Original title: Predikce spotřeby elektřiny: Dopad COVID-19 na zatížení elektrizační soustavy v České republice
Translated title: Electricity Load Forecasting: Impact of COVID-19 on the Czech Republic's Load Profile
Authors: Mutama, Christopher Nyasha ; Van Koten, Silvester (advisor) ; Mutluer, Konuray (referee)
Document type: Master’s theses
Year: 2025
Language: eng
Abstract: [eng] [cze]
CHARLES UNIVERSITY FACULTY OF SOCIAL SCIENCES CERGE-EI Electricity Load Forecasting: Impact of COVID-19 on the Czech Republic's Load Profile Master's thesis Author: Christopher Nyasha Mutama Study program: MA Economic Research Supervisor: Prof. Silvester van Koten Year of defense: 2025 Declaration of Authorship The author hereby declares that he compiled this thesis independently, using only the listed resources and literature, and the thesis has not been used to obtain any other academic title.1 The author grants to Charles University permission to reproduce and distribute copies of this thesis in whole or in part and agrees with the thesis being used for study and scientific purposes. Prague, July 29, 2025 Christopher Nyasha Mutama 1 During the preparation of this thesis, the author used Gemini and ChatGPT to assist with refining the translation of the abstract from English to Czech, LaTeX code formatting and PDF/A compliance of the final files. The author reviewed and edited the content after use of these tools and takes full responsibility for the final content. Abstract Accurate forecasting of electricity demand is critical for stable grid operation, energy policy formulation, and investment planning. Shocks threaten this sta- bility, which in turn potentially introduces economic problems. This thesis... CHARLES UNIVERSITY FACULTY OF SOCIAL SCIENCES CERGE-EI Electricity Load Forecasting: Impact of COVID-19 on the Czech Republic's Load Profile Master's thesis Author: Christopher Nyasha Mutama Study program: MA Economic Research Supervisor: Prof. Silvester van Koten Year of defense: 2025 Declaration of Authorship The author hereby declares that he compiled this thesis independently, using only the listed resources and literature, and the thesis has not been used to obtain any other academic title.1 The author grants to Charles University permission to reproduce and distribute copies of this thesis in whole or in part and agrees with the thesis being used for study and scientific purposes. Prague, July 29, 2025 Christopher Nyasha Mutama 1 During the preparation of this thesis, the author used Gemini and ChatGPT to assist with refining the translation of the abstract from English to Czech, LaTeX code formatting and PDF/A compliance of the final files. The author reviewed and edited the content after use of these tools and takes full responsibility for the final content. Abstrakt Přesné predikce poptávky po elektřině jsou klíčové pro stabilní provoz elek- trizační soustavy, tvorbu energetické politiky a plánování investic. Různé šoky tuto stabilitu ohrožují a mohou vést k hospodářským problémům. Tato práce...
Keywords: Artificial Neural Network (ANN); Counterfactual Analysis; COVID-19 Impact; Czech Republic; Electricity Demand Forecasting; Exogenous Shocks; LASSO Regression; Load Profile; XGBoost; Dopad COVID-19; Exogenní šoky; Kontrafaktuální analýza; LASSO regrese; Predikce poptávky po elektřině; Umělá neuronová síť (UNS); XGBoost; Zátěžový profil; Česká republika

Institution: Charles University Faculties (theses) (web)
Document availability information: Available in the Charles University Digital Repository.
Original record: http://hdl.handle.net/20.500.11956/203722

Permalink: http://www.nusl.cz/ntk/nusl-691268


The record appears in these collections:
Universities and colleges > Public universities > Charles University > Charles University Faculties (theses)
Academic theses (ETDs) > Master’s theses