Increasingly, solar power generation is used to meet household needs, and forecasting solar power yield has attracted significant interest from scientists, which is important for optimal management of renewable energy. An approach based on energy data and forecasts is proposed in this study to predict the amount of solar energy required to power the electrical appliances in a camper. The relationship between solar radiation, temperature and generated power is analyzed using statistical methods. Based on the results, the predicted solar power yield follows an upward trend with the expected solar time, demonstrating the reliability of the proposed methods. The study demonstrates the need for models that can adapt to dynamically changing conditions using uncertainties in external factors. These approaches can improve the management of the energy system, increasing the efficiency and stability of renewable energy sources.