| 1. |
EE5104 |
Renewable Energy Integration ▼
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3 |
0 |
0 |
3 |
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Course Number
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EE5104
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Course Credit (L-T-P-C)
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3-0-0-3
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Course Title
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Renewable Energy Integration
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Learning Mode
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Lecture
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Learning Objectives
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Complies with Program goals 1, 2 and 3
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Course Description
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The course is designed to meet the requirements of M. Tech. The course aims at giving a broad overview of renewable energy grid integration with emphasis on the power electronics, policy, regulation and control.
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Course Outline
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Policy and Regulation, Modeling of Variable energy resources, Variable energy resources in power system, forecasting renewable energy
Connecting renewable energy to power grids, System flexibility, demand response and distributed energy resources
Variable energy resources in island power system, Solar, Wind, Tidal and Wave energy integration
Power Electronics for grid integration: DC-DC converter, DC-AC converter, Filter Design, Parallel Inverter etc.
Enabling and disruptive technologies for grid integration
DC distribution system and microgrids: Concept of DC distribution, Power electronic, DC distribution standard, grid integration etc.
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Learning Outcomes
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Complies with PLO 1a, 2a and 3a
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Assessment Method
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Quizzes/Assignments, Mid Sem, and End Sem
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Suggested reading
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Textbooks:
1. Robert Ericson, Fundamentals of Power Electronics, Chapman & Hall, 2004.
1. Lawerence E Jones, Renewable Energy Integration, Science Direct, 2014.
2. Moreno-Munoz, Antonio. Large scale grid integration of renewable energy sources. No. 137837. IET, 2017.
3. Fox, Brendan. Wind power integration: connection and system operational aspects. Vol. 50. Iet, 2007.
4. Dragicevic, Tomislav, Patrick Wheeler, and Frede Blaabjerg. DC distribution systems and microgrids. Institution of Engineering and Technology, 2018.
5. Jamil, Majid, M. Rizwan, and D. P. Kothari. Grid Integration of Solar Photovoltaic Systems. CRC Press, 2017.
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| 2. |
EE6101 |
Advanced Power System Reliability ▼
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3 |
0 |
0 |
3 |
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Course Number
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EE6101
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Course Credit (L-T-P-C)
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3-0-0-3
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Course Title
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Advanced Power System Reliability
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Learning Mode
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Lectures
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Learning Objectives
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Complies with Program Goals 1 and 2
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Course Description
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The course is designed to meet the requirements of Ph.D. and M. Tech. The course aims at giving a broad overview of power system reliability at an advanced level.
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Course Outline
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Basic Probability Theory: Probability concepts, rules for combining probability, probability distributions, random variables, density and distribution functions, mathematical expectations, variance and standard deviation.
Basic Reliability Evaluation: General reliability functions, probability distributions in reliability evaluation, network modeling and evaluation of series, parallel, series –parallel, network modeling and evaluation of complex systems, cut-set method, tie-set method, discrete Markov chains, continuous Markov process, frequency and duration technique concepts, application to multi-state problems, approximate system reliability evaluation.
Generation System Reliability: Generation system models, capacity outage table, recursive algorithm, loss of load indices, inclusion of scheduled outages, load forecast uncertainty, loss of energy indices, expected energy generation, energy limited systems, Gram-Charlier series and its application to generation system reliability evaluation, generating capacity –frequency and duration method.
Interconnected System: Probability array method in two interconnected systems, effect of tie capacity, tie reliability and number of tie lines, equivalent assistance unit method for reliability evaluation of inter-connected system, elementary concepts for reliability evaluation of multi-connected systems.
Composite Generation and Transmission System Reliability: Radial configurations, conditional probability approach, network configuration, state selection, system and load point indices.
Distribution System Reliability: Basic technique and application to radial systems, customer–oriented indices, load and energy indices, effect of lateral distributor protection, effect of disconnects, effect of protection failures, effect of load transfer, meshed and parallel networks, approximate methods, failure modes and effects analysis, inclusion of scheduled maintenance, temporary and transient failures, inclusion of weather effects.
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Learning Outcomes
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Complies with PLOs 1a, 2a, and 3a.
