A modular framework to enable rapid evaluation and exploration of energy management methods in smart home platforms

Xiao Qin, Lin Lin, Susan Lysecky, Meiling Wang, Young-Jun Son, Jonathan Sprinkle

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Numerous efforts focus on developing smart grid and smart home platforms to provide monitoring, management, and optimization solutions. In order to more effectively manage energy resources, a holistic view is needed; however the involved platforms are complex and require integration of a multitude of parameters such as the end-user behavior, underlying hardware components, environment, etc., many of which operate on varying time scale at various levels of detail. A general and modular framework is presented to enable designers to focus on modeling, simulating, analyzing, or optimizing specific sub-components without requiring a detailed implementation across all levels. We incorporate two case studies in which the proposed framework is utilized to help an end user evaluate platform configurations given an energy usage model, as well as integrate an energy optimization module to investigate rescheduling of appliance usage times in an effort to lower cost.

Original languageEnglish (US)
Pages (from-to)215-235
Number of pages21
JournalEnergy Systems
Volume7
Issue number2
DOIs
StatePublished - May 1 2016

Keywords

  • Optimization
  • Simulation
  • Smart grid
  • Transaction level modeling

ASJC Scopus subject areas

  • Energy(all)
  • Modeling and Simulation
  • Economics and Econometrics

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