Courses Catalogue

Renewable Energy Grid Integration

COURSE CODE: REN9207
COURSE CREDIT UNIT: 0
ACADEMIC PROGRAMME: Renewable Energy, PhD
COLLEGE/SCHOOL/FACULTY: School of Engineering and Applied Sciences
STATUS: Core
PROGRAMME TYPE: Postgraduate

Course Description

Renewable energy is widely recognized in power and related industry as the future of electric power. This unit develops a foundation for pursuing research in the area of sustainable energy systems. Issues pertaining to the modelling, control and grid integration of renewable energy sources, including solar and wind, are investigated from device and system level perspectives. The course further discusses the theory and practice of renewable energy and its integration to smart grid. Knowledge about a wide area of renewable technologies and understanding its role in the overall grid operation is also provided. Hence the doctoral students will be able to understand the technical design as well as the current economic conditions, including different regulators aspects, of renewables and its operation influence on power system operation, providing the relevant knowledge for working in a future renewable energy based electricity supply industry. Major topics include, Wind energy conversion systems, and micro grids with hybrid power sources. Modeling and control of renewable energy sources such as wind turbine generation, solar panel and fuel cell and power electronics interfaces will be presented.

Integration of renewable energy systems will also be covered.  . The coverage of fundamental material is complemented by exposure to system simulation software tools within the context of small projects.

COURSE JUSTIFICATION/RATIONALE

This course intends to provide a strong understanding of power systems, their operation and control and particularly of issues related to the integration of distributed renewable generation into the network. The content focuses on technical aspects of traditional and renewable electrical power generation, power transmission and distribution, power network stability, management and control, electricity market operations and smart grid technologies with particular emphasis on the integration of renewable generation onto the network at both transmission and distribution level and the challenges and opportunities associated with that. A solid basis in the understanding of future power networks with distributed generation, storage and smart grid technology is given.

LEARNING OBJECTIVES
By the end of this course, the student should be able to:

  • Discuss basic power electronics principles, like the dc-dc converter and dc-ac inverter.
  • Apply fundamental engineering modelling methods to understand the operation of electrical power systems with embedded generation;
  • Describe the role of and model the operation of power electronic converters within the context of solar and wind based generation;
  • Explain the basic principles of renewable energy integration to smart grid to design a renewable energy system for smart grid using software simulation tools for electrical power systems.
  • Apply techniques from the theory of automatic control systems to address problems associated with the operation and grid integration of renewable energy resources;
  • Gain knowledge about economic and regulatory aspects of renewable generation to evaluate various solutions for the design of renewable production systems

LEARNING OUTCOMES
A doctoral student completing the course is expected to:

  • Apply advanced knowledge of electrical power system operations and control to analyse the challenges and opportunities for distributed renewable generation in both large interconnected grid and microgrid settings.
  • Assess renewable energy applications and projects in the context of integration into both the physical and economic electricity markets.
  • Describe the principles and requirements of the next generation future power network (or smart grid), incorporating distributed generation and storage and demand management.
  • Discuss the principles, power and limitations of computer modelling of complex power networks incorporating distributed generation and storage.
  • Address problems associated with the operation and grid integration of renewable energy resources;