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\begin{document}

\title{Design of a sustainable out-of-town office building in Morocco:
Combining the Multi-Criteria Decision Making (MCDM) approach for
material selection to the rooftop PV system design}



\author[1]{Z. El Hallaoui}%
\affil[1]{Universite Euro-Mediterraneenne de Fes Centre de Recherche Euromed}%


\vspace{-1em}



  
  \date{June 06, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Achieving the building's sustainability requires the assessment of its
life-cycle, involving the selection of sustainable materials during the
construction stage and adopting rooftop PV system in the exploitation
stage, with the objective to lower its carbon footprint. This paper
reports a case study for the design of a sustainable office building,
located out of town, integrating PV panels for autonomous electricity
production. For this purpose, the multi criteria decision making
analysis was carried out to select the optimum sustainable materials,
and the energetic balance of the building was evaluated. Accordingly,
the required rooftop PV panels and the associated area were then
estimated, while a storage battery was included for the building's
continuous electrical supply. Using the Weighting Sum Method, and
considering the technical/environmental and financial constraints,
double wall in hollow brick and expanded polystyrene floor were
selected, while expanded polystyrene was used as the insulating
material. The energetic analysis of the building performances indicated
an average annual heating and air cooling requirement of 0.57 kWh/m
\textsuperscript{2} and 36.87 kWh/ m \textsuperscript{2}, respectively.
Finally, the on-roof PV panels required a nominal peak power of 400kWp
with 1218m \textsuperscript{2} area, while a 82kAh storage battery
capacity was evaluated for a continuous electricity production.%
\end{abstract}%



\sloppy


\textbf{Design of a sustainable out-of-town office building in Morocco:
Combining the Multi-Criteria Decision Making (MCDM) approach for
material selection to the rooftop PV system design}

El Hallaoui, Z.\textsuperscript{*}

\emph{Euromed Research Institute, Euro-Mediterranean University of Fes,
Eco-Campus, Fes, Morocco}

E-mail of the corresponding author:\emph{z.elhallaoui@ueuromed.org}

\textbf{Abstract}

Achieving the building's sustainability requires the assessment of its
life-cycle, involving the selection of sustainable materials during the
construction stage and adopting rooftop PV system in the exploitation
stage, with the objective to lower its carbon footprint. This paper
reports a case study for the design of a sustainable office building,
located out of town, integrating PV panels for autonomous electricity
production. For this purpose, the multi criteria decision making
analysis was carried out to select the optimum sustainable materials,
and the energetic balance of the building was evaluated. Accordingly,
the required rooftop PV panels and the associated area were then
estimated, while a storage battery was included for the building's
continuous electrical supply. Using the Weighting Sum Method, and
considering the technical/environmental and financial constraints,
double wall in hollow brick and expanded polystyrene floor were
selected, while expanded polystyrene was used as the insulating
material. The energetic analysis of the building performances indicated
an average annual heating and air cooling requirement of 0.57
kWh/m\textsuperscript{2} and 36.87 kWh/ m\textsuperscript{2},
respectively. Finally, the on-roof PV panels required a nominal peak
power of 400kWp with 1218m\textsuperscript{2} area, while a 82kAh
storage battery capacity was evaluated for a continuous electricity
production.

\emph{Keywords:}

\emph{Sustainable building; life-cycle; Storage battery; PV integration;
Multiple criteria decision making.}

\textbf{Highlights:}

\begin{itemize}
\tightlist
\item
  Lifecycle assessment to achieve the building' sustainability;
\item
  Combining MCDM material selection and rooftop PV panels design for
  building design;
\item
  The MCDM covered the technical, environmental and financial
  constraints;
\item
  Energy balance performed to design the rooftop PV system and storage
  battery;
\end{itemize}

Introduction

The building and building construction sectors combined are one of the
most energy intensive sectors, consuming almost 33\% of the global final
energy consumption {[}1{]}. It is thus an important source of greenhouse
emissions, with nearly 15\% of direct CO2 emissions. As its energy
demand is expected to increase, preserving the environment and managing
the energy resources emerges in the top of the worldwide economic and
social agenda.

With the depletion of the energetic resources and the environmental
constraints, there is an increasing interest in improving the
sustainability of buildings by integrating renewable energy sources,
which contribute to reduce impact on climate change.

In this sense, achieving a sustainable building requires considering its
life cycle steps (figure 1), which are mainly four stages represented in
the design stage (evaluation of the structure), construction stage
(selection of the materials and installation), exploitation stage (use
and energy consumption efficiency) and end-of-life stage. As both the
construction and the exploitation represent the major stages of the
building life cycle, these two stages should be carefully processed to
achieve the building's sustainability. Hence, a sustainable building
should follow the six principles of conserving, reusing, renewing,
protecting the nature and creating nontoxic and high quality
products{[}2{]}. Such buildings offer benefits either on an economic
level and the social viewpoint. Sustainable buildings therefor worth
more as they have known a 7\% increase in value compared to old
traditional buildings, due to lower operating costs{[}3{]}. Sustainable
building should minimize its environmental impact all over its lifespan
by pursuing two approaches (i) the selection of longer-life
materials/components and the best construction techniques during the
construction stage, followed by (ii) the integration of renewable energy
resources for power supply during the exploitation stage. On one hand,
the right choice of construction methods and techniques might have a
significant impact by controlling waste management and conserving
energy{[}4{]}, while the use of sustainable and low embodied energy
materials would reduce the building' carbon footprint. On the other
hand, during the exploitation phase, integrating renewable energies for
the building electrical need consist mainly in building-integrated solar
panels, which can be located either on the building's surface or on the
rooftop. By integrating solar panels to the building, not only its
carbon footprint is reduced, but also provides a shading effect which
reduces the heat input from the roof and consequently reduces the
building cooling load. Hence, the application of solar panels to the
building sector offers clean energy, provides shade and insulation, and
improves energy efficiency.

Unlike the case of exact sciences, which present generally a unique
solution to engineering problem, materials selection requires the
consideration of simultaneous advantages and limitations. Consequently,
a number of satisfactory solutions could be possible. Suppose you need
to select a material for a lower energy consumption from the various
marketable suggestions, should the cheapest material or the best
performing be chosen?

Figure 1: The building life cycle based on a sustainable approach

It is thus essential to adopt a scientific-based methodology to select
the best construction and insulating materials, which helps to develop
sustainable buildings during the construction stage. For this purpose,
Multi-Criteria Decision Making (MCDM) has emerged as one of the most
important and reliable analyzing techniques for operations research and
science management{[}5{]}. The MCDM refers to the process that aims to
select the more accurate solution considering related criteria.
Multi-Criteria Decision-making (MCDM) is thus an effective method to
enhance all features of decision-making in engineering applications,
from the initial design step to manufacturing{[}6{]}. This method could
be applied to all fields requiring an optimum solution to
multi-parameters problem, for which a decision could not be achieved
only by the users' experiences.

Multi-criteria decision-making (MCDM) theory is based on the use of
computational methods, which incorporate several criteria and order of
preference. This enables to evaluate and select the best option among
many alternatives based on the desired outcome{[}7{]}. The application
gives a ranking result based on the selected criteria, their
corresponding values, and assigned weights. Several techniques exist to
solve MCDM problems {[}8{]}, among which the Weighted Sum Method (WSM)
{[}9-10{]}, the Weighted Product Model (WPM) as a modification of the
WSM {[}11{]}, the Analytic Hierarchy Process (AHP){[}12{]}, Technique
for Order of Preference by Similarities to Ideal Solution
(TOPSIS){[}13{]}, ELECTRE method, Preference Ranking Organization Method
for Enrichment of Evaluations (PROMETHEE){[}14{]}, VIKOR and Data
Envelopment Analysis (DEA){[}15{]}. These solving methods might be
generally grouped in two main families: (i) the outranking methods build
a preference relation among alternatives which are evaluated on several
attributes{[}16{]}, and (ii) a-priori aggregation methods build a
preference relation among alternatives having equal probabilities to
occur{[}17{]}. Each technique differs by its level of complexity, the
model development, the accuracy, the criteria dependency and the
computational time {[}18{]}.

