A direct methodology for intra-day forecasts (1–6 h ahead) of power output (PO) from photovoltaic (PV) solar plants is proposed. The forecasting methodology uses publicly available images from geosynchronous satellites to predict PO directly without resorting to intermediate irradiance (resource) forecasting. Forecasts are evaluated using four years (January 2012–December 2015) of hourly PO data from 2 nontracking, 1 MWp PV plants in California. For both sites, the proposed methodology achieves forecasting skills ranging from 24% to 69% relative to reference persistence model results, with root-mean-square error (RMSE) values ranging from 90 to 136 kW across the studied horizons. Additionally, we consider the performance of the proposed methodology when applied to imagery from the next generation of geosynchronous satellites, e.g., Himawari-8 and geostationary operational environmental satellite (GOES-R).
Direct Power Output Forecasts From Remote Sensing Image Processing
Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received June 5, 2017; final manuscript received December 14, 2017; published online February 20, 2018. Assoc. Editor: Geoffrey T. Klise.
Larson, D. P., and Coimbra, C. F. M. (February 20, 2018). "Direct Power Output Forecasts From Remote Sensing Image Processing." ASME. J. Sol. Energy Eng. April 2018; 140(2): 021011. https://doi.org/10.1115/1.4038983
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