Skip to content

Final Project for AA 228: Decision-Making under Uncertainty: Decision-Making Towards a Multi-Use Framework for Grid-Scale Energy Storage

License

Notifications You must be signed in to change notification settings

kevinrussellmoy/aa-228-final-project

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

30 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Decision-Making Towards a Multi-Use Framework for Grid-Scale Energy Storage

Final Project for AA 228: Decision-Making under Uncertainty

Abstract: Grid-scale energy storage systems (ESSs) are capable of participating in multiple grid applications, with the potential for multiple value streams for a single system, termed "value-stacking". This paper introduces a framework for decision making, using reinforcement learning to analyze the financial advantage of value-stacking grid-scale energy storage, as applied to a single residential home with energy storage. A policy is developed via Q-learning to dispatch the energy storage between two grid applications: time-of-use (TOU) bill reduction and energy arbitrage on locational marginal price (LMP). The performance of the dispatch resulting from this learned policy is then compared to several other dispatch cases: a baseline of no dispatch, a naively-determined dispatch, and the optimal dispatches for TOU and LMP separately. The policy obtained via Q-learning successfully led to the lowest cost, demonstrating the financial advantage of value-stacking.

About

Final Project for AA 228: Decision-Making under Uncertainty: Decision-Making Towards a Multi-Use Framework for Grid-Scale Energy Storage

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages