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A heuristic model predictive control method to activate the energy flexibility of electrically-heated school buildings.

Number: 3419

Author(s) : MOROVAT N., ATHIENITIS A. K., CANDANEDO J. A.

Summary

This paper presents a methodology to model and activate the energy flexibility of electrically-heated school buildings using a heuristic model predictive control approach. The heuristic model predictive control method is developed based on data-driven grey-box models for archetype thermal zones in school buildings. The archetype zones include the zones with convective systems (e.g., classrooms, library, and kindergarten). A third-order RC network for classrooms is developed and calibrated using measured data from an archetype school building. The winter peak load in Québec (Canada) significantly strains the electrical grid. Therefore, very cold and cold winter days are clustered into three categories depending on the one-day-ahead weather prediction: sunny, semi-cloudy/intermediate, and cloudy days. Heuristic setpoint profiles are selected to achieve the optimal zone temperature profile based on forecasted weather scenarios while considering the thermal comfort of the occupants. Key performance indicators are applied to quantify the energy flexibility at the school building. The case study school (located in Québec, Canada) is an electrically-heated building with geothermal heat pumps, radiant floors, and energy storage. Preliminary results show that with an appropriate heuristic model predictive control strategy, the zones with the convective system can provide energy flexibility of 47% during on-peak hours relative to a reference as-usual profile.

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  • Original title: A heuristic model predictive control method to activate the energy flexibility of electrically-heated school buildings.
  • Record ID : 30030232
  • Languages: English
  • Source: 2022 Purdue Conferences. 7th International High Performance Buildings Conference at Purdue.
  • Publication date: 2022

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