Master of Science in Power Engineering

Master (Coursework)

Programme Type

Full-time, Part-time

The MSc (Power Engineering) programme is designed for Electrical Engineering graduates who are practicing engineers, R&D managers, power system designers or industry planners. 

The MSc (Power Engineering) programme is designed for Electrical Engineering graduates who are practicing engineers, R&D managers, power system designers or industry planners who seek an in-depth understanding of power electronics and drives technology, issues of power quality, power system modeling, planning, operation and control. The programme aims to equip students to adapt to the challenging demands of modern power industries.




Have a good relevant bachelor's degree

Relevant working experience is an advantage

For applicants whose native language is not English, TOEFL/IELTS score is to be submitted with the application for admission:

         TOEFL Score (Test dates must be within 2 years or less from the date of application):

          ≥ 563 (paper-based)

          ≥ 223 (computer-based)

          ≥ 85 (internet-based)

         IELTS Score (Test date must be within 2 years or less from the date of application):

          ≥ 6.0

Applicants without TOEFL/IELTS would still be eligible to apply, but they may be subjected to an interview/test if deemed necessary by the School.

Programme Structure

There are two options of study, one with coursework and dissertation, and the other with coursework only. Each course is of 3 AUs and consists of 39 hours of lectures. Candidates who undertake a project of 6 AUs must submit a dissertation on it.

Option 1
Coursework + Dissertation

Option 2

8 courses + dissertation project
(30 AUs in total)
10 courses
(30 AUs in total)
4 specialized electives (≥ 12 AUs) 4 specialized electives ((≥ 12 AUs)
4 general electives (≤ 12 AUs)
6 general electives (≤ 18 AUs)
Dissertation (6 AUs)  

Full-time students are strongly recommended to select the dissertation option, however this option is recommended only for students with a high level of English proficiency. Students taking the dissertation option may take a longer time to complete the programme.

Note:  The programme structure will be subject to change without prior notice.



Both full-time and part-time programmes are offered (unless stated). Part-time candidates are expected to obtain permission from their employer before admission to the programme. All classes are conducted in the evenings, while examinations are conducted during office hours.

Type of Coursework Programme

Minimum Candidature

Maximum Candidature

Master of Science
1 year 3 year
Master of Science
2 year 4 year


Programme Calendar

Semester 1 August to December
Semester 2 January to May
Week 1 to 14 Lecture (Inclusive of 1-week recess)
Week 15 to 17 Examinations
Other Vacation


Graduate courses offered by Master of Science (MSc) Power Engineering:

Specialized Elective Courses (Students are required to take a min of 4 out of all the 5 specialized elective courses

Course Code Course Title Course Content AUs
 EE6501  Power Electronic Converters  Introduction. AC-to-DC Converters. DC-to-DC Converters. DC-to AC Converters. 3
EE6503  Modern Electrical Drives  Components of drives. Types of loads. Modelling of mechanical systems. Selection of drive components. Control theory and closed-loop control. Transient processes. 3
EE6509  Renewable Energy Systems In Smart Grids  Introduction to Power Systems with Distributed Generation. Distributed Generation. Energy Storage. Smart Grids. 3
EE6510  Power System Operation & Planning  Forecasting and Scheduling. Network Application Functions. Probability and Reliability. Generation and Transmission Planning. 3
EE6511  Power System Modelling & Control  Steady-state Power System Networks. Network Components. Stability Analysis. Power System Control. 3


