Spring_ECE753

For non-NC State students who want to take our course, you will have to pay us the tuition and fees.

If you are interested in it, please contact

Dr. Linda Krute, Director

Distance Engineering Education Programs

North Carolina State University

Raleigh, NC 27695

Phone: 919.515.5440

Fax: 919.513.4623

Email: ldkrute@ncsu.edu

The course is project-based so auditing is NOT an option.

• 1. Homework folders

     • 2022: folder

     • 2021: TA/instructor; Homework

  2. Textbook:

Most of the home work assignments and the project reports will be delivered as a recorded slide show.

· Create Voice Over Power point: https://support.office.com/en-us/article/record-a-slide-show-with-narration-and-slide-timings-0b9502c6-5f6c-40ae-b1e7-e47d8741161c and convert to MP4 https://nursing.vanderbilt.edu/knowledge-base/knowledgebase/how-to-save-voppt-to-mp4/

Tips for recording:

1. Use as quiet an area as possible.

2. Avoid areas that have echo:

a. Rooms should be fairly small;

b. Sound dampening with carpeting, curtains, furniture.

3. Hardline internet connections are highly recommended, but if unavailable, a strong Wi-Fi connection should do the job.

4. A good headset with a microphone set close to your mouth BUT away from direct line of mouth to reduce “pops”. Try to avoid using default, built-in microphones on your computer, if possible.

5. Do a test recording of a couple of minutes and review the sound and picture quality, in the MP4 format, and check the bit rate before recording your entire presentation. Make adjustments as needed.

Past Courses:

• 1. 2020 ECE753

     1. synchronous zoom meeting with

1. 2020 Course Recording

   1. All 2020 lectures are recorded and posted here

   2. All marked lecture notes can be accessed here.

   3. Online students: inclassquiz

   4. All Quizes after spring break is posted here.

   5. Best homework solutions are posted here

   6. data folder

• • Class quizs: https://drive.google.com/drive/folders/1Sze1lO7NMOBiUVU_ZZvrZ9BpMS8i8Nnj

2. 2019 course recording

• 1. All 2019 lectures are recorded and posted here.

  2. All 2019 marked lecture notes can be accessed here

3. Course Note

4. Homework folder

5. Course folder

Optimization Methods:

1. Linear Programing - Simplex method

   1. Linear Programing - Interior point method

2. Non-linear Programming: Steepest descent

   2. • Khan Academy: directional derivative; formal Definition;Directional derivatives and slope (A graphical explanation, very well explained); steepest descent;

      • By Michael Zibulevsky: A more rigorous but a bit harder to understand video : Gradient descent method

      • By Chieh Wu: Gradient Descent

      • By Josh Starmer: Gradient Descent, step-by-step

• 1. Non-linear Programming: Dynamic Programming

3. Non-linear Programming: Lambta iteration

4. Iterative method for solving a equation

• 1. bi-section method

  2. Interpolation

  3. fix-step

Useful Resources:

• 1. Formulate your algorithm using correct mathematical representations

• • Arg max: https://www.youtube.com/watch?v=nZXCXZ8JpJ8

• 1. ISO

• • MISO ACE chart

1. Gradient Descent

2. Gradient Descent intuitive

3. Gradient Descent for linear regression

4. 10 Machine Learning based Products You MUST See

OPENDSS Training Materials

1. Matlab codes

2. Other Examples

3. Training Materials

Dynamic State Estimation

• 1. Kalman filter

• • Kalman filter

  • Matlab tech talk Understanding Kalman Filters, Part 1: Why Use Kalman Filters?

  • Part 2: State Observers

  • Part 3: Optimal StateEstimator

  • part 4:Optimal state estimation

  • part 5: Nonlinear State Estimation

  • Part 6: how to use Kalman filter in Simulink

  • part 7: how to use extended Kalman filter in Simulink

  • Special Topics - The Kalman Filter (1 of 55) What is a Kalman Filter?

Generative Adversarial Network

1. Dr Hung-yi Lee 李宏毅 (National Taiwan University), GAN Lecture 01; 02; 03; 04; 05

2. Examples

   • Generative Visual Manipulation on the Natural Image Manifold

     • Image Completion using GAN: 01;Globally and Locally Consistent Image Completion (SIGGRAPH 2017) Fast Forward

3. Variational AutoEncoder

Modeling System Dynamics

• 1. Online Courses

     • MIT Online Courses: Introduction to system dynamics

  2. Feedback Control of Dynamic Systems

• • Lead-lag Compensator

  • Excitation System Models

  • Matlab Excitation system models

Additional Topics to be added in future lectures

• 1. Develop a Cost-effective and Resilient Microgrids Powered by PV and Energy Storage Systems

  2. Machine-learning in Power System Load Forecasting, Modeling, and Control

  3. Smart Meter Data Analysis for Characterizing Power System Loads and Analyzing Utility Revenue Shifts