An Attention-Based Deep Learning Approach for Forecasting Electricity Prices in Real-Time Electricity Markets
Date
2025-01-15
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Abstract
Real-time electricity markets are characterized by irregular and sudden price swings, leading to high price volatility and significant uncertainties for market participants. Accurate and informative electricity price forecasts are essential to reduce these uncertainties and enable more effective decision-making in energy generation, consumption, strategy planning, and risk management. This thesis presents a new forecasting framework for electricity prices in real-time markets, leveraging the capabilities of deep learning and advanced feature engineering. The proposed methodology integrates the Temporal Fusion Transformer (TFT), a deep learning model applied to time series forecasting, with dynamic clustering techniques to enhance forecasting accuracy. This is done by combining Hierarchical Density-Based Spatial Clustering of Applications with Noise and Dynamic Time Warping to cluster generators based on attributes such as geographical location, fuel type, installed capacity, and generation patterns. These clusters provide new covariates for forecasting models, enabling the method to adapt to the unique characteristics of any electricity market. The effectiveness of the proposed framework is demonstrated through a case study of the Ontario electricity market, where the methodology outperforms the forecasts of the system operator in terms of average error, accuracy, precision, and recall across a six-hour forecast horizon. This study underlines the framework's versatility and offers valuable insights into electricity price behavior, aiding market participants in mitigating risks and optimizing energy strategies.
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Keywords
Real-time electricity markets, Electricity price forecasting, Price volatility, Deep learning
Citation
do Carmo, J. (2025). An attention-based deep learning approach for forecasting electricity prices in real-time electricity markets (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.