Headshot of Sinnott Murphy.

Sinnott Murphy

Researcher III-Model Engineering


Sinnott Murphy is a research engineer in the Grid Systems Group within the Grid Planning and Analysis Center. His research is at the intersection of statistics, machine learning, and power systems. Sinnott is currently working to improve the laboratory’s treatment of generator failure dynamics to better quantify power system adequacy and resilience risks on planning and operational timescales. At NREL, he has contributed to multiple packages related to probabilistic adequacy assessment in the Julia technical computing language.

Research Interests

Machine learning applications for grid reliability, security, and resilience

Online learning and optimization in distributed energy systems

Probabilistic load and resource forecasting


Ph.D., Engineering & Public Policy, Carnegie Mellon University

M.S., Transportation Technology & Policy, University of California, Davis

M.S., Agricultural & Resource Economics, University of California, Davis

B.S., Biochemistry & Molecular Biology, University of California, Davis

Professional Experience

Contractor, PJM Interconnection (2017-2019)

Contractor, North American Electric Reliability Corporation (2015-2016)

Researcher, Institute of the Environment and Sustainability, University of California, Los Angeles (2012-2014)

Featured Work

"Resource Adequacy Implications of Temperature-Dependent Electric Generator Availability," Applied Energy (2020)

A Time-Dependent Model of Generator Failures and Recoveries Captures Correlated Events and Quantifies Temperature Dependence,” Applied Energy (2019)

"Resource Adequacy Risks to the Bulk Power System in North America," Applied Energy (2018)