Impact of tropical convective conditions on solar irradiance forecasting based on cloud motion vectors

Abstract

Intra-day forecasts of global horizontal solar irradiance (GHI) are widely produced by displacing existing clouds on a geo-stationary satellite image to their future locations with cloud motion vectors (CMV) derived from preceding images. The CMV estimation methods assume rigid cloud bodies with advective motion, which performs reasonably well in mid-latitudes but can be strained for tropical and sub-tropical climatic zones during prolonged periods of seasonal convection. We study the impact of the South Asian monsoon time convection on the accuracy of CMV based forecasts by analyzing two years of forecasts from three commonly used CMV methods – Block-match, Farnebäck (Optical flow) and TV-L1 (Optical flow). Forecasted Cloud Index (CI) maps of the entire image section are validated against analysis CI maps for the period 2018-2019 for forecast lead times from 0 to 5.5 hours. Site-level GHI forecasts are validated against ground measured data from two BSRN stations – Gurgaon and Tiruvallur, located in hot semi-arid and tropical savanna climatic zones respectively. The inter-seasonal variation of forecast accuracy is prominent and a clear link is found between the increase in convection, represented by a decrease in outgoing longwave radiation (OLR), and the decrease in forecast accuracy. The Gurgaon site shows the highest forecast error in the southwest monsoon period and exhibits a steep rise of forecast error with the increase in convection. The highest forecast error occurs in the northeast monsoon period of December in Tiruvallur. The impact of convection on the number of erroneous time blocks of predicted photovoltaic (PV) production is also studied. Our results provide insights into the contribution of convection to errors in CMV based forecasts and shows that OLR can be used as a feature in future forecasting methods to consider the impact of convection on forecast accuracy.

PV Plant Equipment Labels and Layouts Can Be Validated by Analyzing Cloud Motion in Existing Plant Measurements

“…A variety of methods exist for determining cloud motion vectors (CMVs). Some techniques allow the identification of cloud motion using All Sky Imagers [17], [18], satellite data [19], [20], or numerical weather prediction [13]. Other techniques obtain the CMV by observing spatiotemporal correlations between members of a distributed measurement network [21], [22].…”