Smart Grid Systems (SGS)
This zipped file contains the course materials for ECE6327 Smart Grid Systems offered at the University of Houston (UH) in 2022 Spring; some modifications were made to improve the material quality before making it publicly available.
Course Description:
This course provides a comprehensive introduction to smart grid systems covering analysis and operation of the traditional power grid, the new challenges, and the emerging technologies that make the “dumb grid” become smart. This course is focused on the grid system rather than individual device; and this course is focused on the electrical system rather than the communication system. The emphasis is on smart grid analysis, operation, and management, control architecture, and software systems.
Course Scope and Specific Topics:
- Lectures 1 - 2: Course Introduction and Overview
- Lectures 3 - 4: Power Flow: AC power flow, DC power flow, & neural network based power flow
- Lecture 5: Sensitivity Factor: PTDF
- Lecture 6: AMPL Tutorial (recording available on Youtube)
- Lectures 7 - 8: Linear Programming, DCOPF
- Lecture 9: Unit Commitment
- Lecture 10: State Estimation
- Lecture 11: Cyber Security: False Data Injection Cyber-Attack and Detection
- Lectures 12 - 13: Demand Side Management
- Lectures 14 - 17: Renewable Energy: overview, wind, solar, biomass, hydro, and geothermal power; and grid integration.
- Lectures 18 - 19: Flexible Transmission: network topology control, FACTS, bus splitting, and dynamic line rating.
- Lectures 20 - 21: Energy Storage, Battery Degradation, and DER & Hydrogen
- Lectures 22 - 23: Microgrid, and Offshore Load/Power & Power-Hydrogen
- Lecture 24: Advanced Metering Infrastructure & Home Energy Management
- Lecture 25: ERCOT Grid Crisis 2021, Wholesale Power Energy Market, and LMP
Shared Contents:
- Folder “Lectures” contains all lecture source *.ppt slides and converted pdf copies.
- Folder “Assignments” contains all assignments (source files and the corresponding pdf copies): (i) 6 homework assignments, (ii) 1 discussion assignment, and (iii) the project assignment. Solutions and Exams are not included. If you are a faculty who plans to use these materials, please feel free to send me an email with your institutional email account. My contact information is listed below.
- Folder “AMPL” provides basic information and tutorial materials for AMPL.
- Folder “AMPL_codes” provides about 40 AMPL programs, including codes for tutorial-level examples and codes for course-level DCOPF, SCUC, DSM, SUC, transmission switching, FACTS, energy storage, and microgrid energy management and sizing examples that are used for the class ECE6327 Smart Grid Systems at University of Houston for 2022 Spring.
- file_List.txt lists each individual file contained in this folder including all subfolders.
Software Requirements:
This course uses Matlab and AMPL (other similar alternative tools may work as well).
Suggested Text:
Although the following book is suggested, it is no required and there is no required book for this class. Suggested book: Power Generation, Operation, and Control, 3rd edition, by Allen J. Wood, Bruce F. Wollenberg, and Gerald B. Sheblé. The UH library offers an online version - electronic copy - of this book.
Note that some of the lecture slides (particularly lectures 3-10) overlap with my other class ECE6379.
Contact:
Dr. Xingpeng Li
University of Houston
Email: xli83@central.uh.edu
Website: https://rpglab.github.io/
Acknowledgment:
A number of slides in the attached lectures are adapted from the paper presentations, oral exam presentations and unpublished work of my PhD students including Arun Venkatesh Ramesh, Mingjian Tuo, Cunzhi Zhao, Jin Lu, Thuan Pham, and Jesus Silva-Rodriguez.
Figshare:
This folder was initially uploaded on Figshare. The link is as follows: https://figshare.com/articles/online_resource/ECE6327_SmartGrid/19761268
Citation:
License:
This work is licensed under the terms of the Creative Commons Attribution 4.0 (CC BY 4.0) license.
Disclaimer:
The author doesn’t make any warranty for the accuracy, completeness, or usefulness of any information disclosed and the author assumes no liability or responsibility for any errors or omissions for the information (data/code/results etc) disclosed.