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Assessment Method
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Quizzes/Assignments, Mid Sem, and End Sem
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Suggested Readings
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Texts/References:
1. Reliability Evaluation of Power systems by R. Billinton, R.N.Allan, BS Publications, 2007.
2. Reliability Evaluation of Engineering Systems Concepts and Techniques by R. Billinton, R.N.Allan, Kluwer Academic, 1992
3. Reliability Modeling in Electric Power Systems by J. Endrenyi, John Wiley and Sons, 1978
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| 3. |
EE6102 |
Advanced State Estimation and Target Tracking ▼
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3 |
0 |
0 |
3 |
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Course Number
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EE6102
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Course Credit (L-T-P-C)
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3-0-0-3
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Course Title
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Advanced State Estimation and Target Tracking
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Learning Mode
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Lectures
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Learning Objectives
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Complies with Program Objectives 1 and 2.
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Course Description
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This course will help students learn the theoretical aspects of discrete-time stochastic estimators and filters with target-tracking applications. The interest of the course will cover tracking of a single target as well as multiple targets.
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Course Outline
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Basic Concept of Estimation: Introduction, maximum likelihood and maximum a posteriori estimation, least square and minimum mean square error estimation, Fisher information matrix, Cramer-Rao lower bounds.
State Estimation Methods: Principle of Bayesian estimation, recursive state estimation and filtering, filtering with linear Gaussian systems (the Kalman filter), extended Kalman filter, unscented / sigma point Kalman filtering, cubature Kalman filter, sequential importance sampling, resampling strategy, sampling importance resampling (SIR) filter, particle filtering, Rao–Blackwellization.
Tracking a Single Target: Maneuvering models, multiple model filtering techniques, tracking a single target in clutter, probabilistic data association (PDA).
Tracking Multiple Targets: Multiple targets in clutter, joint probabilistic data association (JPDA), multiple hypothesis tracking (MHT), track-to-track fusion with and without memory, track-to-track association, covariance intersection.
Tracking with Multiple Sensors: multi-sensor tracking of a maneuvering target in clutter, multi-sensor tracking configuration, multi-sensor multi-target data association.
A case study: Multi-sensor air traffic surveillance.
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Learning Outcomes
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Complies with PLOs 1a, 2a, and 3a
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Assessment Method
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Quizzes/Assignments, Mid Sem, and End Sem
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Suggested Readings
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Text/References
1. B. Ristic, S. Arulumpalam, N. Gordon, Beyond the Kalman Filter: Particle Filters for Tracking Applications, Artech House Radar Library, 2004.
2. Y. B. Shalom, and X. R. Li. Multitarget-multisensor tracking: principles and techniques. Vol. 19, 1995.
3. Bar-Shalom, Yaakov, X. Rong Li, and Thiagalingam Kirubarajan. Estimation with applications to tracking and navigation: theory algorithms and software. John Wiley & Sons, 2004.
4. Shovan Bhaumik and Paresh Date, Nonlinear Estimation: Methods and Applications with Deterministic Sample Points, CRC Press, 2019
5. Jia, Bin, and Ming Xin. Grid-based nonlinear estimation and its applications. CRC Press, 2019.
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| 4. |
EE6103 |
Multivariable Control System ▼
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3 |
0 |
0 |
3 |
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Course Number
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EE6103
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Course Credit (L-T-P-C)
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3-0-0-3
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Course Title
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Multivariable Control System
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Learning Mode
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Lectures
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Learning Objectives
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Complies with Program goals 1 and 2
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Course Description
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This course will help students learn the theoretical aspects of dynamical systems in State-Space framework and properties of systems such as Controllability and Observability. Further, State-feedback control, Output feedback control and LQR, Robust Stability will be covered.
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Course Outline
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State-space dynamic systems (continuous-time): Introduction to LTI state-space models, Four canonical forms for LTI state-space models, One more canonical form, transformations, Time (dynamic) response, Balanced Realization, Diagonalizing the A matrix, The Jordan canonical form; MIMO canonical forms, Zeros of a state-space system, Linear time-varying systems, What about nonlinear systems? The z transform, Working with the z transform, Discrete-time state-space form, More on discrete-time state-space models, Linear time-varying and nonlinear discrete-time systems.
Stability: Vector norms and quadratic forms, Matrix gain, Lyapunov stability, Proof of the Lyapunov stability theorem, Discrete-time Lyapunov stability, Stability of locally linearized systems, Input-output stability, LTV case, Input-output stability, LTI case
Observability and controllability: Continuous-time observability: Where am I?, Continuous-time controllability: Can I get there from here?, Discrete-time controllability and observability, Cayley-Hamilton theorem, Continuous-time Gramians, Discrete-time Gramians, Computing transformation matrices, Canonical (Kalman) decompositions, PBH controllability/observability tests, Minimal realizations: Why not controllable/observable ?
