Basic knowledge of mathematics, differential equations, statistics and programming is assumed.

Topics include:

• Time series analysis of wind, solar and energy demand in Europe.
• Complex network theory.
• Power flow in electrical networks.
• Modelling storage, the role of storage versus networks.
• Basics of optimisation, Karush-Kuhn-Tucker conditions.
• Basics of microeconomics.
• Economics of electricity markets.
• Short-run versus long-run efficiency.
• Network optimisation, storage optimisation.
• Programming energy system models.
• Coupling electricity to other energy sectors.
• Role of renewables in electricity markets.

Additional topics may also include:

• Dynamics in power networks.
• Contingency analysis.
• Effects of climate change on energy systems.

This module will cover the many factors that influence future energy system design, with a focus on renewable energies and their interactions with energy networks.

After the completion of the course students will have obtained basic knowledge of energy system modelling and optimisation, and be able to analyse different concepts for the integration of renewable energy, such as network reinforcement, storage, demand-side management and sector coupling.

Students are in the position to:

• describe and explain the challenges when integrating renewable energy in energy systems
• critically evaluate different concepts for the integration of renewable energy
• do model calculations for power systems based on renewable energies
• describe the basics of electricity market theory and operation
• program energy system models using standard open source tools