In this regard, serveral research papers investigated the use of the
MCDM to select the construction/insulating materials during the
construction stage. In this sense, Aparicio Ruiz et al. {[}19{]}
combined the Tabu search technique to a simplified calculation method,
to select the suitable materials and the HVAC system (heating,
ventilation and air conditioning) for a residential building in Spain.
The paper aims ,through the adopted methodology, to reache maximum
energy efficiency and cost savings by choosing the best construction
materials. For the material selection, the thermal properties constitute
the main evaluation criteria which may be summarized in the U-values,the
solar factor, the G-value or their air-tightness. To facilitate the
users decision-making, an automatic programm has been developed with a
graphic interface of the different construction materials. This enables
a rapid estimation, during the design step, to select the materials that
improve the quality of the buildings with the lowest life cyclecosts.
The obtained results showed that the final energy consumption was
estimated at 2.15 kWh/m\textsuperscript{2} for heating and 2.02
kWh/m\textsuperscript{2} for cooling when selecting the HVAC system
based on the method of optimization. These consumptions implied an
important reduction of 29.07\% and 50.39 \% in investment.

In the same perspective, Kanniyapan et al. {[}20{]} investigated the
criteria to select the building materials to achieve the building
maintainability. Combining both the Delphi method and the PLS-SEM
procedure, based on the surveys and questionnary to experts in the
field, a structural model was established between the maintability
coefficients and the selecting criteria. The developed model constitutes
an effective tool for decision makers to verify the maintainability
principles and criteria requiring higher attention. Vighnesh et al.
{[}21{]} studied the possible strategies to reduce the operational
energy in a building as a decisive criterion in a sustainability
standpoint. As the operational energy depends on the thermal properties,
the different components of the building (walls, roofs, floors,
windows\ldots{}) were evaluated through various combinations. To achieve
this goal, the first step consisted in the selection of the adequate
materials for the building componets, based on their U value, enabling
the reduction of the embodied energy through the selection of local
materials. Thereafter, a model was developed to evaluate the cooling
load of the building, with the variation of the construction materials
to study their effects on the annual cooling load. The obtained results
showed that the best wall component consisted in combining gypsum
plaster, bricks and expanded polystyrene, while galapagos selected
reinforced concrete combined with foam concrete as the best roofing
component.

Concerning the exploitation phase, and to achieve the building
sustainability, switching towards the use of renewable energy sources is
crucial to reduce energy costs and greenhouse gas emissions. Several
studies have compared the application of the different solar
technologies for the building energy supply, like PV/T panels and solar
thermal collectors {[}22-24{]}. They investigated the various aspects of
the solar technologies for the building needs, and showed that the PV
panels represent the best solution as they offer minimal maintenance,
decreased investment cost and available roofs space {[}25{]}. Hence,
power generation using photovoltaic (PV) solar energy is particularly
suited for urban environment {[}26{]}, as various unused surfaces (roofs
and facades) could be used for solar energy harvesting. Indeed, rooftop
PV systems for the building use have been increasingly popular in recent
years, as they offer numerous technological, economic, social, and
environmental benefit{[}27-28{]}. For electricity production through PV
panels in buildings, the two common configurations used are represented
by the on-grid and the off-grid configurations{[}29{]}. The on-grid
configuration is a building equipped with PV systems, which injects
whole or a part of its PV production to the grid. In Morocco, this
configuration is opened to electricity production for very high, high
and medium voltage electrical grids. On the other hand, the off-grid
configuration consists of a building equipped with PV systems which is
not connected to the grid. In this case, all the produced energy from
the PV systems must be consumed by the building, either through direct
use or by using storage. This off-grid configuration has no impact on
the electrical grid, and is widespread at low voltage grids for
self-production.

Numerous studies have been carried out on the subject of the PV system's
adoption in buildings to assess the PV system's technical performance,
energy efficiency, and its viability from an economic standpoint. Huang
et al. {[}30{]} investigated the transformation of an actual residential
cluster to electricity prosumers in Sweden. They tried to enhance the
energetic consumption and electricity production of the building
cluster. This was done by integrating PV panels and developing thermal
energy storage for generated excess PV electricity. The adopted
methodology used a genetic algorithm fitness function to optimize the
capacity and positions of PV modules. The obtained results showed a
significant improvement in district-level PV electricity
self-consumption, with almost 77\% compared to the baseline case. The
study proved the technical feasibility to switch the existing Swedish
building into smart electricity prosumers.

In the perspective to meeting the European Commission's climate goals,
Arowolo et al.{[}31{]} studied the techno-economic solutions yielding to
decarbonation of the building and transport sectors in three megapolis
in France. The proposed solutions concerned mainly installing rooftop
solar PV panels and the use of electrical vehicles. With the System
Advisor Model simulations, results showed that exploiting half the
available roof space enables responding to 20 \%--42 \% of total
electricity demand using renewable energy sources, while reducing 43 \%
to 48 \% of the global greenhouse emissions. The economic feasibility of
the study indicated an encouraging payback period of 2 to 3 years,
demonstrating the effectiveness of the proposed solutions. Table 1 is a
synthesis of the existing studies within the building sector, organized
according to the adopted approach, main outcome and limitations of the
study.

Table : Taxonomy of the literature review\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
N\selectlanguage{ngerman}°\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Paper\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Objective\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Approach\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Outcome\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Limitations\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Limitations\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Aparicio et al.{[}19{]}, \emph{2016}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Select construction materials \& HVAC system for a residential
building\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Tabu search technique\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Improve building's consumption; Lower the heating and cooling load;
Reduced investment.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Improve building's consumption; Lower the heating and cooling load;
Reduced investment.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Only the construction stage is investigated\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
2\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Kanniyapan et al.{[}20{]}, \emph{2019}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Investigate the selection criteria for the building's maintability\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Delphi Method \& PLS-SEM procedure\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Build a structural model between the maintability coefficients and
selecting criteria;\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Limited to the construction stage\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Limited to the construction stage\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
3\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Vighnesh et al.{[}21{]}, \emph{2020}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Reduce the building's operational energy\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Rhinocerous3D\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Select the best materials for the walls, roofs, floors and windows;
Optimized operational energy of 123.26 GJ.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Construction stage only evaluated.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Construction stage only evaluated.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
4\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Huang et al.{[}30{]}, \emph{2019}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Transforming a residential cluster to an electricity prosumers in
Sweden\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Genetic algorithm fitness function\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Optimize the capacity and PV panels position; 77\% improvement in
district-level.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Only the exploitation stage is evaluated\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Only the exploitation stage is evaluated\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Arowolo et al.{[}31{]}, \emph{2023}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Evaluate the techno-economic solutions to the building's decarbonation
in France\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
SAM modeling\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Installing roof-top PV panels; Reducing 43\% of the global GHE; An
encouraging payback of 2-3 years.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Exploitation stage investigated\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Exploitation stage investigated\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
6\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Uzair et al. {[}32{]}, \emph{2023}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Optimize the building electricity usage, costs, and user comfort for
sustainability goals\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
A novel MCDM approach\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Develop a novel data driven approach for the building energy management
\& 45\% reduction in electricity cost\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Exploitation stage is investigated \& limitation to few energy sources
optimization\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Exploitation stage is investigated \& limitation to few energy sources
optimization\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
7\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Chen et al. {[}33{]}, \emph{2023}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Develop a comprehensive criteria system to select energy-efficient
architectural glass materials (SAGM)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Combining BIM and ELECTRE MCDM approach\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Quantitative and qualitative criteria considered for SAGM selection \&
Sensitivity analysis to assess the relevance of the selection
method\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Only one component of the building was evaluated for the building'
sustainability evaluation\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Only one component of the building was evaluated for the building'
sustainability evaluation\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
8\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Tashtoush et al. {[}34{]}, \emph{2023}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Optimize the on/off grid rooftop PV system to reduce the carbon
footprint of a residential building\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
PVsyst software for the PV system modeling\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
95\% of the electrical load is covered by the PV system with a 10.6kWh
storage battery \& 5.33 million metric tons of CO2 emissions is
estimated for the apartment residential buildings\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Only the exploitation stage is optimized\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Only the exploitation stage is optimized\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
9\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Monna et al. {[}35{]}, \emph{2022}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Evaluate the rooftop PV system potential for electricity production of
residential buildings\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
PV*SOL 2021 simulation tool is used to estimate electricity
production\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
28\selectlanguage{ngerman}° tilt angle is the ideal for maximum electricity production from
rooftop PV systems \& three to eight times the electrical need is
covered by PV system depending on the tilt angle and location.\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Electrical production using PV system is investigated (Exploitation
stage)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Electrical production using PV system is investigated (Exploitation
stage)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Through the literature review (table 1), most of the research papers
working on the building sustainability have been restricted to study
either the material selection using MCDM approach during the
construction stage, or to design the rooftop PV system for building's
electrical/heat production during the exploitation phase. In the
previous studies, the MCDM material selection was mainly carried on to
respect the global criteria of environmental, financial and technical
constraints. Furthermore, the rooftop PV panels were designed either to
lower the electrical consumption from the grid or to achieve a decent
level of electrical autonomy.

