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Master of Science in Power Engineering
2023-08-12 15:39:41 点击量：
| 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 and Planning | Forecasting and Scheduling. Network Application Functions. Probability and Reliability. Generation and Transmission Planning. | 3 |
| EE6511 | Power System Modelling and Control | Steady-state Power System Networks. Network Components. Stability Analysis. Power System Control. | 3 |
| 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 and 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 and 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 and Design | Basic control algorithms. Model Predictive Control. Multivariable control. Plant parameter estimation. Case studies in process control. | 3 |
| EE6227 | Genetic Algorithms and 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 |
| 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 |
| 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 |
| EE6508 | Power Quality | Concept of Power Quality. Voltage Fluctuations and Variations. Transient Over-voltages. Harmonic Distortions. | 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 |
| EE7207 | Neural and Fuzzy Systems | Introduction to artificial neural networks. Recurrent and Hopfield Neural Network. Multi-layer perception neural network. Radial basis function neural network. Support vector machines. Self-organizing map neural network. Applications of neural network. Fundamentals of fuzzy logic and fuzzy systems. Takagi-Sugeno (T-S) fuzzy modelling and identification. Stability analysis of fuzzy systems. Applications of fuzzy systems. | 3 |
Note: the above curriculum is subject to change.
