A Statistical Model for Hosting Capacity of Distributed Energy Resources Considering Volt/Var Control

초록

The operating conditions of modern power systems are changing. For example, distributed energy resources (DERs) such as photovoltaic (PV) participate in Volt/Var control by controlling reactive power injection. The integration of DERs can increase the uncertainty (e.g., voltage variation) in the grid. Variations of the load, such as heavy, moderate, or light load, can further increase the uncertainty. Depending on the weather conditions and system constraints, the outputs of DERs such as solar PV can vary and might be curtailed. The objective of this study is to determine the most influential factor on the hosting capacity (HC) of DERs given these uncertainties. We used a statistical model combined with the power-flow analysis algorithm (e.g., Newton-Raphson [NR]) and an optimization algorithm based on particle swarm optimization (PSO). To eliminate the uncertainty, this study applies the interval arithmetic method. Using correlation coefficient analysis, this study investigates the impact of key factors such as load condition, conventional fossil fuel generation cost, DER generation cost, and reactive power control capability. In addition to the statistical model with NR and PSO, this study develops a regression model to estimate the system behavior variation as a function of identified key variables. © 2025 IEEE.

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