Journal
INFORMS JOURNAL ON COMPUTING
Volume 24, Issue 4, Pages 665-682Publisher
INFORMS
DOI: 10.1287/ijoc.1110.0470
Keywords
artificial intelligence; simulation; statistical analysis; analysis of algorithms; queues
Ask authors/readers for more resources
We address the problem of modeling energy resource allocation, including dispatch, storage, and the long-term investments in new technologies, capturing different sources of uncertainty such as energy from wind, demands, prices, and rainfall. We also wish to model long-term investment decisions in the presence of uncertainty. Accurately modeling the value of all investments, such as wind turbines and solar panels, requires handling fine-grained temporal variability and uncertainty in wind and solar in the presence of storage. We propose a modeling and algorithmic strategy based on the framework of approximate dynamic programming (ADP) that can model these problems at hourly time increments over an entire year or several decades. We demonstrate the methodology using both spatially aggregate and disaggregate representations of energy supply and demand. This paper describes the initial proof of concept experiments for an ADP-based model called SMART; we describe the modeling and algorithmic strategy and provide comparisons against a deterministic benchmark as well as initial experiments on stochastic data sets.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available