Forecasting Hourly Electricity Prices in European Nations: Utilizing Machine Learning and Deep Learning Techniques for Sustainable Energy Decision-Making

Abstract

Machine learning and deep learning techniques are used to anticipate hourly power costs for European countries (France, Italy, Belgium, Spain, the UK, and Germany). The research intends to develop exact forecast models based on past power pricing data through data visualization and model evaluation. Accurate forecasting is improved by studying seasonality patterns and price trends in various countries. In order to understand pricing changes, the study looks into international interdependence. It also offers useful information to energy sector players, facilitating better energy trading, grid stability, and environmentally friendly decision-making. The suggested methodology accurately forecasts electricity prices, encouraging the use of clean and effective energy sources.