Automated Analysis of Renewable Energy Datasets ('EE/RE Data Mining')

Brian Bush, Daniel Inman, Daniel Getman, Ryan Elmore

Research output: NRELPoster


This poster illustrates methods to substantially improve the understanding of renewable energy data sets and the depth and efficiency of their analysis through the application of statistical learning methods ('data mining') in the intelligent processing of these often large and messy information sources. The six examples apply methods for anomaly detection, data cleansing, and pattern mining to time-series data (measurements from metering points in buildings) and spatiotemporal data (renewable energy resource datasets).
Original languageAmerican English
StatePublished - 2013

Publication series

NamePresented at the LDRD FY13 Annual Review and Poster Session, 13 June 2013, Golden, Colorado

NREL Publication Number

  • NREL/PO-6A20-64976


  • data analysis
  • data mining
  • geospatial
  • machine learning
  • statistics


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