Prediksi Daya yang Dihasilkan oleh Panel Surya dan Turbin Angin Menggunakan Data Cuaca Historis Cuaca

Abstract

This research aims to develop a power output prediction model for solar panels and wind turbines by utilizing historical weather data, including solar radiation, temperature, wind speed, and wind direction. The historical weather data serve as the primary variables in the prediction model to enhance the accuracy of the estimated power output. Additionally, a real-time monitoring system is designed using the ESP32 microcontroller combined with the HX710B sensor to measure air pressure directly. The pressure data is transmitted via a WiFi network and analyzed to observe the effect of air density on the performance of wind turbines and solar panels. Observations indicate that air density positively influences the efficiency of wind turbine power generation, whereas no significant efficiency improvement is observed in solar panels. This research is expected to contribute to the development of renewable energy power systems that are more adaptive to weather data, resulting in more stable and efficient performance under various environmental conditions.