







































R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 
21-35 

21 

 

 

 

Article 

Simulation and analysis of energy consumption in 

all types of residential complexes and choosing the 

best form from the perspective of sustainability 
Rahim Zahedi1*, Alireza Kashani1, Sajad Qezelbigloo2, Soheil Hashemi1 

1Department of renewable energies and environment, University of Tehran, Tehran, Iran 
2School of automotive Engineering, Iran University of Science and Technology, Tehran, Iran 

               A R T I C L E   I N F O 
 

Article history: 
Received 10 December 2024  
Received in revised form 
14 January 2025 
Accepted 27 January 2025 
 
Keywords:  
Building arrangements, Solar thermal system,  
PSI method, HVAC simulation 
 
*Corresponding author 
Email address: 
rahimzahedi@ut.ac.ir 
 
 
DOI: 10.55670/fpll.fusus.3.1.3 
 

A B S T R A C T 
 

Energy demand in residential buildings is growing with the immigration of 

people to urban areas. This study simulates and analyses five different types of 

residential buildings. The possibility of using a solar thermal system is studied, 

and then five choices are ranked with the PSI method, which is a mathematical 

approach. For HVAC simulations, Design builder software, and solar 

simulations, T*Sol software is used. The results show that in terms of heating 

load, towers and skyscraper types of residential buildings demand more energy, 

with 3.67 MW and 3.62 MW, respectively. In terms of cooling, towers and 

surrounding types need bigger values than others, with 1.84 MW and 1.82 MW, 

respectively. Solar simulations indicate that the highest solar fraction with no 

area limitations belongs to the sky scrapper type with 26.9 percent, while 

collector efficiencies of all types are between 9.9 and 11.6 percent. However, 

with rooftop areas in each type, the highest solar fraction belongs to linear and 

surround types both with 24.6 percent. Mathematical analysis shows that by 

taking into account the importance of heating load and solar fraction for all 

types, the best form of residential buildings to use is a mixed type with the first 

rank. 

 

1. Introduction 

1.1 The importance of urban energy consumption and 

methods of analysis 

According to the probable scenario, more than 80% of 

the world's population will live in cities by 2050 [1]. About 

two-thirds of the world's energy consumption comes from 

cities. For this reason, cities have a significant role in the 

consequences of energy consumption, including climate 

change, and therefore, optimization in them can have a great 

impact on achieving the environmental goals set in 

international agreements [2]. Buildings in cities account for 

more than 40% of energy consumption. For this reason, to 

reduce greenhouse gases to the desired amount, special 

attention should be paid to this sector [3]. Recent research 

shows that urban design can positively affect energy 

consumption, such as the distribution of buildings and urban 

areas, maximum use of sunlight, and the development of 

multi-use areas [4]. In regions such as Asia, the Middle East, 

and Africa, where populations are growing rapidly, the 

compact urban form combined with transportation planning 

can encourage crowding and prevent high carbon emissions 

during travel. Therefore, in addition to the fact that in densely 

populated areas, higher density is inevitable, in terms of 

energy consumption and carbon emissions will be better than 

scattered urban patterns. Therefore, special attention to 

urban residential complexes is of particular importance. With 

proper design and proper layout of complexes, energy 

efficiency can be increased desirably [5]. In recent years, 

energy modeling of urban buildings has been recognized as a 

new approach to identifying, supporting, and improving 

sustainable urban development plans and energy 

optimization measures in cities. With the help of this tool, a 

better understanding of the general situation of energy 

consumption in the building and applying design 

modifications can be used to achieve more favorable 

conditions. Because of this, various models and tools have 

been developed and become more advanced hybrid models 

[6]. Designing and operating urban buildings as a group (from 

Future Sustainability 

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R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

22 

 

a city block to a district to an entire city) rather than as single 

individuals requires simulation and optimization to account 

for interactions among buildings and between buildings and 

their surrounding urban environment, and for district energy 

systems serving multiple buildings with diverse thermal 

loads across space and time [7]. Regulations corroborate the 

importance of retrofitting existing building stocks or 

constructing new energy-efficient districts. Thus, there is a 

need for modeling tools to evaluate energy scenarios to 

manage better and design cities, and numerous 

methodologies and tools have been developed [8]. Research 

activities in this field have flourished in recent years and have 

created a stronger urban database that leads to GIS, light and 

range detection, and building hourly energy demand profiles 

for current and future conditions. This is a testament to the 

importance of modeling urban buildings. Depending on the 

availability of energy consumption data for historic buildings, 

a variety of modeling, simulation, and calibration methods, as 

well as applications, have been proposed [9]. Researchers 

worldwide are working on energy modeling and control to 

develop strategies that lead to an overall reduction in building 

energy consumption. One of them is developing control 

strategies and an efficient computational energy model for 

the studied building. Modeling methods for modeling the 

energy systems of buildings have been developed and 

adopted and have shown their ability to provide more 

accurate and comprehensive information about buildings 

[10]. 

