Research Output per Year
Research Output per Year
Overview
Personal Profile
Kirsten Perry’s research interests include applying machine learning and deep learning techniques to assess photovoltaic (PV) field performance data and remote sensing imagery. She is a contributor to multiple open-source Python packages, including PVAnalytics (automated QA of PV time series data), RdTools (PV degradation analysis), and Panel-Segmentation (automated metadata assessment of solar sites via satellite imagery).
Education/Academic Qualification
Master, Computer Science, Georgia Institute of Technology
Bachelor, Mechanical Engineering and Math, University of Oklahoma
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Collaborations and Top Research Areas From the Past 5 Years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Availability and Performance Loss Factors for U.S. PV Fleet Systems
Deline, C., Muller, M., White, R., Perry, K., Springer, M., Deceglie, M. & Jordan, D., 2024, 33 p.Research output: NREL › Technical Report
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PV Inverter Availability from the U.S. PV Fleet
Deline, C., Springer, M., Perry, K., White, R., Anderson, K. & Tse, I., 2024, National Renewable Energy Laboratory (NREL).Research output: NREL › Poster
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PV Reliability and Resilience in Challenging Climates
Jordan, D., Perry, K., Nguyen, Q., White, R. & Deline, C., 2024, 37 p.Research output: NREL › Presentation
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PV System Availability from Commercial and Utility-Scale Systems
Deline, C., Jordan, D., Perry, K., Deceglie, M., White, R. & Anderson, K., 2024, 20 p.Research output: NREL › Presentation
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Quantifying Error in Photovoltaic Installation Metadata: Preprint
Perry, K., Nguyen, Q. & White, R., 2024. 9 p.Research output: Contribution to conference › Paper