Solar Forecasting

Jan Kleissl, University of California, San Diego

Wednesday April 8, 2015, 11:00 a.m. – 12:00 p.m

EBUII, Room 479

ABSTRACT: To effectively manage the growing density of solar power installations, grid operators are increasingly relying on solar forecasts to predict solar power from minutes to days ahead.  Sky imager forecasts are employed for very short time horizons. For forecast horizons of five hours or greater, large-scale computational fluid dynamics models known collectively as numerical weather prediction (NWP) is the most accurate method of predicting solar irradiance.  However,, NWP is consistently erroneous and generally under-represents cloud cover; approximately half of all cloudy days are incorrectly forecast as clear.  Furthermore, these errors are exacerbated for regions with dynamic and localized cloud cover such as the California coast.

To directly improve cloud simulations, a high-resolution NWP specialized for solar irradiance forecasting in coastal areas was developed and implemented operationally.  It was found that simulated MLS clouds dissipated 2 hours earlier than observed and that model error was hypothesized to result from inaccurate initial conditions, physics parameterization issues, and incorrect treatment of the surface energy balance.  To improve model initialization, a method of direct-cloud assimilation was implemented.  In this method, satellite observations of cloud cover were used to populate clouds in the model initial conditions. A mixed layer model was developed to be able to analyze the physical processes that contribute to cloud dissipation, particularly surface heat and moisture fluxes, entrainment of warm and dry air from above, and initial conditions. Cloud dissipation was found to be sensitive to surface moisture only at unrealistically small surface moisture. Developing the mission, science, technology and support for projects of scale is a demanding and multifaceted enterprise. There are many lessons to be learned from the National Ignition Facility (NIF) experience that can be applied in the quest to secure any future large-scale facility.  The presentation will include a historical perspective on the ICF and Stockpile Stewardship program that motivated NIF and the scientific and political strategy that ultimately secured the Facility.

BIO: Jan Kleissl is an Associate Professor in the Department of Mechanical and Aerospace Engineering and serves as co-Director of the Center for Renewable Resources and Integration and Associate Director of the Center for Energy Research at UCSD. Kleissl’s group works solar forecasting with sky imagery and numerical weather prediction, and distribution feeder modeling for solar power integration. He is Editor of the most prestigious journal in the field (Solar Energy) and regarded as the most prolific author in solar forecasting. He has served as PI or Co-PI on $13.5M of solar power integration research over the past five years with funding from DOE, NREL, CEC, CPUC/CSI, and Panasonic/Sanyo. Dr. Kleissl is one of 2 US representatives to the International Energy Agency’s Task 46 Working Grp. on Renewable Energy Forecasting.