Resumo:
Photovoltaic solar energy has shown strong growth in recent years because it is a clean, renewable, competitive and accessible energy. In this context, the Design of Experiments (DoE) is premised on the analysis, modeling and optimization of experiments, with statistical reliability, data and cost savings. In this way, photovoltaic generation was analyzed according to meteorological variables: solar radiation, temperature, wind speed and relative humidity, as well as the isolated and combined influence of each factor, with the objective of validating the model in uncontrollable conditions and define the optimal operating point. Pareto charts and Response Surfaces support the generated power equations, allowing the prediction of results and future estimates, as well as the definition of technical and economic optimal points. In addition, the case study demonstrated the validity of the DoE in an open environment and in the operation of the panels, allowing the identification of noise throughout the analyses, such as wind speed and relative humidity. Situations still little explored in the literature, even with high efficiency in noise analysis and with the potential to contribute to the diagnosis of failures and preliminary studies for the implementation of new projects.
