The procedures used today for prediction of the solar resource available to photovoltaic (PV) projects uses horizontal irradiance validated with thermopile radiometers. However, plane-of-array (POA) irradiance data is known to correlate more directly with plant performance. The significant increase in uncertainty from transposing global horizontal irradiance (GHI) to POA and not explicitly accounting for spectral or angular response of modules adversely impacts the economic attractiveness of PV projects. In this project, researchers will conduct a complete assessment of needed standards for implementing a PV resource approach and develop new models that show 4% improvement in the transposition uncertainty. The goal is to create an integrated web service that provides a 20-year PV resource dataset on demand.
The work will provide more accurate accounting of the solar resource for the POA by testing different types of irradiance sensors to determine the most consistent and reliable sensor technologies for irradiance. The work will also improve the method of using satellite-derived irradiance data to determine the solar resource through improvement of the transposition models and add in new components such as spectral decomposition used in atmospheric science.
The project aims to reduce the uncertainties in PV performance guarantee assessments by up to 6% with commensurate value to the PV customer and installer and create more accurate satellite based “PV Resource” data when compared to the results from current methods, thereby leading to a reduced price of solar electricity and increasing the expected return on investment of PV projects.