Development of Power Production

• Data acquisition for training the machine learning model related to energy production (data related to various energy production methods and meteorological data);
• Initial data analysis and processing;
• Further selection and in-depth processing of data, and creation and training of a machine learning model capable of predicting energy production from various sources over a specific period of time (NOTE: the model may be refined or altered in the future as needed);
• Initial analysis of model performance metrics (r^2 and oob score);
• Initiating discussions on incorporating the results obtained by this model and its utilization in the overall project (e.g., integration with the energy market prediction model, prototype, and end-user interface).

Machine Learning and Statistics Energy Price

• Study of the energy market and how prices are calculated;
• Acquisition of data for training the machine learning model related to energy prices;
• Analysis, selection, and processing of data;

• Conclusion of the study on how blockchain chains and smart contracts function;
• Conclusion of the research on the legal conditions our project could face in the future;