Final version of the report
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14 changed files with 343 additions and 242 deletions
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@ -4,7 +4,7 @@ In order to better analyze the different model training and update methods it
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was decided to replace the physical \pdome\ building with a computer model.
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This allows for faster-than-real-time simulations, as well as perfectly
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reproducing the weather conditions and building response for direct comparison
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of different control schemes over long periods of time.
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of different control schemes over longer periods of time.
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The model is designed using the CARNOT
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toolbox~\cite{lohmannEinfuehrungSoftwareMATLAB} for Simulink. It is based on the
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@ -29,7 +29,7 @@ the choice of all the necessary model parameters.
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\clearpage
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The Simulink model is then completed by adding a \textit{Weather Data File}
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Finally, the Simulink model is completed by adding a \textit{Weather Data File}
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containing weather measurements for a whole year, and a \textit{Weather
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Prediction} block responsible for sending weather predictions to the MPC.\@ The
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controller itself is defined in Python and is connected to Simulink via three
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@ -56,7 +56,8 @@ skylights are measured to be squares of edge 2.5m.
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\begin{figure}[ht]
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\centering
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\includegraphics[width = 0.8\textwidth]{Images/google_maps_polydome_skylights}
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\vspace{-10pt}
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\includegraphics[width = 0.75\textwidth]{Images/google_maps_polydome_skylights}
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\caption{Google Maps Satellite view of the \pdome\ building}
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\label{fig:Google_Maps_Skylights}
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\end{figure}
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@ -70,9 +71,11 @@ as reference, after which the following measurements have been done in
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\citetitle{kimballGIMPGNUImage}~\cite{kimballGIMPGNUImage} using the
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\textit{Measure Tool}.
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The chosen reference object is the \pdome\ HVAC system, the full description of
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which is presented in Section~\ref{sec:HVAC_parameters}, and which has a known
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height of 2061mm \cite{aermecRoofTopManuelSelection}.
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The chosen reference object is the \pdome\ \acrshort{hvac} system, the full
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description of which is presented in Section~\ref{sec:HVAC_parameters}, and
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which has a known height of 2061mm \cite{aermecRoofTopManuelSelection}.
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\clearpage
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\begin{figure}[ht]
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\centering
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@ -91,7 +94,7 @@ Table~\ref{tab:GIMP_measurements}:
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\hline
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Object & Size [px] & Size[mm] & Size[m]\\
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\hline \hline
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HVAC height & 70 & 2100 & 2.1 \\
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acrshort{hvac} height & 70 & 2100 & 2.1 \\
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Building height & 230 & 6900 & 6.9 \\
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Stem wall & 45 & 1350 & 1.35 \\
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Dome height & 185 & 5550 & 5.55 \\
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@ -121,7 +124,7 @@ the model:
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The \pdome\ building has a structure that is mostly based on a dome shape, with
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the difference that the dome portion of the building does not reach the ground,
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but stands above it at a height of $\approx 1.35m$ (cf.
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but stands above it at a height of approximately $1.35$m (cf.
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Table~\ref{tab:GIMP_measurements}), with the large side windows extending to the
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ground and creating a \textit{stem wall} for the dome to sit on.
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@ -177,7 +180,7 @@ therefore be calculated as:
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The total volume of the building is then given as:
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\begin{equation}
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V = V_d + V_s = \frac{1}{6} \pi h (3r^2 + h^2) + l_s^2
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V = V_d + V_s = \frac{1}{6} \pi h (3r^2 + h^2) + l_s^2 * h_s
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\end{equation}
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Numerically, considering a dome diameter of 28m, a dome height of 5.55m and a stem
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@ -187,7 +190,7 @@ wall edge of 25m, we get the approximate volume of the building:
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\end{equation}
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The value presented in Equation~\ref{eq:numerical_volume} is used directly in
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the \textit{room\_node} of the CARNOT model (cf.
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the \textit{room\_node} element of the CARNOT model (cf.
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Figure~\ref{fig:CARNOT_polydome}), as well as the calculation of the Air
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Exchange Rate, presented in Section~\ref{sec:Air_Exchange_Rate}.
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@ -205,15 +208,15 @@ the chairs, tables, etc.\ but due to the restricted access to the building a
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simpler approximation has been made.
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\textcite{johraNumericalAnalysisImpact2017} present a methodology to model the
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furniture in buildings for multiple different materials, as well as an
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\textit{equivalent indoor content material} that is meant to approximate the
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furniture content of an office building. These values for mass content, surface
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area, material density and thermal conductivity have been taken as the basis for
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the \pdome\ furniture content approximation, with the assumption that, since the
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\pdome\ is still mostly empty, it has approximately a quarter of the furniture
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present in a fully furnished office.
