@ARTICLE{talkington_disaggregation_2022,
author={Talkington, Samuel and Grijalva, Santiago and Reno, Matthew J. and Azzolini, Joseph A.},
journal={IEEE Transactions on Power Systems},
title={{Solar PV Inverter Reactive Power Disaggregation and Control Setting Estimation}},
year={2022},
volume={37},
number={6},
pages={4773-4784},
doi={10.1109/TPWRS.2022.3144676}
}The wide variety of inverter control settings for solar photovoltaics (PV) causes the accurate knowledge of these settings to be difficult to obtain in practice. This paper addresses the problem of determining inverter reactive power control settings from net load advanced metering infrastructure (AMI) data. The estimation is first cast as fitting parameterized control curves. We argue for an intuitive and practical approach to preprocess the AMI data, which exposes the setting to be extracted. We then develop a more general approach with a data-driven reactive power disaggregation algorithm, reframing the problem as a maximum likelihood estimation for the native load reactive power. These methods form the first approach for reconstructing reactive power control settings of solar PV inverters from net load data. The constrained curve fitting algorithm is tested on 701 loads with behind-the-meter (BTM) PV systems with identical control settings. The settings are accurately reconstructed with mean absolute percentage errors between 0.425% and 2.870%. The disaggregation-based approach is then tested on 451 loads with variable BTM PV control settings. Different configurations of this algorithm reconstruct the PV inverter reactive power timeseries with root mean squared errors between 0.173 and 0.198 kVAR.
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) / arXiv / 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
Samuel Talkington, Rahul Gupta, Richard Asiamah, Paprapee Buason, and Daniel K. Molzahn
IEEE CDC 2024 / arXiv / slides / bibTeX
A data-driven sensor placement approach for detecting voltage violations in distribution systems
Paprapee Buason, Sidhant Misra, Samuel Talkington, and Daniel K. Molzahn
Electric Power Systems Research / arXiv / bibTeX
A measurement-based approach to voltage-constrained hosting capacity analysis with controllable reactive power behind-the-meter
Samuel Talkington, Santiago Grijalva, Matthew J. Reno, Joseph A. Azzolini, David Pinney
Electric Power Systems Research / bibTeX
Phase Retrieval via Model-Free Power Flow Jacobian Recovery
Samuel Talkington, Santiago Grijalva
ACM e-Energy / slides / bibTeX
Conditions for Estimation of Sensitivities of Voltage Magnitudes to Complex Power Injections
Samuel Talkington, Daniel Turizo, Santiago Grijalva, Jorge Fernandez, Daniel K. Molzahn
IEEE Transactions on Power Systems / arXiv / bibTeX
Calculating PV Hosting Capacity in Low-Voltage Secondary Networks Using Only Smart Meter Data
Joseph A. Azzolini, Matthew J. Reno, Jubair Yusuf, Samuel Talkington, Santiago Grijalva
IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) / bibTeX
Improving Behind-the-Meter PV Impact Studies with Data-Driven Modeling and Analysis
Joseph A. Azzolini, Samuel Talkington, Matthew J. Reno, Santiago Grijalva, Logan Blakely, David Pinney
IEEE 49th Photovoltaics Specialists Conference (PVSC) / bibTeX
Solar PV Inverter Reactive Power Disaggregation and Control Setting Estimation
Samuel Talkington, Santiago Grijalva, Matthew J. Reno, Joseph A. Azzolini
IEEE Transactions on Power Systems / bibTeX
Recovering Power Factor Control Settings of Solar PV Inverters from Net Load Data
Samuel Talkington, Santiago Grijalva, Matthew J. Reno, Joseph A. Azzolini
North American Power Symposium (NAPS) / slides / 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