Prediction of customer consumption and renewable energy production

This bachelor thesis examines the role of renewable energy sources (RES) in the energy market and their production and consumption forecast in the Czech Republic. Despite geographical constraints and continued dependence on fossil fuels, the analysis points to a significant increase in solar energy production, supported by technological advances and a large decrease in costs, and the potential for greater development of wind power. The study uses linear regression and Random forest regression for machine learning to reveal production dynamics strongly influenced by meteorological factors such as UV index and wind speed. These models can be useful for predicting electricity production, which could assist, for example, in planning electricity consumption in residential and commercial buildings. Furthermore, the SWOT analysis addresses strengths, weaknesses, challenges and opportunities in the global and local context. It describes the potential externalities associated with RES deployment, the limitations of weather forecasting and the associated RES production and consumption.