To the best of our knowledge, no published works so far have evaluated
the building sustainability in its comprehensive approach in which the
two concepts are assessed, mainly both construction and exploitation
stages. The existing studies were limited to select the best
construction material in order to reduce the heat loss or to lower the
building carbon footprint, and to reduce the electrical consumption from
fossil fuels.

It in in this context that the present paper investigates the design of
a sustainable office building through a comprehensive approach of its
life cycle. This involved the choice of sustainable
construction/insulating materials during the construction phase,
combined to the adoption of PV panels for the global electricity
production during the exploitation phase. In this sense, this paper is
structured as follow:

\begin{enumerate}
\tightlist
\item
  Section 2 presents the construction stage concerning the material
  selection and the Weighted Sum Method employed to achieve the optimum
  choice;
\item
  Section 3 presents the exploitation stage involving the building
  performance analysis and the PV panels design (required area for PV
  panels setup, storage battery capacity and number of batteries).
\item
  Section 4 then presents selected results of the previous sections.
\end{enumerate}

In a nutshell, the major aims and novelties of the present paper may be
summarized as follow:

\begin{itemize}
\tightlist
\item
  Achieve the office building sustainability through the assessment of
  its lifecycle (both construction and exploitation stages);
\item
  Using the MCDM approach to select the best construction and insulating
  materials, with respect to the decision matrix;
\item
  Rooftop PV system design using a detailed mathematical model of the
  building thermal performances, including the nominal peak power and
  the storage battery.
\end{itemize}

\textbf{Construction stage}

\textbf{Materials selection criteria during the construction stage}

While designing a sustainable building, the selection of the best
construction and insulating material during the construction stage is a
key element to achieve the optimum building' performances. Being a
complex task, it is crucial to identify the significant selection
criteria to choose the best option from the available options. The
materials selection criteria are obtained from previous research papers
{[}19-21{]} and experts' opinion. In this sense, the materials choice
was made based on the following criteria (Table 2):

Table 2: Selection criteria for the construction \& insulating materials\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
Criteria & Technical & Technical & Technical & Technical & Environmental
& Environmental & Economical\tabularnewline
\midrule
\endhead
Attributes & Thermal & Mechanical & Acoustic & Hygrometric & Local
availability & Emissions &\tabularnewline
& thermal conductivity thermal inertia & Strength Ductility
Compressibility & Sound intensity sound absorption coefficient & Steam
resistance Porosity & distance to the production plant, imported
material\ldots{} & Embodied energy, CO\textsubscript{2} emissions &
Purchase cost investment payback\tabularnewline
\bottomrule
\end{longtable}

Hence, we could identify the selection criteria for the construction and
insulating materials as follow:

\begin{itemize}
\tightlist
\item
  Technical (thermal and mechanical properties), financial (purchase and
  maintenance cost) and environmental (embodied energy) constraints for
  the construction materials;
\item
  Thermal, acoustic, hygrometric (resistance to moisture) and
  environmental (local availability) constraints for the insulating
  materials.
\item
  Technical criteria
\end{itemize}

The definition of a sustainable building is technically feasible if and
only if several conditions are fulfilled. In this sense, its energy
consumption must be as low as possible throughout the life cycle of the
building. Hence, the building must have the least heat loss to the
exterior, enabling to achieve a minimal energy requirement for heating
or air cooling. The comparison between the various feasible solutions
will be carried out on a technical level by evaluating four main
factors, in particular, the thermal performances (the thermal inertia,
the thermal conductivity, the density\ldots{}), the acoustic
performances, hygrometric properties and mechanical properties for the
construction materials.

Financial criteria

Sustainable buildings necessarily involve higher costs, whether in the
acquisition of high-performance building materials or for the insulation
to be integrated. In order to encourage investors to commit significant
capital for the implementation of a sustainable construction, it is
necessary to consider the cost of the materials and to analyze the
profitability of the investment in terms of energy savings and return on
investment.

Environmental criteria

To lower the building carbon foot-print, the technical criterion alone
is not enough. It is important to identify the environmental criterion
in the selection of construction materials. In this sense, materials
showing low embodied energy should be prioritized, and local material
availability should also be considered as a smaller distance between the
production plant and the building site lowers the
CO\textsubscript{2}emissions due to transport.

\textbf{Weighted Sum Method for materials selection}

Selecting the most suitable materials for the building sustainability is
a complex task that involves managing a large amount of information
about the material properties and processes, where generally several
options could be adopted for a particular application {[}6{]}. Hence,
the best material should strike a balance between the
technical/environmental performances and the purchase cost.

It is in this sense that the Weighted Sum Method (WSM) multi-criteria
decision-making technique is used, providing the basis for selecting,
sorting, and prioritizing the various materials {[}36{]}. It is known to
be the simplest and probably the most widely used method for evaluating
a number of alternatives in terms of a number of decision criteria. It
is also recommended for a single solution point that reflects
preferences from a set of several options {[}37{]}. It is based on the
selection of the attributes (the various options) and the assigned
weights of the criteria.

The WSM generally includes three main steps, namely:

Development of the decision and weight matrix.

This step consists in building the evaluation matrix of the
alternatives\((D=x_{\text{ij}})\) and the weight vector
(\(w=[w_{1},\ldots,w_{m}])\), which can be expressed in matrix form as follows
(Eq.(1)):

\(D=\par
\begin{bmatrix}x_{11}&amp;\cdots&amp;x_{1n}\\
\vdots&amp;\ddots&amp;\vdots\\
x_{m1}&amp;\cdots&amp;x_{\text{mn}}\\
\end{bmatrix}\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1)\)

Normalizing the weighted decision matrix

The ith alternative for the jth criterion has a normalized value
of\(n_{\text{ij}}\).

\(n_{\text{ij}}=\frac{x_{\text{ij}}}{max,x_{\text{ij}}};\ W_{\text{ij}}={w_{\text{j\ }}n}_{\text{ij}}\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (2)\)

Ranking of alternatives

\(A_{i}^{\text{WSM\ score}}=\sum_{j=1}^{n}{w_{j}n_{\text{ij}}},\ for\ i=1,2,\ldots n\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (3)\)

Where \(w_{j}\) and \(n_{\text{ij}}\) represent the relative
weight of the criterion \(C_{j}\) and the normalized magnitude
of alternative\(A_{j}\), respectively.

Finally, the options are presented as a top-down ranking with the
highest \(A_{i}^{\text{WSM\ score}}\) ranking first.

\textbf{Exploitation stage}

\textbf{Thermal analysis of the building's performances}

The total heat balance (\(\varnothing_{\mathbf{T}})\)is the sum of all internal
and external loads from different surfaces of a thermal zone (Figure 2),
including surface gains (\(Q_{\text{surf}}\)), ventilation gains
(\(Q_{\text{ven\ }}\)), internal gains due to occupants
(\(Q_{\text{occup}}\)) , electrical equipment (\(Q_{\text{equip}}\)) and
lighting (\(Q_{\text{light}}\)), and the solar gains through windows
(\(Q_{\text{solar}}\)). The global heat balance is calculated according
to (Eq.(4)) as:\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 2: the various heat transfer modes for the project

\begin{equation}
\begin{matrix}Q_{T}=Q_{\text{ven\ }}+Q_{\text{sol}}+Q_{\text{surf}}+Q_{\text{occup}}+Q_{\text{equip}}+Q_{\text{light}}\#(4)\\
\end{matrix}\nonumber \\
 \end{equation}

Heat input through surface gains

The heat gains by transmission through the opaque exterior walls- namely
through the walls, the roof, the ceiling and the floor)- and the glazed
walls are calculated using equation (Eq.(5)).

\begin{equation}
\begin{matrix}Q_{\text{surf}}\ =\ U*S\ \#(5)\\
\end{matrix}\nonumber \\
 \end{equation}

Where \(U\) and \(S\) represent the thermal
conductivity and the area.

