Influência das variáveis meteorológicas na eficiência dos painéis solares e mapeamento solarimétrico utilizando modelo atmosférico (wrf) para о Estado de Alagoas

Abstract

The use of photovoltaic energy has been growing significantly on a global scale, as this energy source is crucial in combating climate change by reducing CO2 emissions. Additionally, it harnesses solar light to generate energy, a resource that is abundant and inexhaustible, producing electricity with no negative environmental impacts. The adoption of solar panels contributes to the diversification of the energy matrix, making the study of the performance of photovoltaic panels increasingly important. By calculating the Performance Ratio (PR), one can obtain the true performance of the photovoltaic array. The PR was calculated to evaluate the real efficiency of the system in relation to its nominal capacity, where a photovoltaic array installed with microinverters was used. According to the literature, microinverters provide the best PR results. The analysis took into account meteorological variables and the effect of dirt on the performance of the photovoltaic array. The installation achieved good results, with the average PR value being above 80%. Based on the performance analysis, a photovoltaic equation was developed using linear regression and multiple linear regression models, utilizing the array’s output and meteorological variables. From this, a spatial map of photovoltaic potential was created using the best-developed equation, specializing the results based on the WRF-Solar model.The correlation of PR results in relation to solar radiation and air temperature was inversely proportional (-0.76 and -0.74, respectively). The correlation with relative humidity and precipitation was 0.52 and 0.46 (with INMET) and 0.48 (with EMA). This moderate correlation is due to the fact that both variables are responsible for cooling the system, thus improving the performance of the photovoltaic panels. With the spatial mapping of the photovoltaic map, values ranging from 2.4 kWh/kWp to 4.8 kWh/kWp were found across the entire state.