General Elective Courses

Course Code Course Title Course Content AUs
EE6010  Project Management & Technopreneurship  Project Initiation and Planning. Project Scheduling and Implementation. Project Monitoring, Control and Evaluation. Innovation and Entrepreneurship. 3
EE6102  Cyber Security & Blockchain Technology  Cyber Security Threat Landscape, Industry 4.0 and Cyber Security, Cyber Security Education, Awareness and Compliance, Cyber Security Planning, Policies and Compliance, Cyber Security Risk Assessments and Biometric-based Security approaches, Public key Infrastructure (PKI), Web Security and role of firewalls and Intrusion Detection, Online Payment, and Cryptocurrencies. Basics of Blockchain technology, Types of blockchain Technology, Blockchain Technology Applications for Industry 4.0, use cases and real-world case studies 3
EE6203  Computer Control Systems  Discrete-time system modelling and analysis. Cascade compensation. State-space design methods. Optimal control. Design and implementation of digital controllers. 3
EE6221  Robotics & Intelligent Sensors  Overview of robotics. Motion planning and control. Mobile robots . Controller hardware/software systems. Sensor systems and integration. 3
EE6225  Multivariable Control Systems Analysis & Design  Basic control algorithms. Model Predictive Control. Multivariable control. Plant parameter estimation. Case studies in process control. 3
EE6227  Genetic Algorithms & Machine Learning  Review of Combinatorics and Probability. Introduction of Genetic Algorithms. Differential Evolution. Particle Swarm Optimization. Advanced Techniques. Principles of Machine Learning. Paradigms of Machine Learning. Kernel Methods. 3
EE6285  Computational Intelligence  Introduction to Fuzzy Logic, Introduction to Fuzzy Sets, Introduction to Fuzzy Inference Systems, Fuzzy Logic Applications, Introduction to Genetic Algorithm, Fundamental Concepts of Artificial Neural Networks and Neural Network Architectures, Neural Network Applications 3
EE6301  Smart Biosensors & Systems For Healthcare  Introduction to biosensors and healthcare; Optical biosensors-fundamentals; Optical biosensors-applications; Biomedical imaging with optical technologies; Introduction to electrical biosensors- fundamentals; Introduction to electrical biosensors- fabrications; Applications of electrical biosensor; Introduction to bio-intelligent systems; Artificial intelligence in medical sensing and imaging 3
EE6303  Electromagnetic Compatibility Design  EMC Regulatory Requirements. Non-Ideal Behaviors of Passive Components. Conducted EMI and Filter Design. Electromagnetic Shielding. Basic Grounding Concept. Crosstalk. Printed Circuit Board Layout and Radiated EMI. Electrostatic Discharge. Radio Frequency Interference. Emission and Susceptibility Measurement Methods. 3
EE6341  Advanced Analog Circuits  Low Noise Circuits, Wide-Bandwidth Amplifiers, Power Amplifiers, Active Filters, DC-DC Converters 3
EE6405  Natural Language Processing  Traditional: Bag-of-words, Preprocessing, Term weighting scheme, Feature extraction,. Topic modeling , ML classifiers and clustering methods, Evaluation Metrics, Word Embeddings
Deep Neural Networks: Graph convolutional network, Seq2Seq, Attention mechanism, Transformers and self-attention, Pretrained Language Models, Fine-tuning (hyper-parameter tuning), Applications (chatbot, machine translation, sentiment analysis, summarisation, classification, generation, auto-complete)
EE6483  Artificial Intelligence & Data Mining  Structures and Strategies for State Space Representation & Search. Heuristic Search. Data Mining Concepts and Algorithms. Classification and Prediction methods. Unsupervised Learning and Clustering Analysis. 3
EE6497  Pattern Recognition & Deep Learning  Introduction, probability review, Bayesian Inference, Mixture Models and EM Algorithm, Markov Models and Hidden Markov Models, Sampling, Markov chain Monte Carlo (MCMC), Neural Networks, Deep Learning (CNN, RNN), Training Deep Networks, Deep Network Architectures, Applications, Generative Models, Self-supervised Learning. 3
EE6506  Power Semiconductor Based Converter In Renewable Energy Systems  Module 1: Overview of power electronic circuits and semiconductor devices, Module 2: Power diodes and thyristors as switching devices, Module 3: Power transistors as switching devices 2, Module 4: Protection of devices from overheating di/dt, dv/dt, Module 5: Passive components and magnetics, Module 6: Renewable energy systems 3
EE6507  Switched Mode Power Supplies  Introduction. Basic Switched Mode Power Supplies. Advanced Switched Mode Topologies. Softswitching Converters. Synchronous Rectifier and Multi-element Converters. Control, Modelling and
EE6508  Power Quality  Concept of Power Quality. Voltage Fluctuations and Variations. Transient Over-voltages. Harmonic Distortions. 3
EE6512  High Voltage Engineering & System Protection  Computational Methods for Electric Field. Insulation Engineering. System faults. Protection of Plants
and Lines. System Aspects of Protection. 
EE6534  Modern Distribution System With Renewable Resources  Operation of distribution systems. Power quality. Solar power systems. Wind power systems. 3
EE6604  Advanced Topics In Semiconductor Devices  Bipolar transistor operating principles. Bipolar device modeling. State-of-the-art bipolar structures. MOS device operation. MOSFET modeling. MOS device scaling effects. Semiconductor memories. Semiconductor heterojunctions and devices. New devices and future trends. 3
EE7204  Linear Systems  Input/Output System Models. State Space Representation. Norms of Signals and Systems. Decomposition of Linear Time-Invariant Systems. Linear Feedback Design. Convex Optimization for Linear System Analysis and Design.  3
EE7205  Research Methods  Research Preparation and Planning. Research Sources and Review. Quantitative Methods for Data Analysis. Experimental research methods. Academic Writing & Presentation 3
EE7207  NEURAL NETWORKS AND DEEP LEARNING The key topics to be covered in the context of deep neural networks
and deep learning will encompass convolutional neural networks (CNN), modern recurrent neural
networks (RNN), the attention mechanism and the transformer, self-supervised learning, graph
neural networks, all of which represent the cutting-edge methods in the realm of deep learning. In
addition, some typical applications and advanced topics of deep learning will be introduced.
EE6008  Collaborative Research & Development Project  Project Charter, Design and prototype development, Project implementation, Testing and instrumentation, Project report, Oral presentation, Demonstration 3


