Stud.IP Uni Oldenburg
Universität Oldenburg
28.11.2023 23:31:47
pre014 - Fundamentals for Renewable Energy (Vollständige Modulbeschreibung)
Originalfassung Englisch PDF Download
Modulbezeichnung Fundamentals for Renewable Energy
Modulkürzel pre014
Kreditpunkte 6.0 KP
Workload 180 h
Einrichtungsverzeichnis Institut für Physik
Verwendbarkeit des Moduls
  • Master European Master in Renewable Energy (Master) > Mastermodule
  • Master Sustainable Renewable Energy Technologies (Master) > Mastermodule
Zuständige Personen
  • Torio, Herena (Modulverantwortung)
  • Agert, Carsten (Modulverantwortung)
  • Torio, Herena (Prüfungsberechtigt)
  • Hoppmann, Jörn (Prüfungsberechtigt)
  • Günther, Andreas (Prüfungsberechtigt)
  • Ziethe, Paul (Prüfungsberechtigt)

After successful completion of the module students should be able to:

  • develop a basic understanding and skills for programming in languages relevant for energy systems analysis and modelling (Python)
  • understand and apply fundamental approaches for modelling energy systems (statistical and analytical models)
  • understand the most important economic principles
  • have a basic understanding of the functioning of energy markets
  • have an overview of the types and effectiveness of policies to promote renewable energy technologies
  • understand the interaction between society and renewable energy technologies
  • know which aspects play an important role when founding renewable energy start-ups and developing corporate strategies in the renewable energy sector
  • be able to assess alternative investment and financing possibilities in the context of renewable energy

The module is designed to give students a solid foundation to successfully start the MSc programme. The compulsory content from the fields of Energy Systems Modelling and Programming, as well as energy economics and management intends to provide a homogeneous knowledge base in these fields.

The compulsory content of the course "Python Programming and Modelling" provides a basic introduction to Python as one of the leading programming languages in the fields of energy system analysis as well as a sound introduction to fundamental modelling approaches used in energy system analysis. These two topics provide a solid basis required for understanding the content of the provided specializations during the summer term. Additional optional materials within this course include videos, scripts and exercises in the fields of electric power systems analysis, thermodynamics, fluid dynamics or solid-state physics and are provided as optional self-learning materials that can be used on demand by the students to update their knowledge on these fundamental fields.

The course "Renewable Energy Management" offers an introduction to the most important areas relevant to the management of renewable energy companies. To this end, the course first provides a general introduction to economic fundamentals and principles. Students then gain insights into the following topics:

  • Energy markets
  • Renewable energy policy and climate policy
  • Foundation and strategies of renewable energy companies
  • Investment and financing in the renewable energy sector
  • Innovation management in the renewable energy sector

Each of these topics will be explored in depth through practical exercises, including guest lectures, simulations, stakeholder discussions, case studies and investment calculations.

Python / Modelling:
T.Agami Reddy. 2011. Applied Data Analysis and Modeling for Energy Engineers and Scientists. Springer-Verlag New York.

RE Management (optional):

Anadon, L. D. (2012). Missions-oriented RD&D institutions in energy between 2000 and 2010: A comparative analysis of China, the United Kingdom, and the United States. Research Policy, 41(10), 1742-1756.

Hoppmann, J., Volland, J., Schmidt, T. S., & Hoffmann, V. H. (2014). The economic viability of battery storage for residential solar photovoltaic systems–A review and a simulation model. Renewable and Sustainable Energy Reviews, 39, 1101-1118.

Hoppmann, J., Peters, M., Schneider, M., & Hoffmann, V. H. (2013). The two faces of market support - How deployment policies affect technological exploration and exploitation in the solar photovoltaic industry. Research Policy, 42(4), 989-1003.

Gallagher, K. S., Grübler, A., Kuhl, L., Nemet, G., & Wilson, C. (2012). The energy technology innovation system. Annual Review of Environment and Resources, 37, 137-162.

Jacobsson, S., & Lauber, V. (2006). The politics and policy of energy system transformation - Explaining the German diffusion of renewable energy technology. Energy Policy, 34(3), 256-276.

Nemet, G. F. (2019). How solar energy became cheap: A model for low-carbon innovation. London: Routledge.

Ossenbrink, J., Hoppmann, J., & Hoffmann, V. H. (2019). Hybrid ambidexterity: How the environment shapes incumbents' use of structural and contextual approaches. Organization Science, 30(6), 1125-1393.

Simkins, B., & Simkins, R. (2013). Energy finance and economics: analysis and valuation, risk management, and the future of energy (Vol. 606): John Wiley & Sons.

Wüstenhagen, R., Wolsink, M., & Bürer, M. J. (2007). Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy, 35, 2683-2691

Unterrichtssprache Englisch
Dauer in Semestern 1 Semester
Angebotsrhythmus Modul
Aufnahmekapazität Modul unbegrenzt
Modullevel MM (Mastermodul / Master module)
Modulart Pflicht / Mandatory
Lehr-/Lernform Lectures, Exercises
Lehrveranstaltungsform Kommentar SWS Angebotsrhythmus Workload Präsenz
Vorlesung oder Seminar 2 SoSe oder WiSe 28
Übung 2 SoSe oder WiSe 28
Praktikum 2 SoSe oder WiSe 28
Präsenzzeit Modul insgesamt 84 h
Prüfung Prüfungszeiten Prüfungsform
Python / Modelling: During the semester
RE Management: At the end of the lecture period
Python / Modelling: Practical Exercises (3 exercises, weight 1/3 each)
RE Management: Written Exam