Distributed Energy Resources

Distributed energy resources (DERs) are controllable electrical devices that plug in at the edge of the power grid, typically through buildings. DERs - such as electric vehicles, heating and cooling equipment, energy storage systems, and rooftop solar photovoltaics - will play an increasingly important role in future energy systems that decarbonize, digitalize, and decentralize their operations. In this class, students will learn to model a variety of DERs, optimize DER designs, and control DERs to reduce costs, pollutant emissions, and impacts on the power grid. This class will involve a mix of coding and mathematical analysis. Students will do semester projects on currect DER research and development topics.

ME59700

Credit Hours:

3

Description:

Distributed energy resources (DERs) are controllable electrical devices that plug in at the edge of the power grid, typically through buildings. DERs - such as electric vehicles, heating and cooling equipment, energy storage systems, and rooftop solar photovoltaics - will play an increasingly important role in future energy systems that decarbonize, digitalize, and decentralize their operations. In this class, students will learn to model a variety of DERs, optimize DER designs, and control DERs to reduce costs, pollutant emissions, and impacts on the power grid. This class will involve a mix of coding and mathematical analysis. Students will do semester projects on current DER research and development topics.

Spring 2024 Syllabus

Topics Covered:

  • Introduction to energy systems and DERs (1 class)
  • Modeling and simulating DERs (~6 classes)
  • Optimization (~4 classes)
  • Control (~7 classes)
  • Applications (~8 classes)
  • Project presentations (~4 classes)

Prerequisites:

  • Required:  Linear algebra, ordinary differential equations, and facility with programming in a language such as Matlab, Python, or Julia
  • Not required, but may enhance appreciation: Probability, statistics, control systems, optimization, machine learning

Web Address:

https://purdue.brightspace.com

 

Homework:

 Homework: 20%

  • Homework, the exam, and final projects will involve some mathematical analysis and a lot of coding
  • Code can be written in Matlab, Python, or Julia, but the course staff will only support Matlab
  • Students are encouraged to work together on homework, but each student must submit their own solutions
  • The TA(s) will grade homework quickly on a three-tier scale (full, half, or zero credit) based on how much of the solution is present, clear, and correct

Projects:

Final project: 50%

  • Students can do projects individually or in teams of two to five
  • Each team will submit one final project report, written in LATEX in conference paper format
  • Each team will give one final project presentation, formatted like a conference talk
  • Only one student from each team should present, but the whole team should help them prepare
  • Teams of online students may pre-record video presentations or present during class via Zoom
  • Each student will assess their contributions to their project in a final meeting with instructor and their team

Exams:

 Take-home exam: 30%

  • Each student will individually take a 24-hour take-home exam about halfway through the semester

Textbooks:

None. 

Lecture slides, videos, and sample code will be posted online. 

 

Instructor(s)

Kevin Kircher

Email
kircher@purdue.edu