@inproceedings{asiamah_talkington_boateng_vanin_geth_molzahn_kpec2025,
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.
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Differentiating Through Power Flow Solutions for Admittance and Topology Control
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Optimizing State Estimation Error in the LinDist3Flow Model
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IEEE Opportunity Research Scholars Symposium (ORSS) / bibTeX
Error Bounds for Radial Network Topology Learning from Quantized Measurements
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VArsity: Can Large Language Models Keep Power Engineering Students in Phase?
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57th North American Power Symposium (NAPS 2025) / bibTeX
Covert Distribution Load Tripping Attacks
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57th North American Power Symposium (NAPS 2025) / code / bibTeX
Classifying Reactive Power Control Laws of Behind-the-Meter Solar Photovoltaic Inverters
Richard Asiamah, Samuel Talkington, Michael Boateng, Marta Vanin, Frederik Geth, and Daniel K. Molzahn
Kansas Power and Energy Conference (KPEC) / bibTeX
Strategic Electric Distribution Network Sensing via Spectral Bandits
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IEEE CDC 2024 / arXiv / slides / bibTeX
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2024 IEEE Texas Power and Energy Conference (TPEC) / arXiv / bibTeX
Localized Structure in Secondary Distribution System Voltage Sensitivity Matrices
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ACM e-Energy / arXiv / code / slides / bibTeX
Conditions for Estimation of Sensitivities of Voltage Magnitudes to Complex Power Injections
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IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) / code / bibTeX
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IEEE 49th Photovoltaics Specialists Conference (PVSC) / code / bibTeX
Sparse Time-Series Sampling for Recovery of Behind-the-Meter Inverter Control Models
Samuel Talkington, Santiago Grijalva, and Matthew J. Reno
IEEE PES Innovative Smart Grid Technologies Conference (ISGT) / bibTeX
Solar PV Inverter Reactive Power Disaggregation and Control Setting Estimation
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IEEE Transactions on Power Systems / bibTeX
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North American Power Symposium (NAPS) / slides / bibTeX
Power Factor Estimation of Distributed Energy Resources Using Voltage Magnitude Measurements
Samuel Talkington, Santiago Grijalva, and Matthew J. Reno
Journal of Modern Power Systems and Clean Energy / bibTeX
Rail Transit Regenerative Braking Energy Recovery Optimization to Provide Grid Services
Samuel Talkington, Santiago Grijalva
IEEE Power and Energy Conference at Illinois (PECI) / bibTeX