Maryam Emami Neyestanak : Forecasting of direct solar irradiance using stochastic learning methods, clear sky data and the NWS database

Posted by Tian Tian , part of the Graduate Statistics Seminar.

At

Nov. 2, 2016, 3 p.m.

In

SEO 512

Abstract

As part of Concentrating Solar Power Capital Cost and Expected O&M project, we model the direct solar irradiance using stochastic learning methods, clear sky data and the NWS database. Project partners NREL, Northwestern University, Colorado School of Mines, Argonne National Laboratory, and SolarReserve develop detailed performance and cost models. We use ARMA models with additional predictors from the National Digital Forecast Database (NDFD) of the National Weather Service (NWS), and our approach is motivated in large part by the work of Marquez and Coimbra, although we employ simpler forecasting models than their neural networks.