M5 - Distributed Energy Resources & Economics of Energy Storage
Learning Objectives
In this module we will talk about distributed energy resources with focus on electrical energy storage (EES). The learning outcomes of this module are:
- Understand the multi-service storage can provide to power systems;
- Overview of common EES technologies and existing facilities in US and other countries;
- Overview of energy storage perspective and projections;
- Introduction to operations research and mathematical models with focus on linear programming (LP);
- Learn how to solve LP models in Python using PYOMO library (or R using lpsolve).
Slides
Here is a link to the slide deck used in class.
Resources
And here are additional resources and readings for energy storage.
- 50 States of Grid Modernization
- Overview of current development in electrical energy storage
- Long Duration Energy Storage
Recordings on Linear Programming
- Intro to Operations Research and Linear Programming recording.
- Linear Programming in R with lpsolve recording.
- Linear Programming in Python with Pyomo recording
For more information on LPs and the water heater/chemical solution example, please refer to the additional slides on linear programming linked below. You do not need to worry about the graphical solution since we will use computer solvers to solve our models.
Instructions on how to get Google Colab set up on your machine available here. The script in Python created in the video is available in the link. You may also open the html version of the script here.
The script in R created in the video is available for download here.
Topics for Discussion/Reflection
Deliverables
For this module you will complete Assignment 2. The due date for A2 is Friday Oct 13th.