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power-systems-optimization

Power systems optimization course materials

https://github.com/power-systems-optimization-course/power-systems-optimization

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Power systems optimization course materials

Basic Info
  • Host: GitHub
  • Owner: Power-Systems-Optimization-Course
  • License: other
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 32.1 MB
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  • Stars: 206
  • Watchers: 11
  • Forks: 119
  • Open Issues: 3
  • Releases: 0
Created almost 6 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

Power Systems Optimization

License: CC BY 4.0 License: MIT Binder

These course materials are jointly developed by Michael Davidson and Jesse Jenkins for introducing constrained optimization models applied to power systems. The materials will be used for: - MAE / ENE 539 Optimization Methods for Energy Systems Engineering (Advanced Topics in Combustion I) [Princeton] - MAE 243 Electric Power Systems Modeling [UC San Diego]

Description

This course will teach students constrained optimization problems and associated solution methods, how to implement and apply linear and mixed integer linear programs to solve such problems using Julia/JuMP, and the practical application of such techniques in energy systems engineering.

The course will first introduce students to the theory and mathematics of constrained optimization problems and provide a brief introduction to linear programming, including problem formation and solution algorithms.

Next, to build hands-on experience with optimization methods for energy systems engineering, the course will introduce students to several canonical problems in electric power systems planning and operations, including: economic dispatch, unit commitment, optimal network power flow, and capacity planning.

Finally, several datasets of realistic power systems are provided which students will use in conjunction with building a model for a course project that answers a specific power systems question.

Notebooks

  1. Constrained Optimization

  2. Using Julia and JuMP for Constrained Optimization

  3. Basic Capacity Expansion Planning

  4. Economic Dispatch

  5. Unit Commitment

  6. DC Optimal Network Power Flow

  7. Complex Capacity Expansion Planning

Homeworks

  1. Homework 1 - Building Your First Model

  2. Homework 2 - Basic Capacity Expansion

  3. Homework 3 - Unit Commitment

  4. Homework 4 - Optimal Power Flow

  5. Homework 5 - Complex Capacity Expansion

Project

Project dataset descriptions

  1. ERCOT 120-bus 500kV simulated system for optimal power flow and economic dispatch problems

  2. ERCOT 3-zone 2040 brownfield expansion system for capacity expansion planning problems - (See Notebook 7 for description)

  3. WECC 6-zone 2045 brownfield expansion system w/100% clean resources for capacity planning problems

  4. WECC 12-zone 2020 current capacity for unit commitment and economic dispatch problems

Tutorials

  1. Julia Tutorial

  2. JuMP: Diagnosing infeasible models

  3. Debugging a Julia script with VS Code

License and copyright

If you would like to use these materials, please see the license and copyright page.

Owner

  • Name: Power-Systems-Optimization-Course
  • Login: Power-Systems-Optimization-Course
  • Kind: organization

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Jesse Jenkins j****s@g****m 81
Michael Davidson m****n@u****u 39
Gabe Mantegna g****a@p****u 11
lbonaldo b****2@g****m 5
Filippo Pecci p****o@g****m 1
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