Heat input through ventilation (air renewal)

For hygienic concerns, air renewal should be maintained in an
air-conditioned room. It is generally adjusted either by natural or
mechanical ventilation of the premises, yielding to the ambient air
infiltration into the air-conditioned room.

Considering the labor code, a minimum fresh air flow of
25m\textsuperscript{3}/h should be provided for each occupant. Hence,
the heat gain through air infiltration is calculated using
Eq.(6)I\(\par
\begin{matrix}Q_{\text{ven}\ }\ =\ 0.34\ \text{qv}\text{\ \ }\#(6)\\
\end{matrix}\)

Where \(q_{v}\) represent the minimum fresh air flow
(m\textsuperscript{3}/h).

Heat input by solar irradiation

To estimate the solar heat gain on the building's facades, and for
higher accuracy, it is essential to estimate the annual solar
irradiation on each fa\selectlanguage{ngerman}çade based on its geographic orientation. For this
purpose, the meteorological data of the city were collected from
METEONORM software which can be interfaced with TRNbuild software for
data generation. The global solar heat gain is thus calculated using
Eq.(7):

\(Q_{\text{sol}}\ =\ \alpha.\ \eta\text{.\ S.\ I\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }(7)\)

Where \(\alpha,\ \eta\ \text{and}\text{\ I}\) represent the absorption coefficient, reduction
coefficient and the solar irradiance, respectively.

Heat gain due to occupants and electrical devices

To estimate the internal gains, a base-case scenario was assumed, with a
total occupancy of 3194 co-workers at equal distribution (50\% women and
50\% men). These occupants are equipped with electronic devices that
constitute a considerable source of sensible and latent heat.

The heat gain due to occupants is calculated according to the internal
temperature and the degree of activity of the co-workers. A person with
an increased activity would generate a higher heat to the environment.
Hence, the annual heat gain due to occupants is estimated based on the
occupation time of the building (Eq.8).

\(Q_{\text{occu}}\ =\ n_{\text{occu}}\left(\ SH+LH\right)\ t\ \ \ \)(8)

Where \(n_{\text{occu}},\ SH\ \),LH and
\(t\ \)represent the number of occupants, the sensible heat,
latent heat and the building occupation time respectively.

As laptops are the main electrical devices used in the buildings, they
constitute a source of heat gain to the working area. The annual heat
gain from electronic devices is hence estimated by Eq.(9)

\(Q_{\text{elec}}\ =n_{\text{elec}}\text{\ .}\text{SH}_{\text{ele}}.\ \ t\ \ \ \)(9)

Where \(n_{\text{elec}}\ ,S_{\text{ele}}\) represent the number of electronic devices and
their sensible heat, respectively.

Heat gain from lighting components

The heat gain from lighting elements is a sensible heat source which
depends mainly on the type of the selected lighting lamps. As the
buildings were under construction, the selection of the best lighting
lamps constitutes an essential step in the building's sustainability,
considering that the energetic consumption for lighting in the building
sector ranges from about 20\% to 45 \% of the overall energy consumption
{[}38{]}. Hence, estimating the heat gain from lighting requires the
design of the lighting scheme and the choice of the optimum lamps.

The choice of luminaires depends on the color and the illuminance
targeted. For a classical office building, it is recommended to choose
an average level of illumination of 500 lx {[}39{]}, while the color
rendering index (CRI) should be greater than 80 with 4000 K as color
temperature (CT){[}40{]}.

The lighting Utilance, corresponding to the ratio of the luminous flux
reaching effectively the studied surface (worktop, wall) to the global
flux emitted by the luminaires, expresses the effect of the working room
variables (dimensions and reflectance) on lighting efficiency {[}41{]}.
For this purpose, and considering a reflectance factor of 751 (which
stands for 70\% ceiling reflectance, 50\% wall reflectance and 10\%
useful plan reflectance), the calculation of the local index
`\emph{k'}which depends on the dimensions of the working space
(Eq.(10)).

\begin{equation}
\begin{matrix}K=\frac{a*b}{\left(a+b\right)h}\ \#(10)\\
\end{matrix}\nonumber \\
 \end{equation}

Where a,b and h corresponds to the length, width and the height of the
working space.

Hence, the required luminous flux for the office space
(\(O_{T}\)) is correlated to the dimensions of the space, the
utilance (\(U_{t}\)) and the level of illumination
(\(E\)), and calculated by (Eq.(11)).

\begin{equation}
\begin{matrix}O_{T}\ =\frac{\left(E\ \times S\ \right)}{U_{t}}*\selectlanguage{greek}\frac{\left(\text{δ\ }\right)}\selectlanguage{english}{\zeta\ }\#(11\\
\end{matrix})\nonumber \\
 \end{equation}

The number of lighting elements per working space is estimated
(Eq.(12)).

\(\par
\begin{matrix}N\ =\frac{O_{T}}{O_{\text{selected\ lighting}}}\#\left(12\right)\\
\end{matrix}\)

Based on the heat release of 12\% of the installed power for the LED
lamps, the global heat gain through lighting is calculated as (Eq.(13))
:

\begin{equation}
\begin{matrix}Q_{\text{lighting}}=0.12*P*N_{\text{luminaires}}*N_{h,lighting}\ \#\ (13)\\
\end{matrix}\nonumber \\
 \end{equation}

Where P and \(\mathbf{N}_{\mathbf{h,lighting}}\) correspond to the initial absorbed power
(W) and total hours of artificial lighting annually (hours).

Heating and cooling energy requirements

The heating and cooling energetic requirement are calculated considering
the heat loss to the environment, the external conditions (ambient air)
and the internal set point temperature. In this sense, the heating and
cooling energy requirement can be found using Eq.(14-15) :

\begin{equation}
\begin{matrix}Q_{\text{heating\ }}=Q_{\text{deperditive\ }}*\text{DD}_{\text{heating}}*\ \mu_{\text{heat}}\ \#(14)\\
\end{matrix}\nonumber \\
 \end{equation}\begin{equation}
\begin{matrix}Q_{\text{cooling\ }}=Q_{\text{aperditive\ }}*\text{DD}_{\text{cooling}}*\ \mu_{\text{cool}}\text{\ \ \ }\#(15)\\
\end{matrix}\nonumber \\
 \end{equation}

Where~:

\(\ \mu_{\text{heat}}\ \) and \(\mu_{\text{cool}}\ \)represent the reduction
coefficients for operation in heating and cooling mode, respectively,
corresponding to an average working time of 645 hours and 1643 hours.

\textbf{Solar PV panels integration for autonomous electricity
production}

The design of the required PV panels for the building electricity needs
involves to estimate the global power consumption for the electrical
appliances of the building based on the daily electrical consumption.

As the selected PV system is a `standalone', a storage battery unit is
included to ensure service continuity, namely at the night time or for
unfavorable solar conditions (insufficient level of solar irradiation).

Design of Solar panels

The key element in a PV grid system is the solar panel. It consists in
various cell modules in series and parallel circuits, containing
semiconducting materials that convert sunlight into electrical energy.
Three main types of PV cells are available, (i) Crystalline Silicon
Cells composed of many crystals and presenting the highest energy
efficiency, (ii) Thin-Film Cells consisting of thin layers semiconductor
material deposited on a substrate such as glass or plasticand (iii)
Organic Cells utilize organic molecules or polymers rather than
semiconducting minerals are starting to be commercially applied
{[}42-43{]}.

Hence, the global peak power for the PV panels is calculated by Eq.(16)
:

\(P_{p}=\frac{E_{p}}{I_{r}}\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (16)\)

Where :

\(E_{p}\) (kWh/day) and \(I_{r}\)
(kWh/m\textsuperscript{2}/day) represent the required energetic need of
the building and the solar irradiance, respectively.

Based on the technical properties of the PV cells, the number of
required modules is estimated using Eq.(17):

\(\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ N=\frac{P_{p}}{P_{\text{PV}}}\text{\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }(17)\)

Where \(P_{\text{PV}}\) denotes for the unitary nominal peak power of
the PV panel.

