Electricity Price Forecasting

Electricity price forecasting aims to accurately predict future electricity prices, crucial for efficient market operation and informed decision-making by energy producers and consumers. Current research emphasizes improving the accuracy and reliability of probabilistic forecasts, employing diverse models such as quantile regression, neural networks (including transformers, LSTMs, and NODE-LE combinations), and hybrid approaches that integrate statistical and machine learning techniques. These advancements are significant for optimizing energy trading strategies, managing energy storage systems, and enhancing the overall stability and sustainability of power grids.