Abstract
The direction and environment of photovoltaics (PVs) may influence their energy output. The practical PV performance under various conditions should be estimated, particularly during initial design stages when PV model types are unknown. Previous studies have focused on a limited number of PV projects, which required the details of many PV models; furthermore, the models can be case sensitive. According to the 18 projects conducted in 7 locations (latitude 29.5–51.25N) around the world, we developed polynomials for the crystalline silicon PV energy output for different accessible input variables. A regression tree effectively evaluated the correlations of the outcomes with the input variables; those of high importance were identified. The coefficient of determination, indicating the percentage of datasets being predictable by the input, was higher than 0.65 for 14 of the 18 projects when the polynomial was developed using the accessible variables such as global horizontal solar radiation. However, individual equations should be derived for horizontal cases, indicating that a universal polynomial for crystalline silicon PVs with a tilt angle in the range 0°–66° can be difficult to develop. The proposed model will contribute to evaluating the performance of PVs with low and medium tilt angles for places of similar climates.
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development
Cited by
4 articles.
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