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37 Think Tanks in BriefRecommended Readings Toward High-Resolution Projection of Electricity Prices: A Machine Learning Approach to Quantifying the Effects of High Fuel and CO2 PricesBy: Energy Economics4The article examines how machine learning (ML) can enhance the modeling and forecasting of electricity prices in the context of a transitioning energy market. It aims to identify key factors affecting day-ahead electricity prices and develop a highresolution ML model for daily price predictions over a year. Using data from 2015 to 2021 and analyzing 80 variables, the study emphasizes the significance of interaction variables that influence price fluctuations. The effectiveness of the model is validated by comparing predictions with actual day-ahead prices from the first half of 2022. Overall, the research highlights the need for improved forecasting methods due to the increasing integration of renewable energy and market volatility. Think Tanks in BriefRecommended Readings