## 4 Case Study
### Simulation Modeling  
#### 4.1.1 Target Building and System  
A single-story office building was modeled based on a medium-sized office-building model provided by the U.S. Department of Energy [20]. The weather data used for the simulation were sourced from the International Weather Files for Energy Calculation 2.0 for Daejeon, South Korea [21]. The thermal transmittance of the structure was set to satisfy the criteria for energy-saving design in central region 2 [22]. The cooling system applied to the building model was a variable air volume system consisting of a supply fan, cooling coil, circulation pump, water-cooled chiller, and cooling tower. The supply fan was modeled to variably control the supply air flow based on a partial load to meet the supply air set-point temperature. The circulation pump was modeled to variably control the supply chilled water flow based on the exit air temperature of the cooling coil. The chiller was modeled to variably control the chilled water flow to meet the chilled water set-point temperature. The set-point temperatures for the supply chilled water, supply air, and indoor air were 6.7 \({}^{\circ}\)C, 14 \({}^{\circ}\)C, and 26 \({}^{\circ}\)C, respectively. August was selected as the simulation period, which was the month with the highest annual average outdoor air temperature in Daejeon (Figure 5). The simulations were performed at 1-min intervals. The detailed input variables used for the simulation modeling are summarized in Table 3, and the building model envelope and cooling system schematics are shown in Figure 6.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Parameter** & **Value** \\ \hline  & & LSTM encoder & 140 \\  & Layers & 70 \\  & & LSTM decoder & 140 \\ Hyper & Optimizer & & Adam \\ parameters & Activation function & & ReLU \\  & Loss function & & Mean squared error \\  & Batch size & & 32 \\  & Epochs & & 100 \\ \hline  & & Outdoor air temperature \\  & & Chiller energy consumption \\  & & SCWT \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameters of the LSTM-autoencoder.  
Figure 5: Monthly outdoor air temperature distribution in Daejeon, South Korea.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{2}{c}{**Input Parameter**} & \multicolumn{2}{c}{**Value**} \\ \hline \multirow{4}{*}{Building} & \multirow{2}{*}{Zone} & Location & Daejeon, South Korea \\  & & Type & Office \\  & & Zone volume & 4800 m\({}^{3}\) \\  & & Indoor set-point temp. & 26 \({}^{\circ}\)C \\ \cline{2-3}  & \multirow{2}{*}{U-values} & Exterior wall & 0.24 W/m\({}^{2}\)\(\cdot\)K \\  & & Window & 1.50 W/m\({}^{2}\)\(\cdot\)K \\  & & Roof & 0.15 W/m\({}^{2}\)\(\cdot\)K \\  & & Floor & 0.29 W/m\({}^{2}\)\(\cdot\)K \\ \cline{2-3}  & \multirow{2}{*}{Zone conditions} & People & 117.24 W/person \\  & & Light & 6.89 W/m\({}^{2}\) \\  & & Equipment & 8.07 W/m\({}^{2}\) \\ \hline \multirow{4}{*}{System} & \multirow{2}{*}{Capacity} & Supply fan & 2.7 m\({}^{3}\)/s \\ \cline{3-4}  & & Circulation pump & 0.003 m\({}^{3}\)/s \\ \cline{3-4}  & & Chiller & 70,000 W \\ \hline \multirow{2}{*}{Simulation setting} & \multirow{2}{*}{
\begin{tabular}{c} Run period \\ Time step \\ \end{tabular} } & \multicolumn{1}{c}{8/1 to 8/31} \\  & & Time step & 1 min \\ \hline \hline \end{tabular}
\end{table}
Table 3: Input parameters for simulation modeling.  
Figure 6: _Cont._