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DECEMBER 11, 2019
Web Feature

PNNL to Lead New Grid Modernization Projects

PNNL will lead three new grid modernization projects funded by the Department of Energy. The projects focus on scalability and usability, networked microgrids, and machine learning for a more resilient, flexible and secure power grid.
FEBRUARY 5, 2019
Web Feature

Symposium explores smart city evolution

In November, Northeastern University Seattle (NU-Seattle) hosted "Smart Cities: Critical Infrastructure Protection" to explore technology and policy opportunities and challenges facing the smart city evolution.
JANUARY 8, 2016
News Release

How Seashells Get Their Strength

Calcium carbonate found in chalk, shells and rocks is one of the most important materials on earth. New insights on how it turns into hard, strong materials will help scientists design materials needed for a low-carbon future.

Improving Solar Forecasting

The development of an enhanced version of WRF-Solar

By improving the Weather Research and Forecasting (WRF)-Solar model, this project aims to reduce forecast errors of Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) by 25%, yield better forecasts of irradiance ramps, improve estimates of sub-grid scale variability, and more accurately estimate forecast uncertainty. This enables solar power system operators to know how much solar power will be generated over the coming hours and days, ensuring economic and reliable delivery of renewable energy to American households and businesses.

Solar panels and open sky

Utilities, grid operators, solar power plant owners, and other stakeholders would like to better forecast when, where, and how much solar power will be produced at the desired locations in the United States.

Photo by American Public Power Association on Unsplash

This new system builds on the first version of the WRF-Solar model developed by the National Center for Atmospheric Research (NCAR).

Workflow diagram of WRF-Solar project aims
New model development in the WRF-Solar project aims to improve the representation of boundary-layer clouds, fine scale variability, cloud microphysics, and absorbing particles in WRF-Solar.

Anticipated improvements in Version 2 include the following:

  • New representation of boundary-layer clouds (both shallow cumuli and the breakup of stratocumulus) including the impact of entrainment
  • Improved treatment of cloud microphysics, and impacts of aerosol (including absorbing aerosol)
  • New parameterizations to account for the sub-grid temporal variability of solar irradiance during periods with broken clouds
  • Detailed analysis to better quantify model uncertainty and improved calibration of WRF-Solar v2 using Uncertainty Quantification (UQ) techniques