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Viewing: ECE 753 : Computational Methods for Power Systems

Last approved: Fri, 28 Apr 2017 08:02:48 GMT

Last edit: Thu, 27 Apr 2017 20:20:50 GMT

Change Type
Major
ECE (Electrical and Computer Engineering)
753
006314
Dual-Level Course
Cross-listed Course
No
Computational Methods for Power Systems
Comp Methods for Power Systems
College of Engineering
Electrical & Computer Engineering (14ECE)
Term Offering
Spring Only
Offered Every Year
Spring 2018
Previously taught as Special Topics?
Yes
4
 
Course Prefix/NumberSemester/Term OfferedEnrollment
ECE792-0192013/spring14
ECE792-0192014/spring21
ECE792-0192015/spring12
ECE792-0192016/fall24
Course Delivery
Face-to-Face (On Campus)

Grading Method
Graded/Audit
3
15
Contact Hours
(Per Week)
Component TypeContact Hours
Lecture3
Course Attribute(s)


If your course includes any of the following competencies, check all that apply.
University Competencies

Course Is Repeatable for Credit
No
 
 
Ning Lu
Dr.
assoc

Open when course_delivery = campus OR course_delivery = blended OR course_delivery = flip
Enrollment ComponentPer SemesterPer SectionMultiple Sections?Comments
Lecture1515NoThe enrollment is between 15-20. This course is an elective for EPSE students
Open when course_delivery = distance OR course_delivery = online OR course_delivery = remote
Prerequisite: ECE 451 or ECE 550

Is the course required or an elective for a Curriculum?
Yes
SIS Program CodeProgram TitleRequired or Elective?
14EPSEMSEPSEElective
This course is designed to introduce computational methods used for power grid operation and planning. The course will help students understand the various computational methods that form the basis of major commercial software packages used by grid analysts and operators. Students are expected to have some basic understanding of principles of power system analysis including power system models, power flow calculation, economic dispatch, reliable and stability analysis. The course covers the following computational methods commonly used in power grid operation and planning: Locational Marginal Pricing Schemes, Game Theory, Unconstrained Optimization, Linear Programming, Non-linear Constrained Optimization, and Forecasting Methods.

1) This course is an elective course for the Master of Science in Electric Power Systems Engineering program.


2) This course introduces the algorithms used for power grid operation and planning.  Two software packages are used: Powerworld and GAMS.  It is the only course that systematically introduces the market-based grid operation, forecasting, and optimization algorithms commonly used in power system applications.


No

Is this a GEP Course?
GEP Categories

Humanities Open when gep_category = HUM
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Mathematical Sciences Open when gep_category = MATH
Each course in the Mathematial Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Natural Sciences Open when gep_category = NATSCI
Each course in the Natural Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Social Sciences Open when gep_category = SOCSCI
Each course in the Social Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Interdisciplinary Perspectives Open when gep_category = INTERDISC
Each course in the Interdisciplinary Perspectives category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Visual & Performing Arts Open when gep_category = VPA
Each course in the Visual and Performing Arts category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Health and Exercise Studies Open when gep_category = HES
Each course in the Health and Exercise Studies category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
&
 

 
 

 
 

 
 

Global Knowledge Open when gep_category = GLOBAL
Each course in the Global Knowledge category of the General Education Program will provide instruction and guidance that help students to achieve objective #1 plus at least one of objectives 2, 3, and 4:
 
 

 
 

 
Please complete at least 1 of the following student objectives.
 

 
 

 
 

 
 

 
 

 
 

US Diversity Open when gep_category = USDIV
Each course in the US Diversity category of the General Education Program will provide instruction and guidance that help students to achieve at least 2 of the following objectives:
Please complete at least 2 of the following student objectives.
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Requisites and Scheduling
 
a. If seats are restricted, describe the restrictions being applied.
 

 
b. Is this restriction listed in the course catalog description for the course?
 

 
List all course pre-requisites, co-requisites, and restrictive statements (ex: Jr standing; Chemistry majors only). If none, state none.
 

 
List any discipline specific background or skills that a student is expected to have prior to taking this course. If none, state none. (ex: ability to analyze historical text; prepare a lesson plan)
 

Additional Information
Complete the following 3 questions or attach a syllabus that includes this information. If a 400-level or dual level course, a syllabus is required.
 
