Emerging Dynamics in the Electricity Markets: Net Zero Transition through Machine Learning

This paper provides an overview of the power value chain, from production to trading in European markets highlighting the need for thorough statistical analysis, the use of advanced mathematical-financial modelling, and the application of machine learning to improve the forecasting and management of energy production from renewable sources. Machine learning techniques are employed to develop shortand medium-term forecast models, enhancing the speed and accuracy of predictions and, consequently, the management of renewable energy production. Additionally, these models support the planning of sales and energy storage strategies, contributing to the stability of the electrical grid and hence maximizing profits. In a forthcoming paper, we will focus on enhancing these models and exploring further applications of AI techniques to improve the efficiency and reliability of the energy system by enriching the scientific discussions with diagrams and simulations