Forecast Engine

Coimbra Solar Forecasting Engine Laboratory

Our goal is to develop the highest-fidelity forecasting engines for variable energy resources, focusing mostly on solar and wind generation, but also on integrated renewable forecasts (load+solar; load+wind). Our engines are applicable to load forecasts, and can be used in a variety of other applications where stochastic learning offers a substantial advantage over deterministic methods. Our research interests cover many different areas, including: Atmospheric Radiation and Cloud Physics; Fluid Mechanics, Heat and Mass Transfer; Pattern Recognition; Stochastic Learning Methods; Fractional and Variable Order Methods; Nonlinear Chaos Dynamics; Optimization and Regression Methods (GA, ANN, kNN, SVM, SVR, ARMA/ARIMA, and ensembles of these methods), and Image Processing. Our goal is to develop solar and wind forecast engines that span the whole spectrum of temporal horizons and spatial resolutions, from intra-minute to multiple days ahead forecasts, and from single point radiometers to continental regions.


Short Bio: Prof. Carlos Coimbra received his Ph.D. in Mechanical and Aerospace Engineering from UC Irvine. Dr. Coimbra joined the faculty of the University of California Merced campus in 2006, and shortly after became the Founding Chairman of the Mechanical Engineering and Applied Mechanics graduate program, a position he held until joining UCSD in July, 2011.  He is the director of the Solar Power Forecasting Initiative, a multi-campus effort that oversees the daily operations of a number of solar resource observatories and test-beds distributed throughout the state. His current research focuses on the development of high fidelity, evolutionary forecasting engines for renewable energy integration, a field of study that lies in the intersection of Artificial Intelligence, Meteorology, Applied Mathematics and Renewable Energy Technologies. His work has been supported by grants from the National Science Foundation, NASA, the California Energy Commission, the Center for Information Technology in the Interest of Society, the American Chemical Society, and several branches of the US Department of Defense, among many others. Coimbra has received a number of prestigious teaching awards throughout his career, including the Chancellor’s Citation for Meritorious Teaching at the University of Hawaii-Manoa, the highest teaching award bestowed by the Manoa campus in recognition of faculty members who have made significant contributions to teaching and student learning. He will teach core graduate and undergraduate courses in Thermodynamics, Heat Transfer and Renewable Resources at UCSD, as well as continue his involvement in K-14 outreach programs and research inclusion for undergraduates.




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                                          SEGS facility in Kramer Junction, CA


HMI/Solar image now from SDO/SOHO (Courtesy NASA/ESA).



                                         LIVE DATA FROM OUR SOLAR OBSERVATORIES






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