Comparison of solar irradiance smoothing using a 45-sensor network and the wavelet variability model

With increasing penetrations of solar photovoltaic (PV) power in the electricity grid, the variability of the irradiance, and therefore power, is important to understand because variable resources can challenge grid operations. Predicting PV variability using one irradiance sensor, as is commonly done, does not account for the smoothing of irradiance over the extent of the power plant. This smoothing is examined using two methods: averaging measurements from many irradiance sensors, and using a model developed by Lave, Kleissl, and Stein [1] called the Wavelet Variability Model. The results show the similarities and differences between two irradiance smoothing models. These two models both show that the smoothing effect is significant for large PV power plants, which means the power plant output has less variability and is easier to integrate into the electricity grid than might have been expected using a single point sensor measurement to predict variability.