DETERMINATION OF THE INFLUENCE OF THE SOLAR CELLS DESIGN ON THEIR FUNCTIONING EFFICIENCY - HILORME, TETIANA; NAKASHYDZE, LILIYA (Herald of Khmelnytskyi National University. Economic sciences, 2023)
An essential scientific and practical problem of sustainable development of the country’s energy sector is predicting the parameters and foreseeing the conditions of functioning of solar cells and solar elements in normal and emergency situations. It is emphasized that this allows to provide solar energy with high efficiency indicators, including return on invested capital in the solar panels construction. The main specific research method used is regression analysis aimed at building a model for predicting the total amount of generated energy from solar cells in ground-based installations under variable conditions. The distribution of the model output data by the number of solar cell modules is analyzed on the example of ground-mounted solar installations. To obtain empirical data, we selected 31 facilities in the Dnipro and Zaporizhzhia regions that use solar cells with different numbers of modules. This allows to calculate the weighted average amount of energy generated during operation in variable conditions. We distinguished 10 intervals of frequency values, with the largest range of values being in the range of 10000-20000 solar cell modules. The regression coefficients were checked by two criteria. According to the criterion of "t-statistics value": the coefficients are significant at a significance level of 0.05. The criterion of asymptotic significance determines the rejection of the null hypothesis in a statistical test. The random value is 170.3694, which is significantly higher than the critical value of the F-statistic of 3.33. A model of the dependence of the total amount of generated energy on the number of solar modules and the weighted average amount of generated energy was built on the basis of regression analysis. It is determined that the model influence factor "number of solar modules" has a positive effect on the resultant factor (solar cell productivity). Whereas the influence factor is "weighted average amount of generated energy". However, the influence factor "number of solar modules" is more significant. The obtained results allow us to assert the possibility of their implementation in the energy sector.