Incomplete Air Mixing Reduces the Efficiency of Commercial Buildings Behaving as Virtual Batteries

TL;DR

The paper addresses inefficiencies in modeling HVAC as virtual batteries due to incomplete air mixing, a factor often ignored in conventional state-of-charge definitions. It develops a new RC-based mixing-air model that introduces a mixing zone between supply air and room air, linking mixing quality to virtual-battery efficiency measured by the round-trip efficiency $\text{RTE}=\dfrac{E_{out}}{E_{in}}$. Through simulations and comparison with SHIFDR data, the study shows that poorer mixing degrades efficiency, but that closed-loop control around fan power—including a forced-settling period after events—can substantially restore efficiency toward unity. The results suggest practical strategies for improving grid-relevant flexibility in buildings, either by incorporating mixing dynamics into models or by implementing fan-power-based closed-loop control with accurate baselines and submetering.

Abstract

Commercial building Heating, Ventilation, and Air Conditioning (HVAC) systems can provide flexibility to the electricity grid. Some researchers have found it convenient to model HVAC systems as virtual batteries. These models also better align with models used by grid planners and operators. However, experiments have shown that HVAC load shifting can be inefficient, and virtual battery models do not capture this inefficiency well. While the models typically use the average room temperature as the system's ``state of charge," they do not capture other factors that affect HVAC power/energy such as airflow and mixing. Here, we develop a new analytical building model to explore how incomplete mixing of supply air into a conditioned space leads to inefficiency in a virtual battery capturing the dynamics of HVAC fan power load shifting. The model qualitatively matches experimental results better than previous models, and shows that, as mixing becomes worse, the virtual battery becomes less efficient. Unfortunately, air mixing is unmeasured/unmeasurable. However, we show that, by closing the loop around measurements of fan power, we can improve the virtual battery's performance without the need for air mixing measurements. For example, in one case, we show a roundtrip efficiency improvement from 0.75 to 0.99.

Figures (8)

• Figure 1: Illustration of the basic operation of a VAV HVAC system operating in cooling mode.
• Figure 2: Example of the fan power during a DOWN-UP load shifting event. The actual fan power is shown compared to the baseline fan power. Time $t_\mathrm{start}$ is the start of the event, $t_\mathrm{end}$ is the end of the event, and $t_\mathrm{settle}$ is the point at which the building is assumed to have returned to normal operation. We also shade the regions corresponding to the input energy $E_\mathrm{in}$ and output energy $E_\mathrm{out}$, which are used in the battery model.
• Figure 3: RC circuit model for (A) the model developed in Lin_2R2C_model_paper and (B) the new mixing air model developed in this paper. We highlight in red the addition of an extra state that represents air that has not been fully mixed into the room air and the associated thermal resistance and capacitance.
• Figure 4: Block diagram of two control strategies: 1) open-loop load shifting via temperature setpoint control shown in black and 2) closed-loop load shifting via power control, which adds the loop shown in blue.
• Figure 5: Comparison of 2021 experimental data from SHIFDR SHIFDR, the original model developed in Lin_2R2C_model_paper, and the new mixing air model developed in this paper. For the experimental data (first six sets of plots), we plot the individual events in blue and their time-series average in black. Qualitatively, the mixing air model better matches the experimental data than the original model.