Improving Short-Term Wind Power Forecasting through Measurements and Modeling of the Tehachapi Wind Resource Area

Evaluating wind resources in Tehachapi's complex terrain

University of California - Davis


Davis, CA

Recipient Location


Senate District


Assembly District



Amount Spent



Project Status

Project Result

The project team has completed the measuring program that included sodar, ceilometer, radiometer, radar wind profiler, and radio acoustic sounder measurements scattered over six sites and completed a forecast sensitivity study of wind ramping behavior based on suite of physics-based predictive models versus observed sodar data, including obtaining results for a sensitivity study of observed bias of mean absolute error of 0-15 hour energy forecast for Tehachapi wind resource area.

The Issue

Large, rapid changes (ramps) in wind power production are one of the most significant renewable integration issues for balancing authorities. If not effectively managed, these ramps can impose reliability issues and additional costs on the electric system. Accurate forecasting of wind ramps can ameliorate these impacts. However, this remains difficult because of the complexity of the meteorological processes that drive wind ramps. This is particularly challenging in the Tehachapi Wind Resource Area (TWRA) with its large amount of installed capacity, lack of spatial diversity in generation assets, and complex multi-scale wind patterns across the complex terrain.

Project Innovation

This project comprises coordinated atmospheric field measurements and computational modeling improvements to improve the accuracy of prediction of short-term wind ramps (i.e. large, rapid changes in wind power production). The Tehachapi Pass Wind Resource Area is the focus of the project. Since the area features complex terrain and meteorology, the findings can be readily adapted and applied to many other regions.

Project Benefits

Improvements to accuracy of short-term (3-15 hours) and very short-term (0-3 hours) wind ramp forecasting would reduce generating reserves scheduled by grid operators, with corresponding decreases in grid operating costs and greenhouse gas emissions, and, simultaneously, increased grid reliability.

Lower Costs


Reducing wind forecast error by a little as 10% will reduce annual grid integration costs by $28 million in the WECC (which includes California) at 14% wind penetration, and as much as $100 million annually at 24% wind penetration.

Environmental & Public Health

Environmental Sustainability

Developing more accurate wind forecasting will foster greenhouse gas reductions through accurate predictions of available wind energy and reduction of needed generating reserves.

Greater Reliability


This project will foster greater grid reliability by more accurately forecasting short-term wind energy ramps.

Key Project Members

Project Member

C.P. van Dam



Sonoma Technology, Inc.


AWS Truepower, LLC




Atmospheric Systems Corporation


Mano Nanotechnologies, Inc.


Edward Natenberg


Match Partners


Department of Mechanical and Aerospace Engineering - UC Davis


Contact the Team