1.2 Energy supply and sectors 

Today, the most usable and economical forms of energy 

are fossil fuels, especially oil products and natural gas [11]. 

The importance of using renewable energy is improving due 

to the increasing use of energy and the fact that these forms 

of energy are not renewable. On the other hand, the means of 

effective energy use are vastly considered and so are being 

researched often. This caused broader and more thorough 

studies of energy use that have led to the study of sectors 

including residential, hospital, commercial, official, industry, 

and transportation. 

1.3 Residential sector 

The major use of energy in OECD countries belongs to the 

industry sector. However, in non-OECD countries, the major 

use of energy is considered for the residential sector [12]. 

From a different point of view, oil-exporting countries have a 

lower price of energy use because of the abundance of energy 

supplies. However, the performance of energy-related 

machines is not usually optimal. Immigration to bigger cities 

exists because of the location of major facilities in these cities 

and more work opportunities. So, one of the leading 

residential solutions to accommodate people is using 

residential complexes. Thus, in non-OECD and oil-exporting 

countries, the importance of energy use optimization and 

renewable energy studies are hugely favorable, especially for 

the residential sector and, in big cities, for residential 

complexes. 

1.4 Solar energy 

Solar is one of the renewable energies which, because of 

numerous advantages, is considered recently to supply the 

energy need. One of the main advantages of using solar energy 

is the absence of much pollution that fossil fuels emit [13]. 

However, there are some disadvantages including timing and 

climatic limitations, storage, and expensive equipment which 

caused researchers to study these systems more and more 

recently. There are multiple parameters to classify solar 

energy; but mainly, it is divided into two parts of active and 

passive solar energy. Passive solar is when there is no solar 

energy equipment used and solely by architectural means, the 

energy is stored and eventually used. However, active solar 

always has energy-gaining and systematic equipment to 

procure the energy needed. The active systems can be divided 

into space heating, domestic hot water heating, electricity 

supply, desalination, and solar dryers. Buker et al. [14] 

reviewed the applications of building integrated solar 

thermal collectors in their paper. Based on the scenarios 

reviewed in the paper, passive solar heating combined with 

building construction and energy-efficient applications can 

reduce space heating demand by 30%. On the other hand, 

active solar systems can reduce fuel demand for hot water 

and space heating from 50% to 70% for hot water and 40% to 

60% for space heating. It is also estimated that about 30-40% 

of global heat demand can be met with solar thermal energy 

and 20% of Europe's heat demand. There are many types of 

thermal collectors, but their applications remain limited due 

to reliability, cost, and building integration issues. Therefore, 

significant research is needed mainly in heat absorber design 

and construction, material and coating selection, energy 

conversion and effectiveness, cost reduction, performance 

testing, system control, and building integration facilities. 

Therefore, the use of collectors, along with optimization in 

their design and usage, can play a significant role in energy 

efficiency. Karami et al. [15] investigated residential buildings 

as one of the largest energy consumers due to their valuable 

potential for energy savings. They specifically looked at the 

combined solar thermal systems that supply the energy 

needed for domestic hot water and space heating and 

evaluated their key role in reducing building energy 

consumption. They investigated the effect of climatic 

conditions on the thermal performance of a hybrid solar 

system using dynamic simulation by TRNSYS. For this 

purpose, the performance of the system in five different 

climate zones, including hot-dry, cold-dry, medium-humid, 

hot-semi-humid, and hot-humid, has been considered. Based 

on the obtained results, the energy needed for hot water 

consumption in all climatic regions except for the temperate-

humid and cold-dry climate regions can be supplied to a large 

extent through solar energy. Their findings confirmed that the 

energy consumption of the building could be significantly 

reduced by using the combined solar system as a heating 

system, resulting in significant energy and economic savings. 

Qerimi et al. [16] investigated the use of solar energy for 

building hot water supply in Kosovo. Since the electricity 

produced in most of the electricity produced in Kosovo is 

produced from fossil fuel, the use of renewable energy, 

especially in buildings, was considered one of the promising 

solutions to save non-renewable resources. About 41.4% of 

the total consumption in Kosovo, 15% of this energy is used 

for domestic hot water. This energy demand can be 

significantly reduced by using improved building 

construction techniques and the use of RES sources, 

especially solar heat. For the cases they chose in their work, 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

23 

 

they obtained data related to solar fraction, solar 

contribution, CO2 avoided, collector temperature, financial 

analysis, etc., using TSOL 2018 software. They proposed 

replacing conventional water heaters with domestic solar 

water heaters (DSWH). The results of this paper show that 

DSWH is economically feasible in Pristine and can lead to fuel 

savings and CO2 emission reduction. 

