In designing any power generation system that incorporates photovoltaics (PV) there is a basic requirement to accurately estimate the output from the proposed PV array under operating conditions. PV modules are given a power rating at standard test conditions(STC) of 1000Wm-2, AM1.5 and a module temperature of 25 °C, but these conditions do not represent what is typically experienced under outdoor operation. It is well known that different PV technologies have different seasonal patterns of behaviour. These differences are due to the variations in spectral response, the different temperature coefficients of voltage and current and, in the case of amorphous silicon (a-Si) modules, the extra effect of photo-degradation and thermal annealing. In this study a novel method has been used to obtain highly accurate energy output data from six different PV modules representing five different technologies: Single crystal silicon (c-Si). Poly-crystalline silicon (p-Si) (2 modules). Triple junction amorphous silicon (3j, a-Si). Copper indium diselenide (CIS). Laser grooved buried contact (LGBC, c-Si) crystalline silicon. This data set includes all the associated meteorological parameters and back-of-module temperatures. The monitoring system allows the simultaneous measurement of six different modules under long-term outdoor operation, which in turn allows a direct comparison of the performance of the modules. Each of the modules has been deployed for at least one year, which provides useful information about the seasonal behaviour of each technology. This data set ultimately provides system designers and consumers with valuable information on the expected output of these different module types in climates like that of Perth, Western Australia. The second part of the study uses the output data collected to assess and compare output predictions made by some currently available photovoltaic performance prediction tools or methods. These range from a generalised approach, as used in the Australian Standards, to the commercially available software packages that employ radiation, thermal and PV models of varying complexities. The results of these evaluations provide very valuable information, to PV consumers, about how complex PV output prediction tools need to be to give acceptable results.