A Hierarchical Approach to Multienergy Demand Response: From Electricity to Multienergy Applications

Ali Hassan, Samrat Acharya, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin

Research output: Contribution to journalArticlepeer-review

Abstract

Due to proliferation of energy efficiency measures and availability of the renewable energy resources, traditional energy infrastructure systems (electricity, heat, gas) can no longer be operated in a centralized manner under the assumption that consumer behavior is inflexible, i.e., cannot be adjusted in return for an adequate incentive. To allow for a less centralized operating paradigm, consumer-end perspective and abilities should be integrated in current dispatch practices and accounted for in switching between different energy sources not only at the system but also at the individual consumer level. Since consumers are confined within different built environments, this article looks into an opportunity to control energy consumption of an aggregation of many residential, commercial, and industrial consumers, into an ensemble. This ensemble control becomes a modern demand response (DR) contributor to the set of modeling tools for multienergy infrastructure systems.

Original languageEnglish (US)
Article number9076178
Pages (from-to)1457-1474
Number of pages18
JournalProceedings of the IEEE
Volume108
Issue number9
DOIs
StatePublished - Sep 2020

Keywords

  • Demand response (DR)
  • Markov decision process (MDP)
  • multi-energy systems
  • reinforcement learning
  • robust optimization
  • smart buidlings
  • stochastic optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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