Observation-Based Analog Ensemble Solar Forecast in Coastal California

Historical observations from radiosondes, buoys, and satellite images are used to generate an analog ensemble (AnEn) solar forecast. In coastal California, Stratocumulus (Sc) clouds appear most frequently during late spring and summer months. Sc clouds form at night and begin to dissipate after sunrise, limiting solar energy generation in the morning hours. The AnEn method categorizes cloudy (as either well-mixed or decoupled) and clear events at the forecast initial time and uses several meteorological variables to find the closest analogs. The AnEn forecast is tested at the NKX weather station in San Diego, CA during May to September 2014-2017. The AnEn forecast has a lower root mean square error than a numerical weather prediction model and 24-hour persistence forecasts. The error is lowest for the clear cases and largest for the cloudy decoupled cases. The AnEn forecast is able to capture Sc dissipation for the well-mixed cases in the early morning, but decoupled cases display higher variability throughout the day and are much harder to predict as a result.

I. Introduction

Solar generation can display high variability and an accurate solar forecast enables an improved operation of the electric grid. Despite steady improvements of forecasts from Numerical Weather Prediction (NWP) models, forecast skill is still limited by mean and conditional biases. In coastal California, solar production is often hindered by the formation and dissipation of Stratocumulus (Sc) clouds, which are most prominent in late spring and summer months. The majority of installed rooftop systems are located along the coast, posing a significant challenge. Sc clouds form in a shallow planetary boundary layer (PBL) at night and begin to dissipate after sunrise. Typical PBL height is often less than 1 km. Due to computational constraints, state-of-the-art NWP models have limited vertical resolution and parameterize the physical processes governing Sc clouds instead of directly solving them. This often leads to an erroneous representation of Sc clouds and thus an inaccurate solar forecast. While efforts have been made to improve the physical representation of Sc clouds in NWP models, imperfect initial conditions and numerical and physical approximations still affect the accuracy of the forecast.