Solar Data Monitoring to Reduce Energy Production Uncertainty

Uncertainty in resource assessment plays a significant role in financing renewable energy projects. For large-scale (> 5 MW) solar projects, a year's worth of on-site measurements are now often required in order to get optimal project financing. Uncertainty in the estimated energy production is influenced by several factors, one of which is measurement uncertainty, which in turn is a reflection of data quality management practices, from the design of the solar monitoring station (SMS) and its maintenance schedule, to the treatment of the data collected. This paper will address the role of data quality and frequent data monitoring in the overall uncertainty framework using data from a subset of the more than 35 monitoring locations being monitored in North America, Hawaii and Puerto Rico. The stations represent a variety of types or designs, including some for which redundant measurements of global horizontal irradiance (GHI) are made with identical instruments, some where a rotating shadowband is used for Direct Normal Irradiance (DNI) and GHI measurements, and some which utilize a pyrheliometer. The majority of these stations have been operating for at least a year. The impact of uncertainty in solar resource will be illustrated using output from PVSyst.

Data monitoring includes comparison with modeled clear sky values for GHI and DNI, inter-comparison among redundant measurements, and examination of time series, and other tests. Ancillary meteorological variables (wind speed and direction, temperature, relative humidity and barometric pressure are also monitored.