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Development of a Python model for electricity retail prices in Germany under present regulatory framework and future expectations of high re penetrations

  • This thesis presents the perspective and basis for modeling of retail electricity price components in Germany. Detailed Python models are developed to provide predictions for yearly development of average network charges, EEG, StromNEV-19 and KWK surcharges for the period 2015-2035. For network charges and EEG surcharge, scenario-B (2035) from NEP2015 has been chosen as the model scenario. For KWK surcharge, the 2025 KWK share target, set by KWKG-2016, has been chosen as the model scenario. Individual component model results are validated against available academic literature and institutional reports. Model results for EEG surcharge, indicate an increasing yearly EEG costs till 2024, after which the expiring EEG plants of past will unburden the related high costs and EEG surcharge will drop but still be around 99% of 2015 level in 2035. Model results for network charges indicate a consistently increasing yearly trend owing to high grid investments needed for reaching the target RE share of 57%. KWK model results also indicate a growing KWK surcharge until 2020 which then would remain stagnant at that level onwards. All model results are collected under three consumption categories, namely, households, privileged and nonprivileged industries. The final results indicate that the average German household will face an overall increase of around 3.37 Cents/kWh in retail electricity prices (excluding VAT) till 2028, after which the retail prices will drop a little due to dropping EEG surcharge. The similar but slightly reduced trend can be seen for nonprivileged industrial consumption. The increment effect, however, is only minute for privileged industrial consumption due to high exemptions in EEG & KWK surcharges and reduced individual network charges.

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Author:Bilal Hussain
Referee:Johannes Hamhaber
Document Type:Master's Thesis
Publishing Institution:Hochschulbibliothek der Technischen Hochschule Köln
Granting Institution:Technische Hochschule Köln
Date of Publication (online):2017/10/06
Tag:EEG; Python; Renewable energy
Electricity prices
Institutes:Fakultät für Raumentwicklung und Infrastruktursysteme (F12) / Fakultät 12 / Institut für Technologie und Ressourcenmanagement in den Tropen und Subtropen
CCS-Classification:J. Computer Applications
Dewey Decimal Classification:500 Naturwissenschaften und Mathematik
JEL-Classification:C Mathematical and Quantitative Methods
Open Access:Open Access
Licence (German):License LogoCreative Commons - Namensnennung