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furniture in buildings for different materials, as well as an \textit{equivalent
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indoor content material} that is meant to approximate the furniture content of
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an office building. These values for mass content, surface area, material
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density and thermal conductivity have been taken as the basis for the \pdome\
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furniture content approximation, with the assumption that, since the \pdome\ is
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still mostly empty, it has approximately a quarter of the furniture present in a
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fully furnished office.
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The full set of furniture is therefore approximated in the CARNOT model as a
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The full set of furniture is, therefore, approximated in the CARNOT model as a
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wall, with the numerical values for mass, surface, thickness and volume
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presented below.
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@ -222,11 +225,11 @@ presented below.
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% 1/4 * 1.8 [m2/m2 of floor space] * 625 m2 surface = 140 m2
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% 140 m2 = [7 20] m [height width]
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The equivalent material is taken to have a surface of 1.8 $m^2$ per each $m^2$
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of floor area~\cite{johraNumericalAnalysisImpact2017}. With a floor area of 625
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$m^2$, and assuming the furnishing of the building is a quarter that of a
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fully-furnished office, the \pdome\ furniture equivalent wall has a surface area
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of:
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The equivalent material is taken to have a surface of 1.8 $\text{m}^2$ per each
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$\text{m}^2$ of floor area~\cite{johraNumericalAnalysisImpact2017}. With a floor
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area of 625 $\text{m}^2$, and assuming the furnishing of the building is a
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quarter that of a fully-furnished office, the \pdome\ furniture equivalent wall
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has a surface area of:
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\begin{equation}
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S_f = \frac{1}{4} \cdot 1.8 \left[\frac{\text{m}^2}{\text{m}^2}\right]
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@ -238,7 +241,8 @@ of:
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% 1/4 * 40 [kg/m2 of floor space] * 625 m2 surface = 6250 kg
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The mass of the furniture equivalent wall is computed using the same
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methodology, considering 40 kg of furniture mass per $m^2$ of floor surface.
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methodology, considering 40 kg of furniture mass per $\text{m}^2$ of floor
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surface.
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\begin{equation}
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M_f = \frac{1}{4} \cdot 40 \cdot 625\ \left[\text{m}^2\right] = 6250\
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@ -273,9 +277,9 @@ volume by the surface:
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\subsection{Material properties}
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In order to better simulate the behaviour of the real \pdome\ building it is
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In order to better simulate the behaviour of the real \pdome\ building, it is
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necessary to approximate the building materials and their properties as close as
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possible. This section goes into the details and arguments for the choice of
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possible. This section goes into details and arguments for the choice of
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parameters for each of the CARNOT nodes' properties.
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\subsubsection{Windows}
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@ -293,7 +297,7 @@ models~\cite{WhatAreTypical2018}.
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The US Energy Department states that the
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typical U-factor values for modern window installations is in the range of 0.2
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--- 1.2 \(\frac{W}{m^2K}\)\cite{GuideEnergyEfficientWindows}.
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--- 1.2 \(\frac{W}{m^2K}\)~\cite{GuideEnergyEfficientWindows}.
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The European flat glass association claims that the maximum allowable U-factor
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value for new window installations in the private sector buildings in
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@ -320,8 +324,8 @@ values of 2500 \(\frac{kg}{m^3}\) and 1008 \(\frac{J}{kgK}\) respectively.
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% Heat capacity for each material
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% Density for each material
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The roof structure has been assumed to be made out of 10cm of insulation,
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enclosed on each side by 5cm of wood.
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The roof structure has been assumed to be made out of 10 cm of insulation,
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enclosed on each side by 5 cm of wood.
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%%% Floor
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% [5cm wood, 10cm insulation, 20cm concrete]
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@ -329,8 +333,8 @@ enclosed on each side by 5cm of wood.
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% Heat capacity for each material
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% Density for each material
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The floor composition has been taken as consisting of, from top to bottom, 5cm
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wood, 10cm insulation followed by 20cm of concrete.
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The floor composition has been taken as consisting of, from top to bottom, 5 cm
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wood, 10 cm insulation followed by 20 cm of concrete.
