Evaluating optimal control of active insulation and HVAC systems in residential buildings

Recently, active insulation systems (AIS) have been conceptualized in building envelopes to optimally modulate thermal resistance in response to changing environmental conditions. Building flexibility can further be improved if the building is also equipped with optimized heating, ventilating, and air conditioning (HVAC) control. In this work, we investigate the annual potential benefits of jointly optimizing AIS and HVAC system controls in both heating and cooling days over all climate zones (CZs) in the U.S. To reduce the computational complexity of applying model predictive control (MPC) to annual operations and detailed whole-building energy models, timeseries clustering was used to identify a set of representative days for optimizing in each climate zone. To isolate the increase in benefits from this joint optimization, we compare the performance to cases where the AIS and HVAC controls are optimized separately. Results indicate savings potential in all CZs, with the largest annual average savings of 9.02% and 4.02% observed in the cooling days with large daily temperature swings and heating days with cold sunny conditions, respectively. Savings patterns across climate zone, day types, and HVAC modes (i.e., heating or cooling) are also discussed along with the implications of important system design variables.

© This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

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Work Title Evaluating optimal control of active insulation and HVAC systems in residential buildings
Access
Open Access
Creators
  1. Amin Sepehri
  2. Gregory S. Pavlak
Keyword
  1. Active insulation
  2. Model predictive control
  3. Thermal energy storage
  4. Passive thermal storage
  5. Building thermal mass
  6. Optimal control
  7. Grid-interactive buildings
License CC BY-NC-ND 4.0 (Attribution-NonCommercial-NoDerivatives)
Work Type Article
Publisher
  1. Energy and Buildings
Publication Date December 27, 2022
Publisher Identifier (DOI)
  1. https://doi.org/10.1016/j.enbuild.2022.112728
Deposited November 12, 2023

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Version 1
published

  • Created
  • Added Joint_Setpoint_and_AIS_Optimization-4_post-1.pdf
  • Added Creator Amin Sepehri
  • Added Creator Gregory S. Pavlak
  • Published
  • Updated Keyword, Publication Date Show Changes
    Keyword
    • Active insulation, Model predictive control, Thermal energy storage, Passive thermal storage, Building thermal mass, Optimal control, Grid-interactive buildings
    Publication Date
    • 2023-02-15
    • 2022-12-27
  • Updated