Microwave Remote Sensing Based Solar Generation Forecasting Using Multiple Regression

For short-term estimates of solar energy, microwave remote sensing data is essential. This study forecasts solar generation using data from microwave remote sensing through the application of multiple regression algorithms. To commence the suggested work, the brightness temperature values for each frequency will be accessed and extracted from the Japanese satellite data portal. Processing the data with Beam Visat software is the second stage. Regression analysis considers the data frequencies that have the strongest correlation, as determined by calculating correlation and deterministic coefficient for each frequency, the sophisticated remote sensing technology can accurately predict the amount of solar generation for the following day.