Analysis of the impact of ceiling prices on Turkish day-ahead electricity market clearing price

After the energy crisis in the post-pandemic period, the ceiling price has become more effective in the Turkish day-ahead electricity market. The limiting impact of ceiling prices is evident for hours when we see ceiling prices touched in the market. On the other hand, the effect of ceiling prices on hours when ceiling prices are not touched is essential to consider. Another critical point of consideration is the impact of ceiling prices on the other determinants of market clearing price. In this study, a comprehensive machine learning model comprising data sources of production, consumption, supply-demand curve points, weather conditions, and many other features are constructed, and ceiling price information of the trading day is integrated into this model. The model's behavior, which focuses on ceiling price and other features, is analyzed using the SHAP package in Python. With this analysis, the impact on hours where the ceiling price is not touched has been analyzed. The effect of ceiling prices on the determinants of ceiling prices is analyzed by building a statistical model that considers the ceiling price as a censor to the linear regression model, namely the Tobit model. A classical linear regression model with the same features as the Tobit model as a control model is constructed. The impact of ceiling prices on all hours of the day and the determinants of the market clearing price were found to be evident as the result of the analysis of this thesis.