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All the necessary values to characterise these materials have been taken
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from~\cite{BuildingsHeatTransferData} and are presented in
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@ -356,22 +360,22 @@ Table~\ref{tab:material_properties}:
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\subsection{HVAC parameters}\label{sec:HVAC_parameters}
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The \pdome\ is equipped with an \textit{AERMEC RTY-04} HVAC system. According to
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the manufacturer's manual~\cite{aermecRoofTopManuelSelection}, this HVAC houses
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two compressors, of power 11.2 kW and 8.4 kW respectively, an external
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ventilator of power 1.67 kW, and a reflow ventilator of power 2 kW. The unit has
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a typical \acrlong{eer} (\acrshort{eer}, cooling efficiency) of 4.9 --- 5.1 and
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a \acrlong{cop} (\acrshort{cop}, heating efficiency) of 5.0, for a maximum
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cooling capacity of 64.2 kW.
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The \pdome\ is equipped with an \textit{AERMEC RTY-04} \acrshort{hvac} system.
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According to the manufacturer's manual~\cite{aermecRoofTopManuelSelection}, this
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\acrshort{hvac} houses two compressors of power 11.2 kW and 8.4 kW respectively,
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an external ventilator of power 1.67 kW, and a reflow ventilator of power 2 kW.
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The unit has a typical \acrlong{eer} (\acrshort{eer}, cooling efficiency) of 4.9
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--- 5.1 and a \acrlong{cop} (\acrshort{cop}, heating efficiency) of 5.0, for a
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maximum cooling capacity of 64.2 kW.
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One particularity of this HVAC unit is that during summer only one of the two
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compressors are running. This results in a higher \acrlong{eer}, in the cases
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where the full cooling capacity is not required.
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One particularity of this \acrshort{hvac} unit is that during summer, only one
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of the two compressors are running. This results in a higher \acrlong{eer}, in
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the cases where the full cooling capacity is not required.
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\subsubsection*{Ventilation}
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According to the manufacturer manual \cite{aermecRoofTopManuelSelection}, the
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HVAC unit's external fan has an air debit ranging between 4900
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\acrshort{hvac} unit's external fan has an air debit ranging between 4900
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$\text{m}^3/\text{h}$ and 7000 $\text{m}^3/\text{h}$.
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\subsubsection*{Air Exchange Rate}\label{sec:Air_Exchange_Rate}
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@ -384,7 +388,8 @@ computed by dividing the air flow through the room by the room volume:
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\text{Air exchange rate} = \frac{\text{Air flow}}{\text{Total volume}}
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\end{equation}
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In the case of the \pdome\ and its HVAC, this results in an airflow range of:
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In the case of the \pdome\ and its \acrshort{hvac}, this results in an airflow
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range of:
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\begin{equation}
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\begin{aligned}
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@ -402,7 +407,7 @@ would require more precise measurements to estimate.
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\subsection{Validating against experimental data}\label{sec:CARNOT_experimental}
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In order to confirm the validity of the model it is necessary to compare the
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In order to confirm the validity of the model, it is necessary to compare the
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CARNOT models' behaviour against that of the real \pdome\ building.
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Section~\ref{sec:CARNOT_expdata} presents the available experimental data,
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@ -421,8 +426,8 @@ The data has been collected in the time span of June to August 2017, and is
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divided in seven different experiments, as presented in
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Figure~\ref{tab:exp_dates}. The available measurements are the \textit{Outside
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Temperature}, \textit{Solar Irradiation}, \textit{Electrical power consumption}
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of the HVAC, and two measurements of \textit{Inside Temperature} in different
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parts of the room.
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of the \acrshort{hvac}, and two measurements of \textit{Inside Temperature} in
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different parts of the room.
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\begin{table}[ht]
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\centering
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@ -445,27 +450,29 @@ parts of the room.
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\clearpage
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As mentioned previously, the external fan of the HVAC is constantly running.
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This can be seen in Figure~\ref{fig:Polydome_electricity} as the electricity
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consumption of the HVAC has a baseline of 1.67 kW of power consumption.
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As mentioned previously, the external fan of the \acrshort{hvac} is constantly
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running. This can be seen in Figure~\ref{fig:Polydome_electricity} as the
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electricity consumption of the \acrshort{hvac} has a baseline of 1.67 kW.
