The course

Smart Power Systems (MSc)

This MSc examines the crucial changes in modern power systems today, as well as developments for a sustainable energy future. It will prepare you for the large variety of jobs in the Power System sector, from smart meters and demand side management, load forecasting, distribution or transmission, energy generation, renewables or energy storage.

On completion of this masters you will have an advanced understanding of:

- Current and future Power Systems

- Machine learning, required for many areas of the modern power system

- Coverage of advanced communications systems for smart grid applications

- Training in Engineering management and professional practice

This specialised course provides a strong theoretical and practical understanding of electronic and electrical engineering with links to industry-related topics and employability skills.

You will have the opportunity to gain advanced, research-specific skills and academic knowledge to take forward into further study or into your career.
You will become part of a dynamic research environment where you will acquire industrially relevant knowledge to make a successful contribution to tomorrow’s systems that support everyday life.

From time to time, we make changes to our courses to improve the student and learning experience. If we make a significant change to your chosen course, we’ll let you know as soon as possible.

Course structure

Core Modules

This is a major group project in which students will work on an agreed practical problem that is relevant to tomorrow's societal needs and agreed with their supervisor. The working practice of the groups will be modelled on industrial practices in terms of planning, keeping proper records of meetings and the progress of work, and students will each take on a responsibility within the team that is vital to the professional and successful running of the group project. The overall aim is to provide students with a full appreciation of mechanisms that can support professional group working and its management in engineering practice in the context of exploring and researching solutions to a topic relevant to society.
The aim of this module is to provide theoretical and practical knowledge relating to pattern recognition. The indicative content for this module includes the study of fundamental pattern recognition in relation to supervised and unsupervised learning. Topics will include Bayesian decision theory, Artificial Neural Networks and Support Vector Machines (amongst others). The nature of these algorithms will be studied along with engineering techniques for developing smart applications. Further, deep learning for engineering applictions (e.g. classification of electrocardiograms) will be studied. Finally, students will undertake a coursework to an apply an appropriate machine learning methodology to solve a real-world pattern recognition problem.
In this module you will develop an understanding of the various types of power generators, focussing on renewable technologies. You will look at the main benefits and drawbacks of different generation types and examine why a generation mix is desirable. You will consider the technical, environmental, sustainability, cost and political factors driving engineering and commercialisation decisions, and evaluate the objectives and constraints that are involved in optimisation procedures for power system applications, such as optimal wind farm layout.
The aim of this module is to cover the entire process of using a primary source of energy, converting it to electricity and delivering the generated electricity to where it is required. It provides students with useful knowledge and skills. This course covers the power system basics, such as complex power, calculations including phasors, reactive compensation, power factor, conversion of circuits to phasor domain, instantaneous values, three phase circuits, calculations related to transmission lines, transformers, per unit calculations, synchronous and induction machines, powerflow and optimal power flow. Labs are designed to allow students to actively engage with the covered material and to work through the calculations using Matlab as well as hand calculations.
This module covers advanced communications systems, focusing on microwave, optical, and broadband technologies. Students will gain knowledge and understanding of these systems and their applications in high-speed networks. They will learn to analyse complex microwave systems using mathematical and computational tools, such as estimating satellite link budgets. The module also covers the breakdown and categorisation of communication system elements, including high-speed optical data network architectures. Students will study radio propagation, design principles of advanced microwave systems, and sources of degradation, distortion, and losses. Additionally, they will be introduced to the latest CAD tools for evaluating and synthesising practical microwave systems.
The aim of this module is to provide students with the opportunity to carry out an in-depth engineering project, potentially in collaboration with industry, to solve a real-world problem or create a novel product. For specialised MScs, the project will be related to the specialisation topic.

Optional Modules

All modules are core

Teaching & assessment

This MSc consists of set modules and a dissertation. Teaching follows several different complementary models: face-to-face, online, pre-recorded, workshops, presentations, practical sessions, labs. Assessments cover a variety of activities: groupwork, presentations, reports, Moodle quizzes, etc. Across the four MScs, examples and case-studies are international and cover many different backgrounds. Modules feature built-in formative assessments (e.g. Moodle quizzes, workshops, presentations) that complement and lead up to summative assessment.

Students have a close relationship with their tutors, and with the teaching staff in general, which means they have many opportunities for feedback. They receive oral feedback in workshops, presentations, practical sessions, and labs.

Entry requirements

2:2

A relevant Technology, Computing, Power, or Systems Engineering background

International & EU requirements

English language requirements

MSc Smart Power Systems requires:

IELTS: 6.5 overall. No subscore lower than 5.5.
Pearson Test of English: 61 overall. No subscore lower than 51.
Trinity College London Integrated Skills in English (ISE): ISE III.
Cambridge English: Advanced (CAE) grade C.
TOEFL iBT: 88 overall, with Reading 18 Listening 17 Speaking 20 Writing 17.
Duolingo: 120 overall and no sub-score below 100.

Your future career

The MSc Smart Power Systems course is designed to equip you with relevant technical skills relating to the planning, operations and control of modern electricity networks. Our modules are tailored to expose you to trends in the electric power industry and include state-of-the-arts smart grid concepts and technologies like smart meters, energy storage, flexibility services, renewable energy sources and modern electricity network planning and operations.

You will also develop employability skills such as project management, data analysis, presentation, communication, negotiation, technical writing, etc.

Upon the completion of the course, possible future career roles will include:

Smart Grid Engineer
Renewable Energy Engineer
Electrical Design Engineer
Power Systems Planning Engineer
Power Systems Consultant etc.

We look forward to finding out about the exciting path you will chose for your future and supporting you on your journey.

Fees, funding & scholarships

Home (UK) students tuition fee per year*: £14,400

EU and international students tuition fee per year**: £26,100

Other essential costs***: There are no single associated costs greater than £50 per item on this course.

How do I pay for it? Find out more about funding options, including loans, grants, scholarships and bursaries.

* and ** These tuition fees apply to students enrolled on a full-time basis in the academic year 2025/26. Students studying on the standard part-time course structure over two years are charged 50% of the full-time applicable fee for each study year.

Royal Holloway reserves the right to increase all postgraduate tuition fees annually. Be aware that tuition fees can rise during your degree (if longer than one year’s duration), and that this also means that the overall cost of studying the course part-time will be slightly higher than studying it full-time in one year. The annual increase for continuing students who start their degree in 2025/26 will be 5%.  For further information, see the  fees and funding , and terms and conditions.

** This figure is the fee for EU and international students starting a degree in the academic year 2025/26. Find out more

*** These estimated costs relate to studying this particular degree at Royal Holloway during the 2025/26 academic year, and are included as a guide. Costs, such as accommodation, food, books and other learning materials and printing, have not been included.