SMART: A stochastic multiscale model for the analysis of energy resources, technology, and policy

Warren Buckler Powell, Abraham George, Hugo Simão, Warren Scott, Alan Lamont, Jeffrey Stewart

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


We address the problem of modeling energy resource allocation, including dispatch, storage, and the longterm 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.

Original languageEnglish (US)
Pages (from-to)665-682
Number of pages18
JournalINFORMS Journal on Computing
Issue number4
StatePublished - Sep 2012

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Computer Science Applications
  • Management Science and Operations Research


  • Analysis of algorithms
  • Artificial intelligence
  • Queues
  • Simulation
  • Statistical analysis


Dive into the research topics of 'SMART: A stochastic multiscale model for the analysis of energy resources, technology, and policy'. Together they form a unique fingerprint.

Cite this