Sizing the storage battery

In a photovoltaic grid system, the battery is the equipment in charge of
energy storage. The batteries can be divided into two categories, based
on the integration type to the grid. The first type enables storing
electricity from both the grid and the PV panels, where no sale is
expected for the stored electricity to the grid. On the other hand, the
second type stores power from the grid and the PV panels, where the
stored power could either be supplied for buildings or sold{[}44{]}.

To achieve the highest efficiency and versatility of the solar setup,
the selection of the storage battery should consider both the purpose of
the battery and the construction material. In this regards, various
materials have been used, namely lead-acid, lithium ion, nickel cadmium
and flow batteries. For example, lead-acid batteries have been
widespread for the automotive and industrial applications, while
Nickel-cadmium batteries most popular in airline and industrial
applications for their durability at extreme temperatures. Lithium-ion
battery is the newest technology of energy storage, and is more adapted
for the building sector. This technology features a longer life time,
making it a promising technology for a long term vision despite the
higher upfront cost{[}45{]}.

The nominal capacity of the battery defines the amount of charge
delivered by a fully charged battery under specified conditions of
temperature and load {[}46{]}. Hence, the nominal capacity quantifies
the autonomy of the battery with respect to the energy consumption of
the intended building (Eq.(18)). In this sense, the battery's capacity
should be designed to supply sufficient electrical need during the
targeted autonomy period for the electrical equipment, generally a
period of 2 days autonomy. Accordingly, the number of storage batteries
required for the building's need is calculated considering the global
battery capacity and the nominal capacity of the selected storage
battery (Eq.(19)).

\(\text{\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }C_{\text{battery}}=\ \frac{E_{p}*\text{ND}_{\text{\ autonomy}}}{U_{\text{batterie}}*0.8}\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (18)\)

\(\text{\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }N_{\text{battery}}=\ \frac{C_{\text{battery}}}{\text{Nominal\ capacity\ }}\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (19)\)

\textbf{Results and discussion}

\textbf{Project description}

The project is located in a new area of the city of Casablanca-Morocco
(33.5731\selectlanguage{ngerman}° N, 7.5898° W), consisting in the construction of four
buildings on a global area of 62,121 m². Figure 3 presents the 3-D
modeling of the buildings and their location in a new area out of town,
where no adjacent buildings are built during the project design. Each
building features 7 floors and a ground level, with a 12m separation
between the buildings.

The building is aimed to have a reduced energy consumption while
respecting the Moroccan Building Thermal Regulations (RTCM) and offering
an autonomy in terms of electrical energy consumption of the network.
Table 3 presents the meteorological data of the city, which constitutes
a decisive information for the selection of construction and insulating
materials.

Table 3: Climatic data of the average monthly temperature of Casablanca
City (2022)\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllllll@{}}
\toprule
& Jan. & Feb. & March & Apr & May & June & July. & Aug & Sept & Oct. &
Nov. & Dec.\tabularnewline
\midrule
\endhead
T\textsubscript{max} & 25.7 & 26.9 & 28.3 & 28.9 & 30.5 & 30.2 & 31.2 &
31.2 & 30.1 & 29.8 & 27.3 & 26.6\tabularnewline
T\textsubscript{min} & 15.3 & 16.5 & 18.2 & 18.8 & 21.8 & 22.5 & 23 &
22.7 & 22.4 & 21.9 & 18.2 & 17.6\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure : The buildings construction description. (a): 3-D modeling of
the buildings; (b): location of the buildings

\textbf{Weight Sum Method for material selection during the construction
stage}

Based on the opinion of various experts and the literature review, the
most significant assigned weight for the construction materials
selection might be 40\% for the financial criteria, 50\% for the
technical criteria and 10\% for the environmental constraints.

Concerning the insulating materials, the project aims to purchase
exclusively national raw materials, justifying the assignment of 40\%
for the thermal criteria, 20\% for the acoustic, 30\% for the
environmental and finally 10\% for the hygrometric criteria.

Construction materials selection

Tables 4-5 represent the normalized decision matrix of the attributes
for the construction materials. The performance score of the attributes
obtained by the WSM is indicated in Table 5.

In order to validate the performance score, the Weighted Product Method
(WPM) was adopted. It represents a modification of the WSM, relying on
the product of the normalized weights (Eq. (20)).

\(A_{i}^{\text{WSM\ score}}=\prod_{i=1}^{n}{n_{\text{ij}}}^{w_{j}},\ for\ i=1,2,\ldots n\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (20)\)

The final ranking was obtained by collecting and ranking the performance
score as shown in Table 6. Double wall in hollow brick (T8 for the
interior and T10 for the exterior) was found to be optimum attribute for
the building envelope. The same procedure has been followed for the
floor's construction material, as expanded polystyrene flooring slabs
and thermal breakers scored the best result.

Table 4: Decision matrix for the construction materials\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Attribute/ Criteria & Technical & Environmental &
Financial\tabularnewline
\midrule
\endhead
Natural stone & 6 & 8 & 2\tabularnewline
Mono wall in hollow brick & 2 & 5 & 10\tabularnewline
Double wall in hollow brick & 9 & 4 & 9\tabularnewline
Monowall brick & 10 & 3 & 1\tabularnewline
Adobe & 7 & 8 & 6\tabularnewline
Mud block & 4 & 10 & 6\tabularnewline
Concrete block & 2 & 5 & 7\tabularnewline
Hollow-core slab & 1 & 8 & 8\tabularnewline
Expanded Polystyrene flooring slabs & 8 & 7 & 5\tabularnewline
Thermal breaker in Expanded Polystyrene & 8 & 6 & 4\tabularnewline
\bottomrule
\end{longtable}

Table 5: Normalized matrix for the construction material selection\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Attribute/ Criteria & Technical & Environmental &
Financial\tabularnewline
\midrule
\endhead
Natural stone & 0,6 & 0,8 & 0,2\tabularnewline
Mono wall in hollow brick & 0,2 & 0,5 & 1\tabularnewline
Double wall in hollow brick & 0,9 & 0,4 & 0,9\tabularnewline
Monowall brick & 1 & 0,3 & 0,1\tabularnewline
Adobe & 0,7 & 0,8 & 0,6\tabularnewline
Mud block & 0,4 & 1 & 0,6\tabularnewline
Concrete block & 0,2 & 0,5 & 0,7\tabularnewline
Hollow-core slab & 0,1 & 0,8 & 0,8\tabularnewline
Expanded Polystyrene flooring slabs & 0,8 & 0,7 & 0,5\tabularnewline
Thermal breaker in Expanded Polystyrene & 0,8 & 0,6 & 0,4\tabularnewline
\bottomrule
\end{longtable}

Table 6: Performance \& Ranking of the construction materials (WSM and
validated by WPM)\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Attribute & WSM Performance score & WSM Ranking & WPM score & Validated
by WPM\tabularnewline
\midrule
\endhead
Natural stone & 4.6 & 7 & 5.0 & 6\tabularnewline
Mono wall in hollow brick & 5.5 & 5 & 5.1 & 5\tabularnewline
Double wall in hollow brick & 8.5 & 1 & 6.6 & 1\tabularnewline
Monowall brick & 5.7 & 4 & 5.3 & 4\tabularnewline
Adobe & 6.7 & 2 & 5.9 & 2\tabularnewline
Mud block & 5.4 & 6 & 5.3 & 4\tabularnewline
Concrete block & 4.3 & 9 & 4.8 & 7\tabularnewline
Hollow-core slab & 4.5 & 8 & 4.5 & 8\tabularnewline
Expanded Polystyrene flooring slabs & 6.7 & 2 & 5.9 & 2\tabularnewline
Thermal breaker in Expanded Polystyrene & 6.2 & 3 & 5.8 &
3\tabularnewline
\bottomrule
\end{longtable}

Insulating materials selection

Similarly, tables 7-8 present the decision and normalized decision
matrix for the insulating material selection. The performance score of
the attributes obtained by the WSM and validated by the Weighted Product
Method (WPM) is indicated in Table 9. The final ranking was obtained by
collecting and ranking the performance score as shown in Table 8.
Expanded polystyrene fronts was selected as it scored the best and
showed the highest performance and local availability. On the other
hand, plasterboard was found the best attribute for the acoustic
insulation of the building.