Title and author of any required text or publications.
 

 
Major topics to be covered and required readings including laboratory and studio topics.
 

 
List any required field trips, out of class activities, and/or guest speakers.
 

1) Commercial software package: Powerworld, MATLAB, and GAMS
2) Play in-class bidding games

This course teaches graduate students game theory, optimization and forecasting algorithms with a focus on their applications on power grid operation and planning.  The students will learn to use tools such as the MATLAB optimization toolbox to implement those algorithms. A few commercial software packages will also be introduced to let student learn how industry will apply these computational methods to solve real world problems.


Student Learning Outcomes

Upon completion of this course, students will be able to:



  • Develop basic understanding on the operation mechanism of deregulated electricity markets

    • Locational Marginal Pricing Schemes

    • Generator and Load gaming behaviors and their impacts on the market price and grid operation



  • Develop computer programs (Tools: MATLAB, PowerWorld) to perform unit commitment and economic dispatch

    • Optimization methods for solving unit commitment and economic dispatch problems

    • Stochastic models for power system loads, wind, and solar generation resources



  • Develop computer programs (Tools: MATLAB, PowerWorld) to solve power flow problems

    • Decoupled Power Flow, Fast Decoupled Power Flow, DC Power Flow

    • Optimal power flow



  • Develop computer programs (Tool: MATLAB) for using numerical methods to conduct transient stability analysis

    • PMU Data Analysis

    • Smart Meter Data Analysis




Evaluation MethodWeighting/Points for EachDetails
Midterm24A midterm covers the first half of the learning material as highlighted in the syllabus
Final Exam40The final exam covers the second half of the learning materials as well as some key learning points in the first half of the learning material.
Project20Class project will be modeling a market-based grid operation. Students will consider the impact of renewable integration.
Homework16There will be 7 or 8 homeworks. Students will be using Powerworld, MATLAB, GAMS to implement different algorithms learnt in the class.
TopicTime Devoted to Each TopicActivity
n/an/an/a
mlnosbis 1/13/2017: 1) Rewrite learning outcomes without the word "understand" as directed in the Learning Outcomes Guidelines. 2) Syllabus needs improvement on the following items from the Graduate Syllabus Checklist: 1 (office hours), 4 (cost of textbooks), 10 (how grades are determined), 12 (attendance policy for non-exam days), 14 (general PRR statement).

pjharrie 1/19/2017: As this appears to be a master's level course based on what's written, why isn't a 500-level course. Also, MATLAB is a primary component of the course objective, but isn't discussed at all in the course description. That should be better balanced. Syllabus still does not adequately address items listed above in comment from 1/13/2017.

mlnosbis 2/15/2017: syllabus has been updated.

pjharrie 3/2/2017: The contact hours is only for one lecture a week - it seems, though, that the class meets twice, so that should be fixed. UPDATED.

ABGS Reviewer Comments:
- Abbreviated title got mangled (trivial repair)
- Some items previously requested by Peter Harries have not been addressed: 500 vs 700 level;
-learning outcomes on CIM have not been updated (they are fine in the syllabus) RESOLVED
-I don't understand the formatting of the learning outcomes and it appears that they have not addressed previous recommendations. I would say that the learning outcomes need to be revised at a minimum. RESOLVED

Pjharrie - 3/23/2017 - still don't see the issues have been addressed here as outlined above in various comments
nlu2 (Mon, 27 Mar 2017 17:29:17 GMT): Ning LU: Response to the comments: I have made some changes to address the comments. I am not sure why the reviewers feel that the course is not a 700-level course and what makes them think the content seems to be master's level . Please elaborate. I think teaching theory and applications of Game Theory, linear and non-linear optimization algorithms, as well as a variety of forecasting algorithms make the course content qualified for 700 materials. The course description is attached here for your reference: This course is designed to introduce computational methods used for power grid operation and planning. The course will help students understand the various computational methods that form the basis of major commercial software packages used by grid analysts and operators. Students are expected to have some basic understanding of principles of power system analysis including power system models, power flow calculation, economic dispatch, reliable and stability analysis. The course covers the following computational methods commonly used in power grid operation and planning: Locational Marginal Pricing Schemes, Game Theory, Unconstrained Optimization, Linear Programming, Non-linear Constrained Optimization, and Forecasting Methods.
Key: 11933