In a new weekly update pv magazine, the DNV company Solcast presents the solar radiation power data it has collected from North America since the beginning of May. Nearly 100 wildfires have raged across the province of Alberta since the beginning of the month, and solar plant operators across the affected area can expect reduced efficiency from both radiation effects and increased panel fouling.
Source: Solcast
Almost 100 wildfires raged in the province of Alberta at the beginning of the month consequences and evacuations for over 30,000 residents and several are still burning out of control.
Source: Alberta Wildfire Status Dashboard
Source: Solcast
Smoke affects radiation
Smoke from the fires has blanketed most of western Canada and is pushing it east prevailing winds. Aerosols in the smoke can endanger the health and visibility of the residents of the area In the area, but they also affect solar production: thick aerosol clouds created by biomass burning spread to everyone way to the US Midwest and are clearly visible in the ECMWF CAMS data.
Solar resource operators everywhere in the affected area you can expect a decrease in efficiency from both radiation effects and increased panel fouling.
The radiation force and the cloud together limit the radiation
Solcast ingests aerosol data into its radiation modeling and the effect of fire on the formation of the sun. the smoke is clearly visible in the data processed through the Solcast API Toolkit. The comparison below shows effect of irradiance in Alberta, distinguishing between aerosol losses and cloud losses.
In this comparison, we use May 2022 mean clearsky data as non-aerosol-effected baseline and aerosol-effected clearsky data from May 2023 and the actual Solcast data on May 22 and 23, 2023. Despite the dissipating aerosols On the 23rd, cloud and smoke suppressed the peak radiation on both days.
Solcast produces these numbers through the radiative forcing forecast and weather API by tracking clouds and aerosols to within 1-2 km globally using satellite data and proprietary AI/ML algorithms. This information is used to control the irradiance models, which makes it possible Solcast calculates irradiance with high resolution, typical error less than 2%, and also cloud tracking predictions. This data is used by more than 300 companies that manage more than 150 GW of solar energy worldwide.
