Kirsten Perry

Kirsten Perry is a Data Science Researcher at the National Renewable Energy Laboratory (NREL), specializing in photovoltaic (PV) system performance analysis through machine learning and remote sensing technologies. At NREL, she contributes to open-source Python packages like PVAnalytics, RdTools, and Panel-Segmentation for automated PV data quality assurance and degradation analysis.

• Education: Master of Science in Computer Science from Georgia Institute of Technology
• Education: Bachelor of Science in Mechanical Engineering and Mathematics from University of Oklahoma

Her research focuses on:

• Machine learning applications for PV performance data
• Solar site analysis via satellite imagery
• Extreme weather impact assessment on PV systems
• Developing open-source PV analytics tools
• Time series data processing for solar installations
• Automated metadata extraction from remote sensing

Her recent publications demonstrate expertise in PV degradation analysis, inverter availability, and extreme climate resilience for solar systems.

Collaborations include work with colleagues across multiple institutions on topics like:

• Solar storm damage assessment
• Performance loss quantification
• Photovoltaic reliability under stress conditions