Main Article Content
Finding the optimum panel tilt angle for a photovoltaic device is crucial because it will efficiently convert the solar radiance into electricity. A variety of testing methods were used to determine the tilt angle so as to maximise the amount of radiation received by the solar panel. Recent research, however, has discovered that conversion efficiency is not exclusively determined by the
amount of radiation received and it is also dependent on the tilt angle of the solar panel. Solar panel tilt angle optimization model based on machine learning algorithms is proposed in this paper. Concentration on tilt angle is done, that maximises photovoltaic (PV) device radiance into electricity. Five forecasting models were developed using linear regression (LR), Ensemble, random forest (RF), support vector machine (SVM), and Gaussian Process Regression (GPR), all of which took into account various factors such as weather and dust level. Our model showed an increase in PV yield as compared to ideal point models when we used the best model..