EPN-V2

PENG9620 Smart cities for a Sustainable Energy Future - From Design to Practice Course description

Course name in Norwegian
Smart cities for a Sustainable Energy Future - From Design to Practice
Study programme
PhD Programme in Engineering Science
Weight
5.0 ECTS
Year of study
2020/2021
Course history

Introduction

Students who complete the course are expected to have the following learning outcomes, defined in terms of knowledge, skills and general competence:

Knowledge:

On successful completion of the course, the student:

  • has a good understanding of the latest developments in the field.
  • has a deep understanding of the fundamental scientific theories, standards and methods that are applied in the field.
  • can evaluate the appropriateness and application of various scientific methods and approaches to research and development in the field.
  • can contribute to the development of new knowledge, theories, methods, standards, interpretations and documentation in the field.

Skills:

On successful completion of the course, the student can:

  • deal with complex technical questions and challenge established knowledge and practices within the field.
  • formulate questions, and plan and carry out research development work at an international level in the field.

General competence:

On successful completion of the course, the student can:

  • manage complex interdisciplinary tasks and projects
  • pursue their research ethically and with professional integrity.
  • participate in debates in international fora.
  • communicate research and development though recognised national and international channels

Recommended preliminary courses

Bachelor's or master's degree in engineering or science.

Required preliminary courses

Where appropriate, individual students will be introduced to specific parts of the course by attendance at selected lectures in master courses in the autumn:

  • Seminars/lectures where students present specific parts of the subject matter.
  • In addition, appropriate exercises (calculation or written) will be given, connected to the student's PhD project subject area

Learning outcomes

The following required coursework must be approved before the student can take the exam:

  • All planned seminars must be completed.
  • The given exercises must be passed

Content

The course is divided into three modules.

The first module covers lectures on economic interactions for the energy market, focusing mainly on applications such as demand response management (DRM), and vehicle-to-grid (V2G), etc.

The second module consists of lectures on current and emerging approaches such as machine learning and blockchain for energy intelligence and network security.

The third module will be a seminar which will include a hands-on session on tools such as optimisation and machine learning for solving specific problems in future energy information networks, and will conclude with a project assignment to be submitted by a given deadline.

Teaching and learning methods

Individual oral examination.

The exam cannot be appealed.

Course requirements

Closed book examination. No handwritten notes are permitted. A basic electronic calculator may be used.

Assessment

Pass or fail.

Permitted exam materials and equipment

Internal examination, with two examiners present. External examiner is used periodically.

Grading scale

Students should be aware that a master's degree in a related engineering discipline (electrical, construction, building services, architectural engineering or renewable energy) and relevant undergraduate courses covering the topics of basic indoor climate, and heat and mass transfer is recommended in order to complete this course.

Examiners

The course includes the following specific topics:

  • indoor environmental quality (IEQ) and health for human occupants: in-depth study of indoor air quality (IAQ), user control, thermal preferences and adaption. Advanced methods for field studies of IEQ/IAQ.
  • design of building envelopes, including building form, materials and their environmental assessment, and climate-adaption.
  • HVAC and building automation, including demand-control, automated commissioning, and optimisation of operation and facilities management.
  • building-integrated and city-wide renewable energy supply, including solar energy and energy storage.
  • methods for numerical simulation of indoor climate and energy use in buildings
  • theory and application of life-cycle analysis (LCA), and its methodological issues