Note: the above curriculum is subject to change.

Tuition Fees

Five MSc programmes (Communications Engineering, Computer Control & Automation, Electronics, Power Engineering and Signal Processing) are self-financed programmes. 

Students of these programmes are not eligible for Service Obligation/ MOE Subsidies

The tuition fees per module (3 AUs) and per dissertation (6 AUs) for admission from AY2020 onwards are shown in the table as follows: 

Singaporeans (SC) Singapore PRs (SPR) International Students (IS)
Per Module Per Dissertation^ Per Module Per Dissertation^ Per Module Per Dissertation^
S$3,270* S$6,540* S$3,815* S$7,630* S$4,360* S$8,720*
Minimum Total Programme Fee Minimum Total Programme Fee Minimum Total Programme Fee
S$32,700* S$38,150* S$43,600*

*Inclusive of 9% GST from 1 Jan 2024.

^The tuition fee for the Dissertation (6 AUs) will be twice of each module fee.

All fees listed above are in Singapore dollars (S$) and subject to annual revision by the school. The tuition fee is exclusive of living expenses and miscellaneous student fees.

The deposit fee of S$2,000 is payable upon acceptance of the offer and is non-refundable. It will be deducted from the full tuition fee.

Important Updates:

Below table for intakes starting from August 2024.

Per Course: S$4,883.20* Per Dissertation^: S$9,766.40*
Minimum Total Tuition Fees: S$48,832*
SC/SPR Incentive
All Singapore Citizens (SC) and Singapore Permanent Residents (SPR) will be eligible to receive a S$5,000 subsidy, and S$10,000 for needy SC/SPR students.
NTU Alumni Incentive
All NTU Alumni will receive 10% study incentives in the form of reduction in fees.

*Inclusive of 9% GST from 1 Jan 2024.
A Goods and Services Tax (GST) of 9% is levied on the import of goods, as well as nearly all supplies of goods and services in Singapore starting 1 Jan 2024.
A deposit fee of S$5,000 (from August 2024's intake onward) is payable upon acceptance of the offer and is non-refundable. It will be deducted from the full tuition fee.


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