Table 7: Decision matrix for the insulating materials\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Attribute/ Criteria & Thermal & Acoustic & Resistance to moisture &
Local availability\tabularnewline
\midrule
\endhead
Glass wool & 6 & 9 & 1 & 1\tabularnewline
Rock wool & 7 & 9 & 1 & 1\tabularnewline
Cork & 5 & 8 & 10 & 10\tabularnewline
Expanded polystyrene & 9 & 2 & 8 & 10\tabularnewline
Extruded polystyrene & 8 & 2 & 8 & 1\tabularnewline
Polyurethane & 10 & 2 & 9 & 1\tabularnewline
Plasterboard & 1 & 10 & 5 & 10\tabularnewline
\bottomrule
\end{longtable}

Table 8: Normalized matrix for the insulating materials\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Attribute/ Criteria & Thermal performances & Acoustic & Resistance to
moisture & Local availability\tabularnewline
\midrule
\endhead
Glass wool & 0.6 & 0.9 & 0.1 & 0.1\tabularnewline
Rock wool & 0.7 & 0.9 & 0.1 & 0.1\tabularnewline
Cork & 0.5 & 0.8 & 1 & 1\tabularnewline
Expanded polystyrene & 0.9 & 0.2 & 0.8 & 1\tabularnewline
Extruded polystyrene & 0.8 & 0.2 & 0.8 & 0.1\tabularnewline
Polyurethane & 1 & 0.2 & 0.9 & 0.1\tabularnewline
Plasterboard & 0.1 & 1 & 0.5 & 1\tabularnewline
\bottomrule
\end{longtable}

Table 9: Performance \& Ranking of the construction materials (WSM and
validated by WPM)\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Attribute & WSM Performance score & WSM Ranking & WPM performance score
& Ranking validated by WPM\tabularnewline
\midrule
\endhead
Glass wool & 4.6 & 7 & 5.60 & 7\tabularnewline
Rock wool & 5 & 5 & 5.73 & 5\tabularnewline
Cork & 7.6 & 2 & 6.67 & 2\tabularnewline
Expanded polystyrene & 7.8 & 1 & 6.78 & 1\tabularnewline
Extruded polystyrene & 4.7 & 6 & 5.68 & 6\tabularnewline
Polyurethane & 5.6 & 4 & 5.91 & 3\tabularnewline
Plasterboard & 5.9 & 3 & 5.75 & 4\tabularnewline
\bottomrule
\end{longtable}

Following the selection of the insulating material, the required
insulating thickness needs to be estimated. This parameter is estimated
considering the material characteristics and its purchase cost, the
weather conditions of the implementation site (degree-day) and the life
time of the building. Accordingly, the optimum energetic thickness is
calculated using Eq.(21):

\begin{equation}
\begin{matrix}e_{\text{opt.ener}}=\sqrt{\frac{LC.DD.86400}{\eta}.\frac{\lambda}{E_{i}}}\ -R_{\text{i\ }}.\lambda\ \#\left(21\right)\\
\end{matrix}\nonumber \\
 \end{equation}

Where LC, DD, \(E_{i}\) represent the building lifecycle, the
degree-day and the purchase cost. \(\eta\),
\(R_{i\ }\)and \(\lambda\) represent the cost of the
heating source, the thermal resistance and the thermal conductivity.

\(\left\{\begin{matrix}Tmin\ \geq\ 26\ \ \ \ \ \ \ \ \ \ \ \ \ \ then\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ DDx\ =\ \left(\frac{Tmax\ +\ Tmin}{2}\right)\ -26\\
\ Tmin\ \leq\ 26\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ then\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ DDx\ =\ 0\\
\ Tmin\ <\ 26\ <\ Tmax\ \ \ then\ \ \ DDx\ =\ (Tmax-26)\ (0.08+0.42*(Tmax-26)\ /\ (Tmax\ -\ Tmin)\\
\end{matrix}(22)\right.\ \)

Based on the technical and financial parameters of the insulating
material (Table 10), and considering a set point temperature of 26\selectlanguage{ngerman}°C,
the calculation of the unified degree-day showed a considerable low
value during the winter season (97,41 °K) compared to the summer season
(2,376.02 °K). This leads thus to consider mainly the need to install
the insulating materials for the cooling needs of the building. Using
Eq.(21), the optimum thickness enabling to lower the heat losses to the
exterior of the building is estimated to 4 cm.

Table 10: Characteristics of the expanded polystyrene for the optimum
thickness calculation\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
Parameters & Building lifetime (years) & Cost of the heating source
(DH/kWh) & Thermal conductivity (W/m\selectlanguage{ngerman}·K) & Purchase cost
(DH/m\textsuperscript{3}) & Purchase cost
(DH/m\textsuperscript{3})\tabularnewline
\midrule
\endhead
Value & 25 & 1 & 0.029 & 750 & 0.25\tabularnewline
\bottomrule
\end{longtable}

\textbf{Energy analysis of the building}

Heat input through surface gains and air renewal

Considering the various elements of the building envelope, and based on
their heat transfer coefficients, simulation results of the surface
gains across the 4 buildings are summarized in table 11. Results show
that 43\% of the global surface gains is due to windows, with a total
heat input by transmission through the surfaces estimated of about
29.39kW/K.

Table 11: Calculation of the heat gain through surfaces of the 4
buildings\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Elements & U (W/m\textsuperscript{2}.k) & S (m\selectlanguage{ngerman}²) & Heat flux (W/K) &
Surface gains (kW/K)\tabularnewline
\midrule
\endhead
Door & 2.2 & 35.62 & 78.364 & 29.39\tabularnewline
Windows & 5.66 & 2239.44 & 12675.23 &\tabularnewline
Wall adjacent to a heated area & 0.33 & 13320.44 & 4395.529
&\tabularnewline
Wall adjacent to a non-heated area & 0.85 & 9683.32 & 8230.82
&\tabularnewline
Low-floor & 0.61 & 3069.03 & 1872.10 &\tabularnewline
Ceiling & 0.55 & 3893.97 & 2141.68 &\tabularnewline
\bottomrule
\end{longtable}

For the heat gain through air infiltration, the labor legislation
requires a 25 m\textsuperscript{3}/s air flow for each occupant in an
office space to ensure its comfort. With a total of 3194 occupants, the
total heat gain through air infiltration is estimated to 27.14 kW/K .

Heat input by solar irradiation

Considering an absorption and a reduction coefficient of 1 and 0.63,
respectively, the solar radiation intensity for each side of the
building was generated from Meteonorm software database. As the south
side features the highest DNI, the building design ensured to have the
largest glazing area south-facing. The simulation results of the solar
heat gain are presented in table 12, showing an annual heat gain of 512
kWh by the buildings through solar irradiation.

Table 12: Solar heat gain through the walls of the buildings of the
various geographic orientation\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Side\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Area(m\textsuperscript{2})\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
DNI (kWh/m\textsuperscript{2}/y)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Solar energy heat input (kWh/y)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Total heat gain (kWh/y)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
South glazing\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
859\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
537.11\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
290.66\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
511.95\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
North glazing\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
511\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
446.73\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
143.81\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
West glazing\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
111\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
449.16\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
31.40\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
East glazing\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
361\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
202.62\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
46.08\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Heat gain due to occupants and electrical devices

Considering an average sensible heat of 63W/occupant, and 59W/occupant
as a latent heat, with a total 2288 hours' occupancy per year, an annual
heat gain of global 802 kWh is calculated due to the occupant's presence
and activity.

Similarly, with a total of 3194 laptops, featuring an average power of
200 W/h and a sensible heat of 125W, an annual heat gain of 914 kWh is
estimated due to the electrical devices input.

Heat gain from lighting components

Considering the design requirements in terms of the lighting elements,
the LED panels Energy Class A (Table 13) were selected for the present
project {[}47{]}.

