MSc Electrical Power & Energy Systems

The aim of this class is to provide you with support for your general academic and professional development.

You'll undertake an advanced investigation of an electronic or electrical engineering topic of your choice, to enhance your learning, and develop presentation and communication skills.

This class will allow you to understand, critically analyse and assess technical requirements for power system operation, management and planning. It will enable you to carry out advanced types of power system analysis as well as understand and use results from these analyses in power system operation and planning. You'll also develop an advanced knowledge of the main concepts related to the function, design and operation of protection schemes for distribution, transmission and generation applications.

This class will present and give an understanding of the economics, trading and pricing of electricity supply and how it is shaped by technical, commercial and regulatory considerations.

It will give you an understanding of power system economics under an environment of multiple suppliers and users, and present the challenges, technologies and value of asset management within an electricity supply industry context. You'll gain a deep appreciation of factors affecting security of supply and how it might be quantified.

Modern energy conversion systems rely on the integration of range of technologies including power electronics, electromechanical actuators and energy storage elements. This class will build knowledge of the building block technologies and show their application to modern energy conversion systems.

This class will introduce you to the fundamentals of high voltage electrical insulating systems and the principles, mechanisms and characteristics of high voltage discharges in vacuum and condensed media. It will also provide you with a basic understanding of the behaviour of dielectric materials stressed with electric fields and their use in high voltage systems. You'll also gain an understanding of the principles of high voltage generation and impulse testing of the high voltage systems.

This class will provide an understanding of the principles of wind turbine power generation with attention to the wind resource, rotor aerodynamics, structural design, power conversion and control.

It will also examine the socio-economic issues relating to wind power and provide an underpinning in distributed energy resources including small scale generation, energy storage and demand management and their integration and management within power networks.

A range of different sensors covering electrical, electromagnetic, environmental and mechanical measurements will need to be deployed to achieve efficient management of a power system as we transition to a de-centralised system. This module will provide the student with a broad appreciation of modern sensor technologies and their implementation in industrially relevant applications. It will cover the fundamentals of metrology and traceability, sensor characteristics and limitations, review of commonly used sensors and physical operating principles, and sensor signal conditioning. Examples of ultrasonic and photonic sensors for non-destructive evaluation of components and asset management applications will also be covered.

Students will develop understanding in the principles of common power electronic systems and gain familiarity with the techniques required to analyse common power electronic circuits. The operating principles of common DC and AC machines will be investigated, so that techniques required to analyse DC and AC machines will be gained. Basic principles of generalised machine theory, and the link between DC and AC machines models will be explored. Students will also develop knowledge in the operation of power electronics used to control electrical machines and drives; along with understanding in the combination of machines and power electronics required to achieve speed and torque control in drive systems.

A strong part of the business case for smart grids is using intelligence and automation to gain more capacity from existing assets to avoid large expenditure on further assets. Also, autonomy and intelligence is key to the flexible operation of smart girds, integration of low carbon generation and effective interaction with consumers.

This module teaches the key AI and data science methods that are applicable to smart grids, and provides case studies of their application. We are moving to a future where much more can and will be monitored and new techniques, leveraging data analytics, are needed to fully exploit the data. Areas covered will be machine learning, knowledge based methods, distributed intelligence methods and architectures, applications in asset management, applications in network management and control.

The aim of the research project is to provide you with an opportunity to bring your knowledge and skills together and deploy them in a significant practical investigation, using relevant engineering literature, and where relevant, initial experiments or simulations.