Site-specific energy prediction for photovoltaic devices

This thesis presents an energy prediction tool for photovoltaic (PV) modules, based on the measure-correlate-predict principle. The tool allows quantification of the impact of the different environmental factors influencing PV device efficiency for different sites as they deviate from standardised test conditions and combines their effects for energy yield prediction of different module technologies operating in different climates. Amongst these environmental influences, the impact of angle of incidence has been particularly under-researched. In this work, a systematic investigation of the influence of angle of incidence on PV module performance is realised. This is achieved using both short-term module characterisation and long-term energy yield measurement campaigns. A customised purpose built dual axis tracker for mounting paired sets of modules on a fixed south-facing, 45-degree tilted rack is used to investigate the differences in module performance. The quality and quantity of the composition of the incident irradiance is described for various sky conditions at high latitude locations. Furthermore, an understanding of the entangled effects on photocurrent of both the angle of incidence and spectral variation is presented. This is achieved by analysing data from a system developed especially in this work which integrates an instantaneous all-sky mapping of irradiance from a monochromatic CCD camera with precision measurements of small-aperture normal irradiance from a collimated pyranometer in the short-term measurement campaign. The proposed energy prediction tool is validated using long-term datasets from several locations and is compared to other current methods. This was conducted under the European-funded PV-Catapult and IP Performance projects. The tool's prediction uncertainty falls within the ±5% for crystalline and ±10% for thin films, which is the same accuracy as other methods and within the measurement uncertainty of outdoor measurements.