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 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.

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 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.

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.

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 covers the fundamentals of discrete time convolution, correlation, transform methods, time frequency signal representation, downsampling/upsampling and digital filters that are core to state of the art machine learning and deep learning architectures. The class has an integral Matlab based laboratory set of tasks that students are required to undertake.

The aim of this class is to develop an understanding of the principles by which information can transmitted with varying levels of security and the techniques by which communication systems can be analysed and designed.

This module aims to introduce the basic concepts, mathematical tools and design methods of classical control theory. It also introduces students to advanced control methods and provides a basic understanding of a time-domain approach to control analysis and the design of industrial processes.

The module covers: First and second order systems, delay process, simple saturation models; Simulation tools such as GUI, SIMULINK, MATLAB; Control system performance, transient and steady-state figures of merit, time domain step response, reference tracking and disturbance rejection in time domain; Simple control principles; State space representation of linear systems; Continuous time and discrete-time system fundamentals: eigen-values & eigen-vectors, stability, controllability & observability, canonical forms for systems; State-space control methods: pole placement state feedback control with/without observer design and linear quadratic optimal control.

At the end of this module students will be able to:

• model simple systems with transfer function and state space representation, create simulations using MATLAB and Simulink
• analyse linear open loop and closed loop systems both in frequency and time domain
• understand the theoretical and practical implications of feedback control systems, design control systems using simple PID tuning methods
• assess control performance, make analytical calculations and critical evaluation of control performance-related metrics
• apply and understand the advanced control methods, principles and applications in an industrial context

Assessment and feedback is in the form of a coursework and class test in Semester 1 (15%), a project report (15%) and exam (70%) in Semester 2.

This class will introduce you to the software engineering process through the development and application of C++ programming skills. You'll become competent in specifying, designing and developing software and in writing and testing programs of moderate complexity.

The objectives of this class is to provide a basic understanding of the wind resource and the principal of wind turbine power conversion including:

• an introduction to rotor dynamic suitable for non-specialist engineers and scientists
• an explanation of  the evolution of contemporary wind turbine technology

You'll gain sufficient understanding to outline the design and operation of multi-megawatt machines.

The objective of this class is to provide an understanding of the principles and key transport technologies which underpin 5G communications networks and architectures while giving an insight to the technical and strategic challenges associated with the provision of a Quality of Service (QoS)-based integrated future-network platform.

This module will provide you with the essential skills to design, build and test a sensor network for your smart grid application. The course makes use of radio frequency (RF) Internet of Things (IoT) development boards and a range of sensors and radio modules. You'll program the boards to communicate with the sensor nodes and wirelessly transmit data to gateway and onwards to a PC receiver or mobile wi-fi device. You'll analyse the measurement data and produce a graphical user interface to display it in a user accessible manner.

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.