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\begin{figure}[ht]
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\centering
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\includegraphics[width = \textwidth]{Plots/Fan_baseline.pdf}
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\caption{Electrical Power consumption of the \pdome\ HVAC for Experiment 7}
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\caption{Electrical Power consumption of the \pdome\ \acrshort{hvac} for Experiment 7}
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\label{fig:Polydome_electricity}
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\end{figure}
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Figure~\ref{fig:Polydome_electricity} also gives an insight into the workings of
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the HVAC when it comes to the combination of the two available compressors. The
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instruction manual of the HVAC~\cite{aermecRoofTopManuelSelection} notes that in
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summer only one of the compressors is running. This allows for a larger
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\acrshort{eer} value and thus better performance. We can see that this is the
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case for most of the experiment, where the power consumption caps at around 6
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kW. There are, however, moments during the first part of the experiment where
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the power momentarily peaks over the 6 kW limit, and goes as high as around 9
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kW. This most probably happens when the HVAC decides that the difference between
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the set point temperature and the actual measured values is too large.
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the \acrshort{hvac} when it comes to the combination of the two available
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compressors. The instruction manual of the
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\acrshort{hvac}~\cite{aermecRoofTopManuelSelection} notes that in summer only
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one of the compressors is running. This allows for a larger \acrshort{eer} value
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and thus better performance. We can see that this is the case for most of the
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experiment, where the power consumption caps at around 6~kW. There are, however,
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moments during the first part of the experiment where the power momentarily
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peaks over the 6~kW limit, and goes as high as around 9~kW. This most probably
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happens when the \acrshort{hvac} decides that the difference between the set
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point temperature and the actual measured values is too large to compensate with
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a single compressor.
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Figure~\ref{fig:Polydome_exp7_settemp} presents the values of the set point
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temperature and the measured internal temperature.
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@ -473,7 +480,7 @@ temperature and the measured internal temperature.
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\begin{figure}[ht]
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\centering
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\includegraphics[width = \textwidth]{Plots/Exp_settemp.pdf}
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\caption{Measured vs set point temperature of the HVAC for Experiment 7}
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\caption{Measured vs set point temperature of the \acrshort{hvac} for Experiment 7}
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\label{fig:Polydome_exp7_settemp}
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\end{figure}
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set point temperature is the value that gets changed in order to excite the
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system, and since the \acrshort{hvac}'s controller is on during identification,
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it will oscillate between using one or two compressors. Lastly, it is possible
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to notice that the HVAC is not turned on during the night, with the exception of
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the external fan, which runs continuously.
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to notice that the \acrshort{hvac} is not turned on during the night, with the
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exception of the external fan, which continues running.
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\subsubsection{The CARNOT WDB weather data format}\label{sec:CARNOT_WDB}
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@ -499,12 +506,12 @@ pressure, wind speed and direction, etc. A detailed overview of each
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measurement necessary for a simulation is given in the CARNOT user
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manual~\cite{CARNOTManual}.
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In order to compare the CARNOT model's performance to that of the real \pdome\
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In order to compare the CARNOT model's performance to that of the real \pdome\,
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it is necessary to simulate the CARNOT model under the same set of conditions as
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the ones present during the experimental data collection. In order to do this,
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all the missing values that are required by the simulation have to be filled. In
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some cases, such as the sun angles it is possible to compute the exact values,
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but in other cases the real data is not available, which means that is has to be
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but in other cases the real data is not available, which means that it has to be
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inferred from the available data.
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The information on the zenith and azimuth solar angles can be computed exactly
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@ -514,7 +521,7 @@ information available, the zenith, azimuth angles, as well as the \acrfull{aoi}
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are computed using the Python pvlib
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library~\cite{f.holmgrenPvlibPythonPython2018}.
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As opposed to the solar angles which can be computed exactly from the available
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As opposed to the solar angles, which can be computed exactly from the available
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information, the Solar Radiation Components (DHI and DNI) have to be estimated
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from the available measurements of GHI, zenith angles (Z) and datetime
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information. \textcite{erbsEstimationDiffuseRadiation1982} present an empirical
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@ -535,33 +542,33 @@ are computed using the Python pvlib.
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The values that cannot be either calculated or approximated from the available
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data, such as the precipitation, wind direction, incidence angles in place of
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vertical and main/secondary surface axis have been replaced with the default
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vertical and main/secondary surface axis, have been replaced with the default
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CARNOT placeholder value of -9999. The relative humidity, cloud index, pressure
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and wind speed have been fixed to 50\%, 0.5, 96300 Pa, 0 $\text{m}/\text{s}$
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respectively.
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\subsubsection{\pdome\ and CARNOT model comparison}\label{sec:CARNOT_comparison}
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With the WDB data compiled, we can now turn to simulating the CARNOT model and
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compare its behaviour to that of the real \pdome\ building.