State-feedback control: Bass-Gura pole placement, Ackermann's formula, Reference input, Pole placement, Integral control for continuous-time systems, State feedback for discrete-time systems, MIMO control design
Output-feedback control: Open-loop and closed-loop estimators, The observer gain design problem, Discrete-time prediction estimator, Compensation design: Separation principle, The compensator, continuous- and discrete-time, Current estimator/compensator, Compensator design using current estimator, Discrete-time reduced-order estimator, Discrete-time reduced-order prediction compensator, Continuous-time reduced-order estimator, Estimator pole placement
Linear quadratic regulator: Introduction to optimal control, Dynamic programming: Bellman's principle of optimality, The discrete-time LQR problem, Infinite-horizon discrete-time LQR, The continuous-time LQR problem, Solving the differential Riccati equation via simulation, Continuous-time systems and Chang-Letov Method.
Robust stability and performance analysis for MIMO systems: General control configuration with uncertainty, Representing uncertainty, Obtaining P, N and M, Robust stability of the M -structure, Robust stability for complex unstructured uncertainty, Robust stability with structured uncertainty, Robust Performance
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Learning Outcomes
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Complies with PLO 1a, 2a, 3a
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Assessment Method
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Quizzes, Assignments, Exams
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Suggested Readings
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1. S. Skogestad and I. Postlethwaite, Multivariable Feedback Control: Analysis and Design, John Wiley & Sons, 2nd Edition, 2005
2. J.M. Maciejowski, Multivariable Feedback Design, Addison-Wesley, 1st Edition, 1989
3. J.P. Hespanha, Linear Systems Theory, Princeton University Press, 2nd Edition, 2018
4. L. A. Zadeh and C. A. Desoer, Linear System Theory: The State Space Approach, Springer-Verlag, 2008.
5. W. Rugh, Linear System Theory, Prentice Hall, 2nd Edition, 1995.
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| 5. |
EC6105 |
CMOS Phase Locked Loops ▼
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3 |
0 |
0 |
3 |
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Course Number
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EC6105
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Course Credit (L-T-P-C)
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3-0-0-3
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Course Title
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CMOS Phase-Locked Loops
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Learning Mode
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Lectures
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Learning Objectives
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Complies with Program Goals 1 and 2
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Course Description
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CMOS Phase-Locked Loops (PLLs) involve the design and implementation of frequency synthesis circuits using Complementary Metal-Oxide-Semiconductor (CMOS) technology. The course covers topics such as PLL architecture, phase detection and comparison, loop filter design, voltage-controlled oscillator (VCO) characteristics, and applications in clock generation, frequency synthesis, and communication systems.
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Course Outline
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Introduction to PLL, Various types of PLL
PLL building blocks: Phase detectors, Phase/Frequency detectors, Ring and LC Voltage-controlled Oscillators (VCO), Frequency Dividers
Analysis of PLL: Type-I and Type-II 2nd order PLL; Higher-order loop filters and PLL; PLL Stability
Designing PLL: a 2nd order PLL
Jitter and Phase noise in Oscillators and PLLs,
PLL-based frequency synthesizer: Integer-N and Fractional-N synthesizers, Δ∑ Fractional-N synthesizers
All-Digital PLL: Time-to-Digital Conversion, Digital Filters, Digitally Controlled Oscillators,
Delay-locked Loops
Low jitter frequency synthesizer: Subsampling PLL Architecture and it components
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Learning Outcomes
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Complies with PLOs 1a, 1b, 2 and 3a
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Assessment Method
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Quizzes/Assignments, Mid Sem, and End Sem
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Suggested Readings
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Text/References
1. B. Razavi, “Design of CMOS Phase-Locked Loops” Cambridge Univ Press, 2020.
2. William F Egan, “Phase-lock Basics,” IEEE-Wiley
3. Floyd M. Gardner, “Phase Lock Techniques” 3rd Edition, Wiley-inter-science
4. Ronald E Best, “Phase-locked Loop, Design, Simulation and Applications”, 6th edition, McGrawHill
5. Venceslav F Kroupa, “Phase Lock Loops and Frequency Synthesis,” Wiley
6. Shanthi Pavan, Richard Schreier, “Understanding Delta-Sigma Data Converters” IEEE-Wiley
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