A Markov process approach to ensemble control of smart buildings

Roman Pop, Ali Hassan, Kenneth Bruninx, Michael Chertkov, Yury Dvorkin

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper describes a step-by-step procedure that converts a physical model of a building into a Markov Process that characterizes energy consumption of this building. Relative to existing thermo-physics-based building models, the proposed procedure reduces model complexity and depends on fewer parameters, while also maintaining accuracy and feasibility sufficient for system-level analyses. Furthermore, the proposed Markov Process approach makes it possible to leverage real-time data streams available from intelligent building data acquisition systems, which are readily available in smart buildings, and merge it with physics-based and statistical models. Construction of the Markov Process naturally leads to a Markov Decision Process formulation, which describes optimal probabilistic control of a collection of similar buildings. The approach is illustrated using validated building data from Belgium.

Original languageEnglish (US)
Title of host publication2019 IEEE Milan PowerTech, PowerTech 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647226
StatePublished - Jun 2019
Event2019 IEEE Milan PowerTech, PowerTech 2019 - Milan, Italy
Duration: Jun 23 2019Jun 27 2019

Publication series

Name2019 IEEE Milan PowerTech, PowerTech 2019


Conference2019 IEEE Milan PowerTech, PowerTech 2019

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Safety, Risk, Reliability and Quality


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