Table 13: Summary of the technical brochure of the selected luminaires\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Reference\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
CRI\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Initial absorbed power (W)\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
CT (k)\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Luminoux flux (Lm)\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Luminous efficiency (lm/W)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
RC091V LED36S/840 PSU W60L60 GM G2 Philips\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\textgreater{}80\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
40\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
4000\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
3600\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
90\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Considering a reflectance factor of 751, the calculation of the local
index `\emph{k'} yielded to the estimation of the utilance, which
corresponds to a value of 0.92 (Figure 4). Consequently, a global
luminous flux of 36141.3 lm is calculated, and considering the unitary
luminous flux of the selected LED panels (Table 10), a total of 10
lighting elements per working space is estimated. Table 14 summarizes
the number of luminaires required for all the working spaces of the 4
buildings, with the 3-D lighting distribution using DIAlux software
{[}48{]} is presented in Figure 4. This simulation on DIAlux validates
the design of the lighting elements based on the Standard NBN-EN 124
64-1{[}49{]}. Finally, Hence, an annual heat gain through lighting is
estimated to achieve 100 kWh.

Table 14: Total number of luminaires for the lighting requirements for
the 4 buildings\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& Area (m\textsuperscript{2}) & Number of luminaire per working space &
Number of working spaces & Global luminaires needed\tabularnewline
\midrule
\endhead
Global area of the 4 buildings & 26292.27 & 10 & 553 &
5535\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 5: 3D light distribution in the working space using DIALUX
software

Cooling and heating load of the building

With an annual heating degree-day of 97.41 \selectlanguage{ngerman}°K, and considering a heating
reduction coefficient of 0.27, table 15 summarizes the heating need for
the project. The simulations showed that an annual 0.57
kWh/m\textsuperscript{2} is estimated for the buildings.

As the cooling need is more prominent considering the meteorological
conditions of the project, with an annual degree-day of 2376 °K and
effective cooling time of 1643 hours, table 16 shows the necessary
cooling requirement of the building, considering the heat input and heat
losses. Results showed that an annual cooling load of 36.87
kWh/m\textsuperscript{2} is required to ensure a fresh ambiance to the
occupants.

Table 15: Heating needs of the 4 buildings\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Heat gain & Flux (kW/K) & Heating need (kWh/y) & Global heating need
(kWh/m\textsuperscript{2}.y)\tabularnewline
\midrule
\endhead
Surface heat gain & 29.39 & 18551.46 & 0.57\tabularnewline
Air renewal heat gain & 27.14 & 17131.22 &\tabularnewline
\bottomrule
\end{longtable}

Table 16: Summary of the cooling energy requirement of the 4 buildings\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Flux (kW/K)\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Heat need (GWh/y)\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Heat flux (GWh/y)\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Required cooling need (Gwh/y)\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Global cooling need (kWh/m\textsuperscript{2}.y)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Surface gains\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
29.4\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1675,95\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1190\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
2.29\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
36.86\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Ventilation gains\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
27.1\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1547,64\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
1099\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Solar heat gain by glazing\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.51\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.363\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Internal gains due to occupants\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.8\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.569\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Equipment gains\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.9\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.648\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Lighting gains\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.099\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0.07\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

The obtained results of the building thermal performances showed that
the total energy requirement necessary for the comfort of the occupants
complies with the requirements of the local construction standards,
since the annual energy requirement of the present project of
37.45kWh/m\textsuperscript{2} remains below its set value of
45kWh/m\textsuperscript{2} per year (figure 5); whereas the main energy
requirement for the building is dedicated to air cooling.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 6: Representation of the energetic balance of the building,
showing the cooling and heating requirements compared to the regulation
reference value

\textbf{Solar PV panels design}

Design of Solar panels

The second step during the exploitation stage consists in integrating PV
panels for the building's electrical supply. The design of the PV panels
should be based on the least favorable conditions, that is the lowest
DNI registered for the city, to ensure a continuous power supply for the
building needs particularly during the winter period. Considering the
annual meteorological data of the city, the minimal solar irradiance is
observed in December, with a value of 4.51 kWh/m\textsuperscript{2}/day
{[}50{]}.

A benchmarking of the various PV cells available on the market showed
that the Polycrystalline PV panels constitute the most consolidated and
tested photovoltaic technology. Hence, this technology was selected to
supply the electrical need of the building. In this sense, JASOLAR PV
panels with a nominal peak power of 550Wp were used, as they offer
financial and technical advantages {[}51{]}.

Based on the energetic requirement of the building and the solar
irradiance, the required peak power for each building was estimated, as
shown in Table 17. The number of PV panels was afterwards estimated and
the simulation results are presented in Table 18. A maximum of 1012
panels is required for the 4\textsuperscript{th} building as its
energetic need is the highest.

Table 17: Peak power calculation for each building\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
& Energy need (kWh/day) & Solar irradiance
(kWh/m\textsuperscript{2}.~day) & Peak power (kWp)\tabularnewline
\midrule
\endhead
Building N\selectlanguage{ngerman}º1 & 1592.70 & 4.51 & 353.14\tabularnewline
Building N\selectlanguage{ngerman}º2 & 1669.92 & & 370.27\tabularnewline
Building N\selectlanguage{ngerman}º3 & 1821.74 & & 403.93\tabularnewline
Building N\selectlanguage{ngerman}º4 & 2504.81 & & 556.62\tabularnewline
\bottomrule
\end{longtable}

Table 18:Calculation of the required number of PV panels\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
& Peak power (kWp) & Nominal peak power of the PV panel (Wp) & Number of
PV panels\tabularnewline
\midrule
\endhead
Building N\selectlanguage{ngerman}º1 & 353.14 & 550 & 609\tabularnewline
Building N\selectlanguage{ngerman}º2 & 370.27 & & 673\tabularnewline
Building N\selectlanguage{ngerman}º3 & 400 & & 727\tabularnewline
Building N\selectlanguage{ngerman}º4 & 556.62 & & 1012\tabularnewline
\bottomrule
\end{longtable}

Required area for solar panels

To ensure taking advantages of the best sunshine conditions, the PV
panels should be installed tilted. As the panels are intended to be
installed on the roof of each building, the panels are fixed to a
load-bearing structure at with a tilt angle of 30\selectlanguage{ngerman}º, yielding to minimize
the wind's load and the shading between the rows. Table 19 shows the
required area for the PV panels to be installed, which can clearly be
fitted on the roofs of each building. This on-roof technique ensures at
the same time a shading effect for the building, as it enables lower the
heat input to the building's ceiling, yielding to reduce the cooling
need of the building. It also enables to reduce the installing area
issue related to solar technology, as the available space for their
implementation constitutes the major limitation.

Table 19: Calculation of required area for PV panels installation\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& Roof area (m\textsuperscript{2}) & Area of the PV panel
(m\textsuperscript{2}) & Number of PV panel & Required area for the PV
panels (m\textsuperscript{2})\tabularnewline
\midrule
\endhead
Building N\selectlanguage{ngerman}º1 & 1675.10 & 2 & 609 & 1218\tabularnewline
Building N\selectlanguage{ngerman}º2 & 1756.63 & & 673 & 1346\tabularnewline
Building N\selectlanguage{ngerman}º3 & 1741.00 & & 727 & 1454\tabularnewline
Building N\selectlanguage{ngerman}º4 & 2511.31 & & 1012 & 2024\tabularnewline
\bottomrule
\end{longtable}

Optimization of the building' energy need

The calculation of the required area for PV panels installation (table
19) shows that almost 80\% of the roof area is occupied by the PV
panels. This affects directly the available solar radiation for the last
floor of the building as the shading effect gets significant. In this
sense, the last floor of the building receives less external heating
flow, leading to reduce its energy need (heating and cooling load). A
literature review of the shading effect on the energy load due to PV
panels setup on the building rooftop showed a significant reduction of
the energy need of 40\% for the adjacent floor, namely the last floor of
the building {[}52-54{]}.

Considering the energy need reduction for the last floor of the
building, the building is clearly optimized in both its energetic need
(heating and cooling load) and the storage batteries. Table 20 showed
the optimized energy need of the building, taking into account the
shading effect from PV panels setup on the rooftop. It is clear that the
global energy need of the buildings has been reduced, showing an average
reduction of 6\%.

Table : Optimized energy need of the buildings considering the shading
effect from PV panels setup\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& Building N\selectlanguage{ngerman}°1 & Building N\selectlanguage{ngerman}°2 & Building N\selectlanguage{ngerman}º3 & Building
N\selectlanguage{ngerman}º4\tabularnewline
\midrule
\endhead
Energy need (kWh/day) & 1592.70 & 1669.92 & 1821.74 &
2504.81\tabularnewline
Optimized energy need (kWh/day) & 1501.7 & 1574.5 & 1717.6 &
2361.7\tabularnewline
\bottomrule
\end{longtable}

Optimal sizing of the storage battery

Sizing the storage battery is essential to ensure a continuous
electrical power of the building, either on cloudy days or during the
night. Considering the various types of the storage batteries, the
lithium batteries has shown to be the best solution. Hence, they were
selected for the building's need, featuring a nominal capacity and rated
voltage of 3.55kAh and 48V, respectively, for a single battery {[}55{]}.

