Course Structure Overview
The Power Systems program at Thdc Institute Of Hydro Power Engineering And Technology is structured over eight semesters, ensuring a progressive and comprehensive learning experience. The curriculum balances foundational science courses with core engineering principles and specialized electives that prepare students for advanced careers in power systems.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | PHYS101 | Physics for Electrical Engineering | 3-1-0-4 | - |
| 1 | MATH101 | Calculus and Differential Equations | 3-0-0-3 | - |
| 1 | MATH102 | Linear Algebra and Numerical Methods | 3-0-0-3 | - |
| 1 | CSE101 | Introduction to Programming | 2-0-2-3 | - |
| 1 | EE101 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | ENG101 | English for Technical Communication | 2-0-0-2 | - |
| 2 | MATH201 | Probability and Statistics | 3-0-0-3 | MATH101 |
| 2 | PHYS201 | Electromagnetic Fields | 3-1-0-4 | PHYS101 |
| 2 | EE201 | Circuit Analysis | 3-1-0-4 | EE101 |
| 2 | EE202 | Signals and Systems | 3-1-0-4 | MATH101, EE101 |
| 2 | EE203 | Electric Machines | 3-1-0-4 | EE101 |
| 2 | EE204 | Power Electronics | 3-1-0-4 | EE201, EE203 |
| 3 | EE301 | Power System Analysis | 3-1-0-4 | EE201, EE202 |
| 3 | EE302 | Transmission Line Theory | 3-1-0-4 | EE201 |
| 3 | EE303 | Distribution Systems | 3-1-0-4 | EE301 |
| 3 | EE304 | Control Systems | 3-1-0-4 | MATH201, EE202 |
| 3 | EE305 | Renewable Energy Systems | 3-1-0-4 | EE203, EE301 |
| 3 | EE306 | Energy Management Systems | 3-1-0-4 | EE301, EE303 |
| 4 | EE401 | Smart Grid Technologies | 3-1-0-4 | EE301, EE302 |
| 4 | EE402 | Power System Protection | 3-1-0-4 | EE301 |
| 4 | EE403 | Grid Stability and Reliability | 3-1-0-4 | EE301, EE304 |
| 4 | EE404 | Distributed Generation | 3-1-0-4 | EE301, EE305 |
| 4 | EE405 | Power System Economics | 3-1-0-4 | EE301 |
| 4 | EE406 | Energy Storage Systems | 3-1-0-4 | EE204, EE305 |
| 5 | EE501 | Advanced Power System Analysis | 3-1-0-4 | EE301 |
| 5 | EE502 | Power Quality Improvement | 3-1-0-4 | EE301 |
| 5 | EE503 | Cybersecurity in Smart Grids | 3-1-0-4 | EE401 |
| 5 | EE504 | Power System Planning and Operation | 3-1-0-4 | EE301, EE303 |
| 5 | EE505 | Renewable Energy Forecasting | 3-1-0-4 | EE305 |
| 5 | EE506 | Electrification of Transportation | 3-1-0-4 | EE204, EE305 |
| 6 | EE601 | Research Methodology | 2-0-2-3 | - |
| 6 | EE602 | Project Development and Management | 2-0-2-3 | - |
| 6 | EE603 | Mini Project I | 0-0-6-3 | - |
| 6 | EE604 | Mini Project II | 0-0-6-3 | - |
| 7 | EE701 | Final Year Thesis/Capstone Project | 0-0-12-6 | - |
| 8 | EE801 | Internship | 0-0-12-6 | - |
Detailed Course Descriptions
The department emphasizes a project-based learning approach to ensure students gain practical experience alongside theoretical knowledge. Students engage in hands-on experiments, simulations, and real-world problem-solving exercises throughout their academic journey.
Advanced departmental elective courses are designed to deepen understanding of specialized areas within power systems:
- Advanced Power System Analysis: This course covers modern techniques for analyzing complex power systems including load flow studies, short circuit analysis, and stability assessment methods. Students learn to use industry-standard software tools like MATLAB/Simulink and ETAP for system modeling and simulation.
- Power Quality Improvement: Focuses on identifying and mitigating power quality issues such as harmonics, voltage fluctuations, and flicker. Students explore filtering techniques, reactive power compensation, and compliance with international standards like IEEE 519.
- Cybersecurity in Smart Grids: Explores vulnerabilities in smart grid infrastructure and defensive strategies against cyber threats. Topics include intrusion detection systems, secure communication protocols, and regulatory frameworks for critical infrastructure protection.
- Power System Planning and Operation: Teaches students how to plan, design, and operate power systems efficiently under varying load conditions. The course includes optimization techniques, economic dispatch, and environmental impact assessments.
- Renewable Energy Forecasting: Provides insights into predicting renewable energy generation using statistical models and machine learning algorithms. Students learn to process large datasets, validate forecasting accuracy, and integrate forecasts into power system operations.
- Electrification of Transportation: Examines the challenges and opportunities associated with electric vehicle adoption. The course covers charging infrastructure planning, grid impact analysis, and policy frameworks supporting electrified transportation.
- Smart Grid Technologies: Introduces students to smart meters, demand response programs, and automated control systems that enhance grid efficiency and reliability. The curriculum includes hands-on lab sessions using real-time simulation platforms.
- Power System Protection: Focuses on designing and implementing protection schemes for power system components. Students study relay coordination, fault analysis, and modern protection relays used in utility networks.
- Grid Stability and Reliability: Analyzes factors affecting grid stability including transient response, frequency regulation, and voltage control. The course emphasizes preventive measures and post-fault recovery strategies.
- Distributed Generation: Explores the integration of small-scale generation units into existing power networks. Topics include microgrids, community energy projects, and interconnection standards for distributed resources.
- Power System Economics: Combines engineering principles with economic analysis to evaluate cost-effective power system designs. Students learn about pricing mechanisms, market structures, and regulatory policies influencing power generation and distribution.
- Energy Storage Systems: Investigates various energy storage technologies including batteries, pumped hydro, compressed air, and supercapacitors. The course covers design considerations, performance characteristics, and applications in grid-scale energy storage.
Project-Based Learning Approach
The department's philosophy on project-based learning emphasizes experiential education that bridges the gap between theory and practice. From early semesters, students are encouraged to participate in lab-based projects and mini-projects that reinforce classroom learning.
Mini-projects begin in the sixth semester and involve working on real-world problems under faculty supervision. These projects typically last 3-4 months and require students to apply concepts learned in earlier courses to solve practical engineering challenges.
The final-year thesis/capstone project is a significant component of the program. Students select topics aligned with their interests or industry needs, often collaborating with faculty members who provide mentorship and guidance. The project involves extensive literature review, experimental design, data analysis, and presentation skills development.
Project selection is guided by student preferences, faculty expertise, and current industry trends. Faculty mentors are assigned based on subject matter expertise and availability, ensuring that students receive appropriate support throughout their project journey.