Hardware-in-the-Loop Simulation of a Distribution System with Air Conditioners under Model Predictive Control: Preprint

Bethany Sparn, Mark Ruth, Dheepak Krishnamurthy, Annabelle Pratt, Monte Lunacek, Wesley Jones, Hongyu Wu, Saurabh Mittal, Jesse Marks

Research output: Contribution to conferencePaper


Many have proposed that responsive load provided by distributed energy resources (DERs) and demand response (DR) are an option to provide flexibility to the grid and especially to distribution feeders. However, because responsive load involves a complex interplay between tariffs and DER and DR technologies, it is challenging to test and evaluate options without negatively impacting customers. This paper describes a hardware-in-the-loop (HIL) simulation system that has been developed to reduce the cost of evaluating the impact of advanced controllers (e.g., model predictive controllers) and technologies (e.g., responsive appliances). The HIL simulation system combines large-scale software simulation with a small set of representative building equipment hardware. It is used to perform HIL simulation of a distribution feeder and the loads on it under various tariff structures. In the reported HIL simulation, loads include many simulated air conditioners and one physical air conditioner. Independent model predictive controllers manage operations of all air conditioners under a time-of-use tariff. Results from this HIL simulation and a discussion of future development work of the system are presented.
Original languageAmerican English
Number of pages7
StatePublished - 2017
Event2017 Power and Energy Society General Meeting - Chicago, Illinois
Duration: 16 Jul 201720 Jul 2017


Conference2017 Power and Energy Society General Meeting
CityChicago, Illinois

NREL Publication Number

  • NREL/CP-5D00-67392


  • demand response
  • discrete-event systems
  • electricity tariffs
  • energy management
  • hardware-in-the-loop simulation
  • HEMS
  • HIL
  • home energy management system
  • power engineering computing
  • power system analysis computing
  • power system modeling
  • power system simulation
  • smart grids


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