# Modeling Heat Consumption of an Office Building During COVID-19 Restrictions
###### Abstract
\begin{table}
\begin{tabular}{c c} \hline \hline
**Research Gap** & **Explanation** \\ \hline \multirow{4}{*}{\begin{tabular}{c} Insufficient modeling of heat \\ consumption changes post COVID-19 \\ \end{tabular} } & \begin{tabular}{c} Current models fail to incorporate the unique and enduring impacts of \\ reduced office occupancy, remote work trends, and the psychological and \\ operational shifts brought about by the pandemic. These factors have \\ altered internal heat gains and user behavior in ways that traditional heat \\ consumption models cannot predict accurately \\ \end{tabular} \\ \hline \multirow{4}{*}{\begin{tabular}{c} Lack of comprehensive integration of \\ diverse factors \\ \end{tabular} } & \begin{tabular}{c} Factors such as night setbacks, cold air infiltration, internal and solar \\ gains, wind-induced convection, and variations in the performance of \\ thermostatic radiator valves (TRVs) are often studied in isolation. Existing \\ studies (e.g., [PERSON] et al. [2], [PERSON] et al. [4], [PERSON] [7]) focus on \\ individual aspects rather than a holistic approach that integrates these \\ variables into a single, robust model \\ \hline \multirow{4}{*}{\begin{tabular}{c} A gap in control system analysis for \\ realistic HVAC systems \\ \end{tabular} } & \begin{tabular}{c} Few studies explore the performance of real-world HVAC control systems, \\ especially in conjunction with flexible operation strategies like \\ temperature adjustments and thermal inertia. While some research has \\ examined PI controller tuning or indoor temperature stabilization (e.g., \\ [PERSON] et al. [10], [PERSON] et al. [6]), these studies have not sufficiently \\ addressed the interplay between flexible operation and long-term energy \\ efficiency in post-COVID scenarios \\ \end{tabular} \\ \hline \multirow{4}{*}{\begin{tabular}{c} Limited focus on \\ building-specific factors \\ \end{tabular} } & \begin{tabular}{c} Variations in building structure, insulation, and design characteristics \\ significantly impact heat recovery and energy flexibility. Current models \\ rarely differentiate between building types or include realistic operational \\ scenarios influenced by building-specific parameters \\ \end{tabular} \\ \hline \multirow{4}{*}{\begin{tabular}{c} Underexplored potential of flexible \\ heating operations \\ \end{tabular} } & \begin{tabular}{c} The potential for saving and optimization through flexible operation \\ strategies, including thermal inertia and the use of building envelopes for \\ energy storage, is not adequately explored. Studies like those by [PERSON] \\ et al. [7] have highlighted the benefits of flexibility but lacked a detailed \\ analysis of its implementation across diverse building configurations \\ \end{tabular} \\ \hline \multirow{4}{*}{\
\begin{tabular}{c} Insufficient post-COVID adaptations in \\ heating system profiles \\ \end{tabular} } &
\begin{tabular}{c} Adjustment factors that capture the differences in heat consumption \\ profiles before and after COVID-19 restrictions remain underexplored. \\ The novelty is addressing these profiles for light, medium, and \\ heavy structures \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The research gaps in relation to the existing literature. To sum up, this paper addresses the gap in integrating and simulating all relevant factors affecting heat consumption in office buildings under new operational conditions influenced by COVID-19. Specifically, it aims to develop and validate a detailed model that incorporates internal/external heat gains, HVAC control logic, and flexible operation strategies, addressing the limitations of the existing literature and providing actionable insights into optimizing heat consumption for varied building types and scenarios.