inverter capability limits. Results demonstrate that Volt/Var control enhances robust dynamic HC compared with the baseline case, highlighting the effectiveness of Volt/Var control for hosting capacity enhancement of distribution system under high uncertainties.