Курсы

[WiSe 2024/25] Exkursion EVT (Energiesysteme)

[WiSe 2024/25] Seminar: New Developments in Energy Markets

[WiSe 2024/25] Energy Economics

This course provides a comprehensive understanding of international energy markets and their dynamics. By the end of the course, students will have gained a foundational knowledge of how these markets operate and will be equipped to conduct thorough analyses of various energy sectors. The curriculum covers national and international transport and consumption of key energy sources, including fossil fuels and renewables. Students will explore the external costs associated with energy use and the instruments used to mitigate these costs. They will also gain insights into the latest developments in energy economics and learn essential skills in cost accounting and capital budgeting specific to the energy sector.

The course is designed with a focus on 40% knowledge and comprehension, 40% application and practice, and 20% analysis and methods. Key topics include energy balances, fossil fuel and renewable energy markets, electricity generation, energy efficiency technologies, and the use of modeling tools to evaluate innovations and regulatory measures. Additionally, the course covers the impacts on energy demand, innovation processes in energy economics, and the evaluation of energy systems, providing a holistic view of the field. This blend of theory and practical application ensures a well-rounded learning experience for all participants. Additionally, you have the chance to participate in a bonus point group project, which can boost your grade of the exam.

[WiSe 2024/25] PR Energieverfahrenstechnik I

[WiSe 2024/25] Wirtschaftliche Grundlagen für Studierende der Ingenieurswissenschaften

Wirtschaftswissenschaftliche Grundlagen für Studierende der Ingenieurwissenschaften (6 LP)


Lernergebnisse

Die Studierenden sollen: - ein Grundverständnis zu wirtschaftlichen Sachverhalten und Zusammenhängen vorweisen, - die Funktionsweise von wichtigen wirtschaftlichen Institutionen kennen, - Literatur und weitere Informationsquellen für ihre Arbeit beschaffen können sowie diese Informationen in wissenschaftliche und praktische Zusammenhänge einordnen können, - in der Lage sein, selbständig einfache Investitions- und Finanzierungsrechnungen durchzuführen, - anhand einer kontrakttheoretischen Einführung in das Wesen von Unternehmen einen Überblick über ausgewählte zentrale Begriffe und Konzepte aus der Betriebswirtschaftslehre, der Mikro- und der Makroökonomik haben (dabei steht der handelnde Unternehmer bzw. dessen Produktions-, Investitions- und Finanzierungsentscheidungen im Zentrum), - Entscheidungskriterien und die wichtigsten Restriktionen erarbeiten können, - anhand von Fallbeispielen das fundierte fachliche Wissen verstanden haben und anwenden können. Die Veranstaltung vermittelt: 40 % Wissen & Verstehen, 40 % Analyse & Methodik, 20 % Recherche & Bewertung

Lehrinhalte

- Unternehmen - Betriebliches Rechnungswesen - Kostenrechnung - Investitionsrechnung - Steuern, Abschreibung - Liquidität, Finanzierung, Kapitalmarkt - Bewertung von Unternehmen

Link zu MTS

[WiSe 2024/25] Data Science for Energy System Modelling

This module will cover the modelling and analysis of future energy systems, with a focus on renewable energy resources and how storage and network infrastructures can aid their integration into the energy system. Directly from the start of the course, students will be exposed to working with real data regarding historical weather data, land eligibility constraints, existing power plant fleets, transmission network data, electricity markets, and demand time series to learn about the challenges and solutions for a successful transition towards climate-neutral energy systems across the globe. Topics of the course include:

  • Time series analysis of wind and solar generation, energy demands, technology costs and prices.
  • GIS-based evaluation of renewable energy potentials.
  • Modelling of daily and seasonal energy storage.
  • Modelling of (linearised) power flows and transmission networks.
  • Introduction to mathematical optimization (or repetition thereof).
  • Electricity market designs with renewable electricity (merit order, market values, re-dispatch, nodal pricing)
  • System planning of renewables deployment, energy storage and transmission infrastructure.
  • Modelling of sector-coupling and demand-side management (examples from industry, buildings or transport).
  • Modelling under uncertainty and methods of complexity reduction.
  • Programming of energy system models in Python (e.g. pandas, geopandas, networkx, pyomo, cartopy, rasterio, PyPSA and atlite).
  • Visualization and communication of energy system analysis.