A Systematic Approach for Exploring Tradeoffs in Predictive HVAC Control Systems for Buildings
Joshua Gluck, Christian Koehler, Jennifer Mankoff, Anind Dey, Yuvraj, Agarwal

TL;DR
This paper introduces a simulation framework to analyze tradeoffs between energy savings, occupant comfort, and predictive control accuracy in HVAC systems, validated on real-world building data.
Contribution
The authors develop a novel simulation framework that enables systematic exploration of tradeoffs in predictive HVAC control strategies using real occupancy data.
Findings
Predictive control can improve energy efficiency but may impact comfort.
Tradeoffs between control accuracy, energy savings, and occupant comfort are quantifiable.
Simulation results reveal optimal configurations for different stakeholder priorities.
Abstract
Heating, Ventilation, and Cooling (HVAC) systems are often the most significant contributor to the energy usage, and the operational cost, of large office buildings. Therefore, to understand the various factors affecting the energy usage, and to optimize the operational efficiency of building HVAC systems, energy analysts and architects often create simulations (e.g., EnergyPlus or DOE-2), of buildings prior to construction or renovation to determine energy savings and quantify the Return-on-Investment (ROI). While useful, these simulations usually use static HVAC control strategies such as lowering room temperature at night, or reactive control based on simulated room occupancy. Recently, advances have been made in HVAC control algorithms that predict room occupancy. However, these algorithms depend on costly sensor installations and the tradeoffs between predictive accuracy, energy…
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Taxonomy
TopicsBuilding Energy and Comfort Optimization · Energy Efficiency and Management · Facilities and Workplace Management