Table 21 presents the design of the required storage battery capacity
and the number of batteries. For instance, the building N\selectlanguage{ngerman}°4 requires a
total battery capacity of 78.2 kAh, and considering the nominal capacity
of 3.55kAh of a single battery, the number of required battery is 22
(Eq.(19)).

The comparison between the initial design and the optimized design shows
that the battery capacity is clearly reduced when considering the
shading effect from PV panels. In this sense, an average reduction of
10\% for the battery capacity is observed when the shading effect is
taken into account. In addition, for the 4\textsuperscript{th} building,
a maximum of 35 batteries is required in the optimized design versus 37
batteries if no shading effect was considered. It is clear that the
shading effect from PV panels has impacted the storage batteries design,
yielding to lower the purchase cost.

Table : Optimized design of the storage battery capacity of the
buildings\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
& & Building N\selectlanguage{ngerman}º1 & Building N\selectlanguage{ngerman}º2 & Building N\selectlanguage{ngerman}º3 & Building
N\selectlanguage{ngerman}º4\tabularnewline
\midrule
\endhead
Initial design & Energy need (kWh/day) & 1592.70 & 1669.92 & 1821.74 &
2504.81\tabularnewline
& Battery capacity (kAh) & 82.95 & 86.97 & 94.88 & 130.45\tabularnewline
& Number of batteries per pack & 24 & 25 & 27 & 37\tabularnewline
Optimized design (PV panels shading effect considered) & Energy need
(kWh/day) & 1501.7 & 1574.5 & 1717.6 & 2361.7\tabularnewline
& Battery capacity (kAh) & 78.2 & 82 & 89.5 & 123\tabularnewline
& Number of batteries per pack & 22 & 23 & 25 & 35\tabularnewline
\bottomrule
\end{longtable}

\textbf{Conclusion}

Developing sustainable buildings is becoming increasingly common to
tackle the energetic and environmental issues raised by the building and
construction sectors, which are considered as an energy-intensive
activity responsible of considerable greenhouse emissions and solid
waste. In this paper, the design of a sustainable office building
considering its the life cycle assessment (both construction and
exploitation stages) is investigated. In this regard, the sustainability
during the construction stage requires the selection of the best
construction and insulating materials offering high energetic
performance, while the exploitation stage sustainability involves the
integration of renewable energy resources for the building's power
supply. To achieve this objective, the Weighted Sum Method was adopted
for its simplicity and reliability to select the best choice among
various alternatives (for ceiling, walls and insulating materials), with
consideration to the technical, environmental and cost constraints
during the construction stage. Followed by the exploitation stage, the
rooftop PV panels were selected to power the electrical need of the
building. For this, an energetic analysis of the building's performance
was carried out to estimate the energetic consumption of the building,
which enables to design the photovoltaic panels and storage battery.

Hence, the major findings are as follows:

\begin{itemize}
\tightlist
\item
  During the construction stage, the material selection criteria and
  weights were based on the engineer's experience and an exhaustive
  literature review, indicating a weight vector of 50\%, 40\% and 10\%
  for the technical, financial and environmental criteria respectively,
  when selecting the construction materials. Similarly, for the
  insulating materials which selection required the use of national raw
  products, a weight vector of 40\%, 30\%, 20\% and 10 was considered
  for thermal, environmental, acoustic and hygrometric criteria,
  respectively.
\item
  Considering the Weighted Sum Method, and validating the obtained
  results by the Weighted Product Method (WPM), the best attribute for
  the construction materials that scored the best were double wall in
  hollow brick and floors built using expanded polystyrene and thermal
  breakers. Similarly, for the insulating materials, expanded
  polystyrene fronts along with plasterboard for the acoustic insulation
  of the building ranked first in the decision matrix.
\item
  During the exploitation stage, the heat balance of the building
  indicated an annual energy need of 37.44 kWh/m\textsuperscript{2}, of
  which 0.57 kWh/m\textsuperscript{2} and 36.87
  kWh/m\textsuperscript{2}attributed to heating and air cooling
  requirement, respectively. The building's energy need remains below
  the limit value of the local thermal regulation
  (45kWh/m\textsuperscript{2}), showing clearly that the building's
  sustainability is achieved.
\item
  The last step for the exploitation stage sustainability concerned the
  solar PV panels adoption to generate the electrical need of the
  building. Located on the rooftops, an average peak power of 400kWp is
  estimated for each building requirement. This peak power involves the
  setup of 609 PV panels with a global area of 1218 m\textsuperscript{2}
\item
  \textbf{Limitations and future work}
\end{itemize}

The findings from this research are applicable for office buildings
located out-of-town, where no adjacent buildings exit. This implies
dismissing the shading impacts from adjacent buildings. Our forthcoming
research will concentrate on considering this effect for a broad
generalization of the results.

Finally, the study has limitations and assumptions that can be addressed
in future studies, including the wind flow pattern on the building
performances and the maintenance/cleaning of the PV system.

\textbf{Data Availability Statement}

All data, models, and code generated or used during the study appear in
the submitted article

\textbf{Declaration of competing interest}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

\textbf{Nomenclature}\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
a & Length & m\tabularnewline
b & Width & m\tabularnewline
DD & Degree day & \selectlanguage{ngerman}°K.day\tabularnewline
e & Thickness & m\tabularnewline
E & Level of illumination & lx\tabularnewline
\(E_{p}\) & Peak power & kW\textsubscript{c}\tabularnewline
H & height & m\tabularnewline
I & Solar irradiance & kWh/ m\textsuperscript{2}.y\tabularnewline
K & Local index & (-)\tabularnewline
LC & Life cycle & years\tabularnewline
LH & Latent heat & W\tabularnewline
Q & Heat flux & W/\selectlanguage{ngerman}°K\tabularnewline
q\textsubscript{v} & Air flow rate &
m\textsuperscript{3}/h\tabularnewline
\(R_{i}\) & Heat resistance &
m\textsuperscript{2}.\selectlanguage{ngerman}°K/W\tabularnewline
S & Area & m\textsuperscript{2}\tabularnewline
SH & Sensible heat & W\tabularnewline
T & Temperature & \selectlanguage{ngerman}°K\tabularnewline
U & Heat transfer coefficient & W/m\textsuperscript{2}.\selectlanguage{ngerman}°K\tabularnewline
\textbf{Scripts} & \textbf{Scripts} & \textbf{Scripts}\tabularnewline
equip & Equipment &\tabularnewline
light & lighting &\tabularnewline
min & Minimum &\tabularnewline
max & maximum &\tabularnewline
occup & Occupants &\tabularnewline
opt & Optimum &\tabularnewline
sol & Solar &\tabularnewline
surf & Surface gains &\tabularnewline
vent & Ventilation &\tabularnewline
\textbf{Abreviations} & \textbf{Abreviations} &
\textbf{Abreviations}\tabularnewline
CRI & color rendering index &\tabularnewline
CT & color temperature &\tabularnewline
MCDM & multi criteria decision making &\tabularnewline
WSM & Weighted Sum Method &\tabularnewline
WPM & Weighted Product Method &\tabularnewline
\textbf{Greek letters} & \textbf{Greek letters} & \textbf{Greek
letters}\tabularnewline
\selectlanguage{greek}α & Absorption coefficient & (-)\tabularnewline
\selectlanguage{greek}λ & Thermal conductivity & W/m.\selectlanguage{ngerman}°K\tabularnewline
\selectlanguage{greek}η & Reduction coefficient & (-)\tabularnewline
\selectlanguage{greek}Δ\selectlanguage{english}t & Hours occupancy & h\tabularnewline
\(O_{T}\) & Luminous flux & lm\tabularnewline
\selectlanguage{greek}δ & depreciation factor & (-)\tabularnewline
\selectlanguage{greek}ζ & Efficiency of Lighting elements & (-)\tabularnewline
\bottomrule
\end{longtable}

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