This module provides students with a solid understanding of analysis and management strategies to advance the use of economically and environmentally sustainable electrical energy systems. Key topics include distributed and renewable generation, supply and demand side strategies, power distribution system models with embedded generation and microgrids, supply-grid interconnection, and reliability and power quality issues.
A core power systems course that equips students with analytical tools to assess the performance of electric power systems under various operating conditions and to plan future system development. It also introduces industry relevant protection schemes and methodologies for ensuring robust and reliable power supply.
A graduate level course covering principles and computational techniques of evolutionary computation - a class of machine learning methods inspired by biological evolution. The course emphasises applications of evolutionary algorithms and related techniques to intelligent systems and real world problem domains.
A graduate level course that explores advanced concepts and technologies in smart grids, including power converters for emerging energy systems, electric and fuel cell vehicles, battery management, and intelligent control systems. It integrates practical and theoretical perspectives to equip students with a comprehensive understanding of modern grid technologies.
This graduate course delves into selected emerging areas of smart grid research and practice. Topics include microgrid architectures, smart vehicle technologies, energy storage systems, intelligent multi agent control, and cybersecurity aspects in smart energy systems.