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Friday, 12 September, 2025

Master´s Thesis Defense Presentations 2025

Defense Committee: Jan Zápal (CERGE, chair), Michal Bauer (CERGE), Filiáp Matějka (CERGE)

09:00     Emma Mikayelyan:  Financial Literacy across the Commonwealth of Independent States: a Comprehensive Cross-Country Analysis with a Focus on Gender Disparities

                Chair: Daniel Münich

                Opponent: Jan Zápal

10:00     Mario Aquiles Guzmán Fredes:  Water Scarcity: Its Present, Future, and Possible Mitigation Through Technology

               Chair: Sebastian Ottinger

               Opponent: Paolo Zacchia

11:00     Christopher Nyasha Mutama: Electricity Load Forecasting: Impact of COVID-19 on the Czech Republic’s Load Profile

                Chair: Silvester van Koten

                Opponent: Konuray Mutluer

Christopher Nyasha Mutama

Abstract:

Accurate forecasting of electricity demand is critical for stable grid operation, energy policy formulation, and investment planning. Shocks threaten this stability, which in turn potentially introduces economic problems. This thesis investigates the impact of COVID-19 on the Czech Republic’s electricity load profile. Unlike most forecasting methods which rely on historical consumption data, this study generates synthetic electricity load profiles based on weather variables. The annual peak load is the only load input for the model and is intended to condition the model to the consumption limits. The methodology is inspired by Behm et al. (2020), and the resulting counterfactual analysis lays the foundation for estimating the impact of future shocks on the Czech Republic’s load profile in the medium and long term. Through an iterative and systematic evaluation of a LASSO regression model, an Artificial Neural Network (ANN), and an eXtreme Gradient Boosting (XGBoost) model, this study identifies XGBoost as the most robust and accurate method for this application. Using an XGBoost model with LASSO-selected features, I estimate that COVID-19 reduced electricity demand in the Czech Republic by 2.66 TWh between 2020 and 2021, equivalent to 4.0% of 2019’s total annual load (66.15 TWh). This “COVID” effect was more pronounced in 2020 compared to 2021. A statistically significant difference was found between day and night impacts: the calculated average reductions in consumption were 145.68 MW during the day and 157.37 MW at night (p = 0.03). While unexpected, the pronounced night-time decline may reflect broader systemic changes in industrial and commercial consumption patterns that persisted, and may still persist beyond the typical working hours.

Full Text: “Electricity Load Forecasting: Impact of COVID-19 on the Czech Republic’s Load Profile"