PENG9200 Scientific Research Methods and Data Analysis in Engineering Science Emneplan

This course covers two central areas of scientific research: the construction and justification of a research plan, and the subsequent analysis and interpretation of its implementation and of the resulting data.

The course will be offered once a year, provided 3 or more students sign up for the course. If less than 3 students sign up for a course, the course will be cancelled for that year.

None.

None.

The student is expected to have the following outcomes on completion of the course:

Knowledge:

On successful completion of the course, the student:

• has advanced knowledge of the research process.
• has advanced knowledge of data collection techniques relative to his/her field of study within engineering sciences
• can critically assess the usefulness of using qualitative, quantitative, and mixed methodologies in the engineering sciences.
• has a high-level command of qualitative and quantitative methods of analysis relative to his/her field of study.

Skills:

On successful completion of the course, the student can:

• construct a problem statement or research question and evaluate its soundness.
• create technically and scientifically sound research proposals.
• select a methodology to address a research problem.

General competence:

On successful completion of the course, the student can:

• distinguish and formulate research problems.
• develop and critically assess the components of a research proposal.
• critically reflect on the nature of research, scientific practice and knowledge

The results for the project assignment, process description, and the code will be assessed by the course leader. The exam can be appealed.

This course will feature lectures and practical work to provide both theoretical and hands-on content. The students will work in groups and complete various assignments related to the practical and theoretical aspects of the course. The students will supplement the lectures and group work with their own reading.

None.

This course covers contemporary topics in smart energy systems such as smart power grid, smart buildings, vehicle-to-grid (V2G) and communication technologies for and network security in smart energy systems, including emerging approaches towards energy intelligence such as machine learning and blockchain.

The course will be offered once a year, provided 5 or more students sign up for the course. If less than 5 students sign up for a course, the course will be cancelled for that year

None.

Knowledge

On successful completion of the course, the student:

• is at the forefront of knowledge about smart energy systems, both at the system level and at the specific component/application level.
• understands what different technologies can be used at what level in energy generation, transmission, distribution and consumption networks.
• knows about communication technologies and their performance limits for enabling energy intelligence in smart energy systems.

Skills

On successful completion of the course, the student can:

• solve resource optimisation problems for the energy information network.
• apply optimisation techniques and machine learning-based approaches for residential demand response management and vehicle-to-grid.

General competence

On successful completion of the course, the student can:

• communicate and collaborate with experts from other disciplines on larger interdisciplinary and multidisciplinary research projects.
• Recognise and assess a project's potential and value
• participate in debates and communicate results through recognised international channels, such as academic conferences.
• can construct and develop relevant models and discuss the model's validity.
• Disseminate knowledge to broader audiences

Module 1 and 2 will take the form of a series of lectures. Module 3 will be a combination of hands-on sessions along with the project assignment.

Practical training

The students will solve specific problems using optimisation or machine learning techniques. The students will submit a brief report with results for the problem in the assignment, also describing the process they used for solving the assignment, including the code.