A wide range of factors affect the dynamic and complex environment that is the commodity market. The most significant of these are external drivers, such as political decisions and weather conditions, which cannot be directly controlled. Nevertheless, specific characteristics and price behaviors are exhibited by individual commodities, which manifest through seasonal patterns and characteristic fluctuations. This study aimed to analyze the day-ahead electricity market and identify the key factors shaping electricity price formation. Particular focus was given to the role of meteorological variables and the interrelationships between the prices of other commodities, such as natural gas, coal, and oil. The analysis combined empirical techniques, such as Fourier transform and correlation analysis, with a predictive LSTM model using a Seq2Seq architecture to forecast short-term electricity prices. A basic forecast of electricity prices in the day-ahead market was provided by a simple predictive model that was developed based on the findings. The results highlight the interconnectedness of energy markets and confirm that external factors play a crucial role in shaping electricity prices.
Matejko et al. (Mon,) studied this question.