@inproceedings{asiamah_classifying_2025,
author={Asiamah, Richard and Talkington, Samuel and Boateng, Michael and Vanin, Marta and Geth, Frederik and Molzahn, Daniel K.},
booktitle={6th IEEE Kansas Power and Energy Conference (KPEC)},
title={{Classifying Reactive Power Control Laws of Behind-the-Meter Solar Photovoltaic Inverters}},
year={2025},
volume={},
number={},
pages={1-6},
doi={10.1109/KPEC65465.2025.11045009}
}
Various types of reactive power control laws are heterogeneously used for inverter-based resources (IBRs) in distribution grids. As a result, grid operators may not be aware of which type of control law is used by a particular IBR. Different control laws imply different voltage support behaviors, which need to be known for the development of accurate computational models for power system analysis. To help mitigate this challenge, this paper develops simple classification algorithms to identify which type of control law governs the reactive power output of a behind-the-meter solar photovoltaic inverter when the specific control law selected by the IBR owner is unknown. Notably, the two algorithms introduced only require aggregated smart meter measurements to assign candidate reactive power control laws (e.g., constant power factor, volt-var control) to distribution network inverters. We present a case study to assess their accuracy in performing the classification task.
Admittance Matrix Concentration Inequalities for Understanding Uncertain Power Networks
Samuel Talkington, Cameron Khanpour, Rahul K. Gupta, Sergio A. Dorado-Rojas, Daniel Turizo, Hyeongon Park, Dmitrii M. Ostrovskii, and Daniel K. Molzahn