# Modeling Heat Consumption of an Office Building During COVID-19 Restrictions
## 4 Results
With no employees, the DHW demand profile was very similar to the continuous uniform distribution and was established using the surveyed statistical data from the previous paper [25]. It had a negligible impact on the total energy consumption profile, so simplifying DHW demand as almost constant during the year seemed viable. At the same time, supply temperature was still regulated by Equations (2) and (3), leading to overheating and high return temperatures in current conditions (Figure 1). These results refer to any typical winter day (November, December, January, or February). However, in winter, the supply and return temperatures after and before a substation varied now not only according to the outdoor temperature but also due to wind, solar insolation, and the behavior of occupants changing the adjustment of TRV valves [9]. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Daily Average** & **Daily Operation** & **Night Operation** & **Indoor Design** & **Heating** \\
**Range** & **(07:00–22:00)** & **(2:00–07:00)** & **Temperature** & **Demand** \\ \({}^{\circ}\)C** & **[h]** & **[h]** & **[\({}^{\circ}\)C]** & **[kWh per Annum]** \\ \hline \(-34\) and below & 9 & 2 & 18 & 250 \\ \(-32\) to \(-33.9\) & 6 & 2 & 18 & 160 \\ \(-30\) to \(-31.9\) & 6 & 1 & 18 & 152 \\ \(-28\) to \(-29.9\) & 15 & 4 & 18 & 363 \\ \(-26\) to \(-27.9\) & 26 & 10 & 18 & 598 \\ \(-24\) to \(-25.9\) & 32 & 19 & 18 & 697 \\ \(-22\) to \(-23.9\) & 38 & 14 & 18 & 782 \\ \(-20\) to \(-21.9\) & 36 & 12 & 18 & 697 \\ \(-18\) to \(-19.9\) & 83 & 41 & 18 & 1506 \\ \(-16\) to \(-17.9\) & 111 & 29 & 18 & 1880 \\ \(-14\) to \(-15.9\) & 157 & 46 & 18 & 2470 \\ \(-12\) to \(-13.9\) & 135 & 43 & 18 & 1960 \\ \(-10\) to \(-11.9\) & 168 & 65 & 18 & 2236 \\ \(-8\) to \(-9.9\) & 211 & 71 & 18 & 2553 \\ \(-6\) to \(-7.9\) & 183 & 60 & 18 & 1993 \\ \(-4\) to \(-5.9\) & 158 & 36 & 18 & 1529 \\ \(-2\) to \(-3.9\) & 146 & 33 & 18 & 1237 \\ \(0\) to \(1.9\) & 163 & 51 & 18 & 1183 \\ \(2\) to \(3.9\) & 149 & 54 & 18 & 901 \\ \(4\) to \(5.9\) & 163 & 53 & 18 & 789 \\ \(6\) to \(7.9\) & 150 & 37 & 18 & 545 \\ \(8\) to \(9.9\) & 133 & 31 & 18 & 322 \\ \(10\) to \(11.9\) & 115 & 22 & 18 & 139 \\ \(12\) to \(13.9\) & 75 & 14 & 18 & n/a \\ \(14\) to \(15.9\) & 48 & 12 & 18 & n/a \\ \(16\) to \(17.9\) & 28 & 7 & 18 & n/a \\ \(18\) to \(19.9\) & 30 & 7 & 18 & n/a \\ \(20\) to \(21.9\) & 14 & 3 & 18 & n/a \\ \(22\) to \(23.9\) & 4 & 1 & 18 & n/a \\ \(24\) and above & 18 & 3 & 18 & n/a \\ Total & 2610 & 783 & n/a & 24,943 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The number of hours in which a temperature occurs in the specified band yearly (2020). Our methodology suggests a lower profile and more smoothly distributed SH demand, which actually happened in the studied building (Figure 2). To know the adjusting factors introduced in every simulation, the reader is invited to view Table 6. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Scenarios** & \
\begin{tabular}{c} **Number of Radiators** \\ **with TRVs** \\ \end{tabular} & **Shutdown** & **Wind** &
\begin{tabular}{c} **Indoor Temperature** \\ **Feedback** \\ \end{tabular} & **Occupancy** \\ \hline Notation & \(\xi\) & \(\beta\) & \(\mu\) & Lvent & f \\ \(\Lambda\)s i\({}^{*}\) & 1 & 1 & 1 & 4A & 1 \\ \#1 (Indoor & 0.7 & 1 & 1 & 4A–10A & 0–0.5 \\ temperature feedback) & \#2 (Solar insolation) & 0.7 & 1 & 1 & 4A & 0–0.5 \\ \#3 (Night setbacks) & 0.7 & 1.11 & 1 & 4A & 0–0.5 \\ \#4 (TRVs) & 0.5–1 & 1 & 1 & 4A & 0–0.5 \\ \#5 (Thermal inertia) & 0.7 & 1 & 1 & 4A & 0–0.5 \\ \#6 (Wind) & 0.7 & 1 & 1–1.15 & 4A & 0–0.5 \\ All the & 0.5–1 & 1.11 & 1–1.15 & 4A–10A & 0–0.5 \\ scenarios implemented & \multicolumn{1}{c}{} & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: A summary of adjusting factors for each scenario. Figure 2: Example of an hourly heat consumption profile for the studied building: (**a**) traditional regulation before COVID-19 and effect of scenarios #2 and #3; (**b**) effect due to novel regulation during COVID-19 restrictions: scenarios #4, #5, and combined.