A global annual optimum tilt angle model for photovoltaic generation to use in the absence of local meteorological data

Abstract

This manuscript proposes a series of global models to estimate optimum annual tilt angle (ßsubíndice opt) 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 ß[subíndice opt] 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 ß[subíndice opt] . A variation of 40° with respect to ß[subíndice opt] , implies a 12–18% energy loss depending on latitude. In addition, if only latitude is considered to estimate ß[subíndice opt], different expressions should be used for latitudes depending on the hemisphere. These variations are a result of the influence of diffuse irradiance on , due to the fact that sites with higher amounts of diffuse irradiance have a lower ß[subíndice opt]. Secondly, a polynomial surface regression model to estimate 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 ß[subíndice opt] 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.