Analysis of predicted mean vote-based model predictive control for residential HVAC systems

Wang, Junke; Jiang, Yilin; Tang, Choon Yik; Song, Li

doi:10.1016/j.buildenv.2022.109952

Analysis of predicted mean vote-based model predictive control for residential HVAC systems

Journal Article · Thu Dec 22 23:00:00 EST 2022 · Building and Environment

DOI:https://doi.org/10.1016/j.buildenv.2022.109952· OSTI ID:2418656

^[1]; Jiang, Yilin ^[2]; ^[2]; Song, Li ^[2]

Univ. of Oklahoma, Norman, OK (United States); OSTI
Univ. of Oklahoma, Norman, OK (United States)

Model Predictive Control (MPC) is an advanced process control method that has attracted much attention in building heating, ventilation, and air conditioning (HVAC) systems. Here, this paper analyzes the optimal precooling performance in residential buildings using MPC with two different comfort indices, namely, temperature and predicted mean vote (PMV). It first formulates, for each comfort index, an optimization problem that accounts for different factors, such as weather, home thermal condition, prediction horizon, time-of use (TOU) utility rate, and rated cooling capacity. The problem is then solved, resulting in an MPC strategy that determines the HVAC on/off control signal and minimizes energy cost over a receding time horizon while maintaining thermal comfort. The energy performance difference between temperature-based and PMV-based MPC strategies is subsequently investigated, especially in light of the interior wall surface temperature and under different combinations of the factors. Extensive simulation results demonstrated that the proposed MPC strategies are adaptive and their performances depend primarily on weather, home thermal condition, and prediction horizon, while the impact of TOU utility rate and rated cooling capacity is relatively small. Because the PMV-based MPC strategy can take advantage of the lower interior wall surface temperature due to precooling, it resulted in 8–45% cost savings for the scenarios investigated and an average increase of 0.042–0.113 in the absolute value of the PMV index compared to the temperature-based MPC strategy.

View Accepted Manuscript (DOE)

Research Organization:: Univ. of Oklahoma, Norman, OK (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: EE0008697

OSTI ID:: 2418656

Alternate ID(s):: OSTI ID: 1907292

Journal Information:: Building and Environment, Journal Name: Building and Environment Vol. 229; ISSN 0360-1323

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
HVAC system
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Predicted mean vote
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Time-of-use rates

Analysis of predicted mean vote-based model predictive control for residential HVAC systems

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References (24)

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