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The use of photovoltaic cells has increased in the last few decades as their manufacturing cost has decreased and as people have become more concerned about energy use. Designers need a reliable tool to predict energy production resulting from building integrated photovoltaic panels in order to make a sound decision on whether or not to incorporate this technology into a building. A few models that predict energy production have been developed, but they require a large amount of input data that are normally not available during the design phase. The 5-Parameter model investigated in this research uses the data provided by the manufacturers and semi-empirical correlation equations to predict the energy production for specified cell parameters and operating conditions. Data were obtained from a building integrated photovoltaic facility at the National Institute of Standards and Technology (NIST), where four different cell technologies were tested. These data were used to verify the accuracy of the energy production predictions, therefore validating the model suggested in this study. The model was analyzed for these four different cell technologies and compared with different existing models, showing acceptable and sometimes even better results than the existing models that require more input information. Because the model only requires a iv small amount of input data available from the manufacturer, it provides a valuable tool for energy prediction.v

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