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• W3046492684 abstract "This manuscript proposes a series of global models to estimate optimum annual tilt angle (βopt) 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 βopt 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 βopt. A variation of 40° with respect to βopt, implies a 12–18% energy loss depending on latitude. In addition, if only latitude is considered to estimate βopt, different expressions should be used for latitudes >50° depending on the hemisphere. These variations are a result of the influence of diffuse irradiance on βopt, due to the fact that sites with higher amounts of diffuse irradiance have a lower βopt. Secondly, a polynomial surface regression model to estimate βopt 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 βopt 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." @default.
• W3046492684 created "2020-08-07" @default.
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• W3046492684 date "2020-12-01" @default.
• W3046492684 modified "2023-09-27" @default.
• W3046492684 title "A global annual optimum tilt angle model for photovoltaic generation to use in the absence of local meteorological data" @default.
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• W3046492684 doi "https://doi.org/10.1016/j.renene.2020.07.098" @default.
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