FEBRUARY 15, 2024 Report Procurement Options for Low Temperature Geothermal Technologies at Federal Facilities ( Read More )
NOVEMBER 8, 2023 Journal Article Availability of State-Level Climate Change Projection Resources for use in Site-Level Risk Assessment ( Read More )
NOVEMBER 7, 2023 Journal Article A Self-Sustained CPS Design for Reliable Wildfire Monitoring ( Read More )
SEPTEMBER 23, 2023 Report Design and Development of a High Fidelity Cyber-Physical Testbed ( Read More )
SEPTEMBER 16, 2023 Conference Paper Disturbance Propagation Stability in Droop-Controlled Microgrids ( Read More )
SEPTEMBER 13, 2023 Report San Ildefonso Day School Indoor Environmental Assessment: FEMP Healthy Buildings Program ( Read More )
SEPTEMBER 13, 2023 Conference Paper Incorporating climate change into risk-informed resilience planning ( Read More )
AUGUST 13, 2023 Journal Article Projection of future fire emissions over the contiguous US using explainable artificial intelligence and CMIP6 models ( Read More )
AUGUST 13, 2023 Journal Article Extension of large fire emissions from summer to autumn and its drivers in the western US ( Read More )
AUGUST 1, 2023 Conference Paper Large-Scale Simulation of Regional Demand Flexibility Implementation and Customer Economic Impact ( Read More )
JULY 11, 2023 Journal Article Multi-Level Optimization with the Koopman Operator for Data-Driven, Domain-Aware, and Dynamic System Security ( Read More )
JULY 11, 2023 Journal Article Analyzing At-Scale Distribution Grid Response to Extreme Temperatures ( Read More )
JULY 11, 2023 Journal Article Distributed Ledger Technology for Fault Tolerant Distribution Grid Operations ( Read More )
JUNE 29, 2023 Report Valuing Demand Flexibility During a Grid Disturbance: A Granular Approach to Resilience Valuation ( Read More )
JUNE 23, 2023 Conference Paper Hydropower Potential at Non-Powered Dams: A Multi-Criteria Decision Analysis Tool based on Grid, Community, Industry, and Environmental Impacts ( Read More )
JUNE 23, 2023 Conference Paper Leveraging High-Fidelity Datasets for Machine Learning-based Anomaly Detection in Smart Grids ( Read More )