A Review of Recent Trends in Electricity Price Forecasting Using Deep Learning Techniques

Abstract

Precise electricity price forecasts are gaining importance as the economy evolves. For years, researchers have attempted to generate such forecasts using artificial intelligence techniques. Recently, there has been a surge in the application of deep learning methods. This paper aims to identify the latest developments in this field, present the most significant solutions, and highlight existing research gaps. Numerous articles published since 2023 that employ deep learning neural networks for electricity price forecasting are analyzed. In addition to describing individual novel models, the paper provides a summary of error metrics for selected forecasting systems, indicating the markets covered by each study. One of the key conclusions drawn from this review is the limitation in the length of test sets, which in some cases were restricted to only a few days. The review also underscores the rationale for employing hybrid approaches that combine different deep neural network architectures and often incorporate data preprocessing.