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Logan Blakely
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Year
Spectral clustering for customer phase identification using AMI voltage timeseries
L Blakely, MJ Reno, W Feng
2019 IEEE Power and Energy Conference at Illinois (PECI), 1-7, 2019
602019
A deep neural network approach for behind-the-meter residential PV size, tilt and azimuth estimation
K Mason, MJ Reno, L Blakely, S Vejdan, S Grijalva
Solar Energy 196, 260-269, 2020
592020
Perspectives on the integration between first-principles and data-driven modeling
W Bradley, J Kim, Z Kilwein, L Blakely, M Eydenberg, J Jalvin, C Laird, ...
Computers & Chemical Engineering 166, 107898, 2022
412022
Identifying common errors in distribution system models
L Blakely, MJ Reno, J Peppanen
2019 IEEE 46th Photovoltaic Specialists Conference (PVSC), 3132-3139, 2019
342019
Assessment of measurement-based phase identification methods
F Therrien, L Blakely, MJ Reno
IEEE Open Access Journal of Power and Energy 8, 128-137, 2021
282021
Phase identification using co‐association matrix ensemble clustering
L Blakely, MJ Reno
IET Smart Grid 3 (4), 490-499, 2020
282020
AMI data quality and collection method considerations for improving the accuracy of distribution models
L Blakely, MJ Reno, K Ashok
2019 IEEE 46th Photovoltaic Specialists Conference (PVSC), 2045-2052, 2019
282019
930 berg, Jordan Jalvin, Carl Laird, and Fani Boukouvala
W Bradley, J Kim, Z Kilwein, L Blakely, M Eyden
Perspectives on the integration between first-principles and data-driven …, 2022
262022
Systematic study of data requirements and AMI capabilities for smart meter analytics
K Ashok, MJ Reno, L Blakely, D Divan
2019 IEEE 7th International Conference on Smart Energy Grid Engineering …, 2019
222019
Identifying errors in service transformer connections
L Blakely, MJ Reno
2020 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2020
142020
Identification and correction of errors in pairing AMI meters and transformers
L Blakely, MJ Reno
2021 IEEE Power and Energy Conference at Illinois (PECI), 1-8, 2021
132021
Estimation of pv location in distribution systems based on voltage sensitivities
S Grijalva, AU Khan, JS Mbeleg, C Gomez-Peces, MJ Reno, L Blakely
2020 52nd North American Power Symposium (NAPS), 1-6, 2021
122021
Decision tree ensemble machine learning for rapid QSTS simulations
L Blakely, MJ Reno, RJ Broderick
2018 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2018
122018
Machine learning for rapid qsts simulations using neural networks
MJ Reno, RJ Broderick, L Blakely
2017 IEEE 44th Photovoltaic Specialist Conference (PVSC), 1573-1578, 2017
122017
Improving Behind-the-Meter PV Impact Studies with Data-Driven Modeling and Analysis.
JA Azzolini, S Talkington, M Reno, S Grijalva, L Blakely, D Pinney, ...
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022
92022
Imofi-intelligent model fidelity: Physics-based data-driven grid modeling to accelerate accurate pv integration final report
M Reno, L Blakely, RD Trevizan, B Pena, M Lave, J Azzolini, J Yusuf, ...
United States, 2022
72022
Estimation of PV location based on voltage sensitivities in distribution systems with discrete voltage regulation equipment
C Gómez-Peces, S Grijalva, MJ Reno, L Blakely
2021 IEEE Madrid PowerTech, 1-6, 2021
72021
Parameter tuning analysis for phase identification algorithms in distribution system model calibration
BD Pena, L Blakely, MJ Reno
2021 IEEE Kansas Power and Energy Conference (KPEC), 1-6, 2021
52021
Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV
RJ Broderick, MJ Reno, MS Lave, JA Azzolini, L Blakely, J Galtieri, ...
Sandia National Lab.(SNL-CA), Livermore, CA (United States); Sandia National …, 2021
52021
Ac-optimal power flow solutions with security constraints from deep neural network models
Z Kilwein, F Boukouvala, C Laird, A Castillo, L Blakely, M Eydenberg, ...
Computer Aided Chemical Engineering 50, 919-925, 2021
52021
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Articles 1–20