Case Study: National Renewable Energy Laboratory achieves faster, more accurate solar energy analysis with JMP

National Renewable Energy Laboratory scientists examine nuances of solar energy systems

National Renewable Energy Laboratory scientists needed a way to analyze huge, complex datasets from solar energy systems across different climates and terrains to better understand long-term performance and degradation. They turned to JMP statistical discovery software from SAS to help study photovoltaic reliability and support efforts toward an international compliance standard.

Using JMP, National Renewable Energy Laboratory automated data mining and time-series analysis to filter noise, calculate degradation rates more accurately, and generate quarterly reports much faster. JMP helped cut reporting time from up to two weeks to overnight, and in some cases from a week of manual work to about 10 minutes, while also improving confidence in findings that about 90% of systems performed as expected.

National Renewable Energy Laboratory

Dirk Jordan

Senior Reliability Engineer