The Solar Forecasting Prize challenged participants to develop innovative methods for predicting solar power generation. My solution focused on improving short-term solar forecasting accuracy by combining weather prediction models with machine learning techniques. The approach helps grid operators better integrate solar energy into the power system by providing more reliable forecasts of solar generation.