Forecasting the solar energy potential of Muş province with machine learning

Energy production forecasting is of critical importance for decision-making processes and the integration of variable energy sources into the grid, as these forecasts allow fluctuations in energy supply to be addressed at different time and spatial scales. In particular, the solar energy sector has a high production share in renewable energy production. Solar energy has the potential to meet humanity's energy needs in a clean, renewable and sustainable way. Solar energy is important in avoiding the environmental impacts of fossil fuels and combating climate change. Solar radiation forecasting, which is directly related to solar energy production, will contribute to this production process. This thesis study for Muş Province in the Eastern Anatolia Region of Turkey was carried out using machine learning methods to determine the solar energy potential of the province. Solar radiation prediction was performed with time series and regression methods using meteorological data between 2018 and 2023. Successful forecasts were made with the methods used. The results of the study show that Muş has a significant potential for solar energy production.