Abstract
Abstract This manuscript proposes a series of global models to estimate optimum annual tilt angle ( β o p t ) as a function of local variables (latitude, diffuse fraction and albedo) based on the hourly irradiance data of 14,468 sites spread across the globe from the One Building database. As a result, these models can be used for any location in the absence of local meteorological data. First, a polynomial regression model, applicable worldwide, is proposed to estimate β o p t as a function of latitude. This model fits the global data considered with a 2% RMSE error. Average energy losses are estimated to be 1% for a 10° variation from β o p t . A variation of 40° with respect to β o p t , implies a 12–18% energy loss depending on latitude. In addition, if only latitude is considered to estimate β o p t , different expressions should be used for latitudes > 50 ° depending on the hemisphere. These variations are a result of the influence of diffuse irradiance on β o p t , due to the fact that sites with higher amounts of diffuse irradiance have a lower β o p t . Secondly, a polynomial surface regression model to estimate β o p t as a function of latitude and the annual diffuse fraction is proposed improving the results, reaching a 0.7% RMSE error. Thirdly, a simplified polynomial surface regression model to estimate β o p t as a function of latitude and albedo (without the influence of the diffuse fraction) is proposed, and finally a model gathering all three variables under study (latitude, annual diffuse fraction and albedo) to calculate the optimum tilt angle is presented.
Published Version
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