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
Name of exam | Applied Optimization for Energy Systems Engineering: Theory and
Practice |
Type of exam | Oral exam |
ECTS | 5 |
Assessment | 7-point grading scale |
Type of grading | Internal examination |
Criteria of assessment | The criteria of assessment are stated in the Examination
Policies and Procedures |