Galen Maclaurin is the group manager of the Geospatial Data Science Group in the Strategic Energy Analysis Center.

His research focuses on techno-economic assessment and potential generation capacity of renewable energy technologies at national and continental scales. He leads a geospatial modeling team that develops scalable, innovative methods for understanding the barriers and opportunities for deployment of utility-scale solar and wind plants from a cost-performance perspective.

Research Interests

Geospatial examination of land use, ecological, and social acceptance considerations for renewable energy deployment

Uncertainty in meso-scale renewable energy resource data

Opportunities for deployment driven by technology innovation and cost reductions

Interplay between policy, land ownership, and energy markets in the viability of wind, solar, and transmission projects

Wind and solar resource assessment

System performance and financial modeling

Predictive modeling and remote-sensing image analysis

Scientific programming and high-performance computing

Education

Ph.D., Geography, University of Colorado Boulder

M.S., Geography, University of Colorado Boulder

B.A., Geography and Spanish, University of Colorado

Professional Experience

Group Manager, NREL (2015–Present)

Lecturer and Graduate Faculty, University of Colorado Denver (2016–2018)

Research Assistant, National Center for Atmospheric Research (2013–2015)

Graduate Instructor and Research Assistant, University of Colorado Boulder (2008–2010)

Featured Work

National-Scale Impacts on Wind Energy Production Under Curtailment Scenarios to Reduce Bat Fatalities, Wind Energy (2022)

Spatially-Explicit Prediction of Capacity Density Advances Geographic Characterization of Wind Power Technical Potential, Energies (2021)

A Physical Downscaling Algorithm for the Generation of High-Resolution Spatiotemporal Solar Irradiance Data, Solar Energy (2021)

Land Use and Turbine Technology Influences on Wind Potential in the United States, Energy (2021)

U.S. East Coast Synthetic Aperture Radar Wind Atlas for Offshore Wind Energy, Wind Energy Science (2020)

The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling, NREL Technical Report (2019)

Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States, IEEE International Conference on Probabilistic Methods Applied to Power Systems (2018)

The National Solar Radiation Data Base (NSRDB), Renewable and Sustainable Energy Reviews (2018)

Reverse Engineering of Land Cover Data: Machine Learning for Data Replication in the Spatial and Temporal Domains, Trends in Spatial Analysis and Modelling (2017)

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB, NREL Technical Report (2016)

Temporal Replication of the National Land Cover Database Using Active Machine Learning, GIScience and Remote Sensing (2016)

Transportation of Large Wind Components: A Review of Existing Geospatial Data, NREL Technical Report (2016)

Extending the Geographic Extent of Existing Land Cover Data Using Active Machine Learning and Covariate Shift Corrective Sampling, International Journal of Remote Sensing (2016)

Understanding the Combined Impacts of Aggregation and Spatial Non-Stationarity: The Case of Migration-Environment Associations in Rural South Africa, Transactions in GIS (2015)