The Solar Power Forecasting Initiative
Lowering the Cost and Increasing the Quality of Solar Power Through Research
Mechanical and Aerospace Engineering
UNIVERSITY OF CALIFORNIA, SAN DIEGO
Jacobs School of Engineering | EBU II Room 554
9500 Gilman Drive #0411 | La Jolla, CA 92093-0411
Phone: (858) 534-4285
At the Forecast Engine Laboratory we strive to develop the highest-fidelity forecasting engines for variable energy resources, mainly related to solar and wind generation. Our engines are also applied to load forecasts, and can be used in a variety of applications where stochastic learning offers a substantial advantage over deterministic methods. Our research interests cover many different areas, including: Atmospheric 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/ARIMA, etc), and Image Processing.
Our goal is to develop solar and wind forecasting engines that span the whole spectrum
of temporal and spatial horizons, from intra-minute to multiple days ahead, and from
single point radiometers to multi-acre renewable energy farms all the way to continental regions.