Solar Panel Analysis for Forecasting Solar Irradiation Using Fuzzy Time Series and ANN Methods - Falah, Moh. Zainul; Wahyu Tri Handoko; Sujito; Abdullah Iskandar Syah; Muladi; Arif Nur Afandi (Journal Electrical and Computer Experiences, 2023)
Solar energy is very important because it is a renewable and environmentally friendly source of energy. The demand for solar energy is increasing every year because people are increasingly aware of the importance of using clean and sustainable energy sources. This study aims to analyze the performance of solar panels using a solar irradiation forecasting model developed by the Fuzzy Time Series and Artificial Neural Network (ANN) methods. Solar irradiation data obtained from measurement of solar irradiation by means of IoT is used as input in the forecasting model. The forecasting model is then tested to see its accuracy in predicting solar panel performance. The test results show that the developed forecasting model has high accuracy in predicting solar panel performance. Therefore, the Fuzzy Time Series and ANN methods can be used as an effective tool in analyzing the performance of solar panels by taking into account environmental factors that have an impact on electricity production from solar panels. This research can be a reference for solar panel developers to improve solar panel performance by utilizing solar irradiation forecasting information.