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The participants understand various approaches for modeling energy systems. They therefore acquire the necessary knowledge in optimization, economics and game theory. They have basic knowledge about quantitative system models. They understand the problem of data acquisition and learn to gauge data quality. From this basis, students are able to create new models. They are capable of understanding and assessing models used in practice.

Introduction in mathematical modeling and its application to energy systems, Mathematical optimization as an important tool for energy models, Fundamentals of economics and important concepts of energy economics, General equilibrium theory and game theory with regard to energy and environment problems, System theory applied to global scope, Insights into modeling practice and its data requirements

Bachelor in natural sciences or engineering (fundamentals of higher mathematics and physics)

Lectures, presentations and blackboard Written exercise questions are to solved independently first and then discussed together.

Examination with the following parts: Module examination by written exam. Theoretical knowledge is tested with short answer questions as well as multiple choice. In order to check the knowledge on algorithms and applications the students have to perform calculations in the exam. Essay-type questions are given to test for methodological knowledge on data quality and model applications, within others. The written exam will be graded.

Thie 2008, Introduction to Linear Programming and Game Theory, Wiley Bhattacharyya 2011, Energy Economics, Springer Erdmann 2010, Energieökonomik, Springer Mankiw 2011 – Economics, South-Western Bofinger – Grundzüge der Volkswirtschaftslehre, Pearson Samuelson, Nordhaus 2005 – Economics, McGraw-Hill Club of Rome – Die Grenzen des Wachstums, 1972 More literature recommendations can be found in the lecture notes.