Content, progress and pedagogy of the module

The module is based on knowledge achieved in Probability Theory, Stochastic Processes and Applied Statistics and Optimisation Theory and Reliability.

Learning objectives

Knowledge

• Knowledge of integrated electrical/thermal energy systems engineering problems, which are suitable for optimisation
• Knowledge of building different programming models such as non-linear models and mixed-integer programming, and solving them using appropriate methods
• Knowledge of optimisation tools suited optimization of integrated electrical/thermal energy systems.
• Knowledge about the optimal design and planning of energy systems (system configuration, placement and sizing of energy-related devices)
• Knowledge about optimal operation and scheduling of different energy systems such as multi-energy systems and micro grids, and integrated systems such as power-gas and power-heat networks
• Knowledge about models for optimal dispatch of energy sources considering technical constraints and regulatory frameworks
• Knowledge about incorporation of optimisation techniques in energy systems economics

Skills

• Ability to analyse and solve advanced optimisation problems such as mixed-integer non-linear, non-deterministic and non-control flow programs
• Ability to judge the usefulness of different scientific methods for analysis (e.g. cost-benefit) and modelling of energy systems using digital platforms
• Ability to verify the analytical and numerical approaches by means of experimental data.
• Ability to integrate optimisation models into real-life problems and analyse effectiveness of solutions in practice
• Ability to select an appropriate optimisation procedure and tool for the energy systems and evaluate the optimisation results

Competences

• Communicate technical issues with specialists in cross-disciplinary teams and the public
• Conscious attitude towards the use of appropriate optimisation tools and techniques within energy systems engineering (specifically electric/thermal engineering)
• Control the working and development process within the project theme, and develop new and efficient solutions within the energy sector
• Define and analyse scientific problems in the area of modelling and optimisation of energy systems

Type of instruction

The Master's programme is based on a combination of academic, problem oriented and interdisciplinary approaches and organised based on the following types of instruction that combine skills and reflection:

• Lectures
• Class teaching
• Project work
• Workshops
• Exercises (individually and in groups)
• Digital learning in different ways including flipped class room, blended learning, game or quiz
• Supervisor feedback
• Professional reflection
• Portfolio work
• Laboratory work

Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student

Exam

Exams