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With the \acrshort{wdb} data compiled, we can now turn to simulating the CARNOT
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model and compare its behaviour to that of the real \pdome\ building.
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Unfortunately, one crucial piece of information is missing: the amount of heat
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the HVAC either pumps in or takes out of the building at any point in time. This
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value could be approximated from the information of electrical power consumption
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and the EER, COP values given that it is known if the HVAC is in either heating
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or cooling mode.
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Unfortunately, one crucial piece of information is still missing: the amount of
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heat that the \acrshort{hvac} either pumps in or takes out of the building at
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any point in time. This value could be approximated from the information of
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electrical power consumption and the \acrshort{eer}/\acrshort{cop} values given
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that it is known if the \acrshort{hvac} is in either heating or cooling mode.
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This information lacking in the existing experimental datasets, the heat
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supplied/ taken out of the system has been inferred from the electrical energy
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use, measured building temperature and HVAC temperature set point, with the
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assumption that the HVAC is in cooling mode whenever the measurements are
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higher than the set point temperature, and is in heating mode otherwise. As it
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can already be seen in Figure~\ref{fig:Polydome_exp7_settemp}, this is a very
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strong assumption, that is not necessarily always correct. It works well when
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the measurements are very different from the set point, as is the case in the
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first part of the experiment, but this assumption is false for the second part
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of the experiment, where the set point temperature remains fixed and it is purely
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the HVAC's job to regulate the temperature.
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use, measured building temperature and \acrshort{hvac} temperature set point,
|
||||
with the assumption that the \acrshort{hvac} is in cooling mode whenever the
|
||||
measurements are higher than the set point temperature, and is in heating mode
|
||||
otherwise. As it can already be seen in Figure~\ref{fig:Polydome_exp7_settemp},
|
||||
this is a very strong assumption, that is not necessarily always correct. It
|
||||
works well when the measurements are very different from the set point, as is
|
||||
the case in the first part of the experiment, but this assumption is false for
|
||||
the second part of the experiment, where the set point temperature remains fixed
|
||||
and it is purely the \acrshort{hvac}'s job to regulate the temperature.
|
||||
|
||||
\begin{figure}[ht]
|
||||
\centering
|
||||
|
@ -575,23 +582,23 @@ the HVAC's job to regulate the temperature.
|
|||
The results of the seven simulations are presented in
|
||||
Figure~\ref{fig:CARNOT_simulation_validation}. Overall, the simulated
|
||||
temperature has the same behaviour as the real \pdome\ measurements. A more
|
||||
detailed inspection shows that for most of the experiments the simulated
|
||||
detailed inspection shows that for most of the experiments, the simulated
|
||||
temperature is much more volatile than the true measurements. This could be due
|
||||
to an overestimated value of the Air Exchange Rate, underestimated amount of
|
||||
furniture in the building, or, more probably, miscalculation of the HVAC's
|
||||
heating/cooling mode. Of note is the large difference in behaviour for the
|
||||
Experiments 5 and 6. In fact, for these experiments, the values for the
|
||||
electrical power consumption greatly differ in shape from the ones presented in
|
||||
the other datasets, which could potentially mean erroneous measurements, or some
|
||||
other underlying problem with the data.
|
||||
furniture in the building or, more probably, miscalculation of the
|
||||
\acrshort{hvac}'s heating/cooling mode. Of note is the large difference in
|
||||
behaviour for the Experiments 5 and 6. In fact, for these experiments, the
|
||||
values for the electrical power consumption greatly differ in shape from the
|
||||
ones presented in the other datasets, which could potentially mean erroneous
|
||||
measurements, or some other underlying problem with the data.
|
||||
|
||||
Finally, it is possible to conclude that the CARNOT building behaves comparably
|
||||
to the real \pdome\, even if not perfectly simulates its behaviour. These
|
||||
differences could come from multiple factors, missing information that had to
|
||||
be inferred and/or approximated, such as the Air Exchange Ratio, the heat
|
||||
differences could come from multiple factors --- missing information that had
|
||||
to be inferred and/or approximated, such as the Air Exchange Ratio, the heat
|
||||
provided/extracted, the amount of furniture in the building, the overall shape
|
||||
and size of the building, as well as possibly errors in the experimental data
|
||||
used for validation. A more detailed analysis of the building parameters would
|
||||
have to be done in order to find the reason and eliminate these discrepancies.
|
||||
have to be done in order to find the reasons and eliminate these discrepancies.
|
||||
|
||||
\clearpage
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue