An evaluation of models and prediction tools for distributed wind turbines has unearthed data that can help potential users make the most informed decisions on upfront investments.

Better representing electric capacity markets, economic retirements, and power-plant age structure provides a more robust understanding of the future evolution of the electric sector.

PNNL wind energy experts have published the Distributed Wind Market Report: 2022 Edition, supplying key findings that can help businesses, communities, and homeowners make informed decisions.

MSD-LIVE, a cloud-based data and code management system, will be released in summer 2022 for hundreds of scientists.

An improved model captures the interactions between the U.S. economy, energy, water, and land systems with increased spatial and temporal detail.

A climate change study co-authored by PNNL scientist Hailong Wang inspired an artist to create an exhibit based on the research.

PNNL contributes to 30 years of data on clouds, radiation, and other climate-making factors as part of field campaigns and analysis conducted by DOE's Atmospheric Radiation Measurement user facility.

New work developed a methodology to generate building temperature setpoint schedules for use by modelers in large-scale building energy simulations.

Storage Targets and Release Function Inference Tool uses data to infer the operating policies of large reservoirs on a national scale.

A multisectoral analysis that combines land use data with hydrological simulations reveals wide disparities in potential source water contamination.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

Using a novel settlement-related dataset produced more accurate population downscaling than using other, more traditional datasets.

Despite an increase in future electricity demands, virtual water trading in the U.S. electricity sector is expected to decline as renewable energy expands.