Towards a multi-time-scale integrated solar forecast system
This project integrates Total Sky Imagers (TSI), NOAA geostationary satellites (GOES), and Numerical Weather Prediction (NWP) models into one seamless solar energy forecasting. A large operating solar PV plant in Nevada, U.S. was instrumented to capture the fine-scale temporal and spatial variability of the cloud-light environment. Two TSIs were deployed to collect and process cloud development, movement and sky cover near and around the PV plant for the purpose of forecasting intra-hour solar energy production. GOES visible satellite imagery provides data for short-term forecasts up to 6 hours ahead using a cloud vector advection scheme. Forecasts beyond 6 hours, up to several days ahead, are obtained from NWP models with a full suite of physics parameterization schemes (radiation, cloud microphysics, etc.) and a statistical post-processing algorithm to minimize systematic errors in the NWP forecasts. The multi-time-scale forecast system incorporates an Optimized Ensemble Algorithm (OEA) that constructs a composite deterministic or probabilistic forecast by statistically weighting the forecasts for the component methods by look-ahead time based on historical performance. Preliminary results from hindcasts or "forecasts in hindsight" for the individual components of the integrated forecast system at different time intervals (5 min, 15 min and 30 min) depending on the forecast horizon (0 to 30 min, 30 min to 5 hours, 6 to 48 hours) will be presented. The first phase of the validation process involves an objective evaluation of each individual forecasting method using standard metrics (e.g. normalized RMSE). Particular attention is given to the validation of 1-minute to 1-hour ramps as well as the intra-hour variability. The next phase will focus on the performance of the integrated multi-time-scale forecast system.