Tang et al. [17] investigated the use of solar energy to 

heat water in residential buildings. They said that in South 

Africa (SA), up to 40% of household energy consumption is 

used for water heating, and in this regard, the use of 

renewable energy, especially solar energy, can help reduce 

the energy crisis in this country. In their study, they 

investigated the use of solar water heaters (SWH) at the 

household scale for the first time using climate data for 21 

cities in South Africa. The technical and environmental 

evaluation was performed by TSOL PRO 5.5 on two types of 

an evacuated tube (ET) and flat plate (FP water heater). In 

addition, these cities were ranked using GAMS 24.1 and two 

types of DEA methods. The results indicate that the efficiency 

of evacuated tube SWHs is better than flat plate SWHs in all 

cities and if we use an FP water heater, the average solar 

fraction is 95.93%, which avoids the emission of about 23.5 

tons of CO2 annually. These values for ET water heaters are 

99.16% and 24.4 tons per year, respectively. Therefore, the 

results confirmed that the use of solar collectors can make a 

significant contribution to providing the heat needed by 

households. Supplying sufficient electrical energy while 

reducing greenhouse gas emissions is one of the major 

concerns of policymakers and scientists all over the world. In 

Saudi Arabia, local authorities are increasingly aware of the 

necessity of reducing the environmental impact of 

nonrenewable energy by exploring alternative sustainable 

energy sources and improving buildings' energy efficiency. 

Recently, building-integrated photovoltaic (BIPV) technology 

has been regarded as a promising technology for generating 

instantaneous sustainable energy for buildings. To achieve a 

substantial contribution regarding zero energy buildings, 

solar energy should be widely used in residential buildings 

within the urban context [18]. 

Due to the nature of the problem investigated in the 

present paper, where various technical and economic criteria 

are discussed, a method to optimize the selection is used. The 

multi-criteria optimization problem for the solution using the 

PSI (Parameter Space Investigation)-method is formulated as 

a generalized problem of nonlinear optimization [19]. 

Different attributes of building types, including orientation, 

size, windows and doors areas, etc., were studied before 

architecturally. However, the impact of most of these 

attributes on energy consumption has not been studied. In 

this study, the impact of five types of buildings on energy 

consumption and solar micro-generation is investigated. In 

this research, the simulation, optimization, and analysis are 

done for different forms of residential complexes and also the 

possibility of using solar energy is studied. Although simple 

architecture is used for each apartment in all of the buildings, 

the arrangement of these apartments is different in each case. 

So, the novelty of this study is that one would be able to decide 

which type of building is the best to build in terms of energy 

based on four main parameters of heating load, cooling load, 

solar fraction, and collector efficiency. 

2. Literature review 

Wang et al. [20] Studied the effect of urbanization on 

residential energy consumption. Using panel data from 136 

countries between 1990 and 2015, they examine the impact 

of urbanization on residential energy consumption around 

the world, and how the impact varies from region to region, 

taking into account regional heterogeneity and stages of 

urbanization. Our findings show that the impact of 

urbanization on residential energy consumption in different 

areas at different stages of urbanization is very different. Most 

sub-Saharan Africa is in the process of accelerating 

urbanization, characterized by rapid population migration to 

urban areas without economic growth. This feature of 

urbanization leads to a reduction in total consumption. In 

contrast, urbanization in developing regions in Asia and the 

Middle East, and North Africa, coupled with emerging 

economies, could increase total residential energy 

consumption. Surprisingly, for highly urbanized areas, 

including the developed regions of the world, Latin America 

and the Caribbean, and developing regions in Europe and 

Central Asia, the impact of urbanization is due to the small gap 

between urban and rural energy consumption in the 

residential sector is based on these findings. , We offer four 

key policy proposals, including evaluating the financial 

viability of cost-benefit home energy transmission plans, 

developing a set of custom options for home energy use, and 

the regular transition process, encouraging bottom-up plans 

for adoption. Clean energy in the residential sector, and 

sharing a public monitoring and planning platform. 

Accordingly, the importance of using tools such as software 

modeling of urban residential neighborhoods, which are the 

main components of cities, becomes more apparent. Given 

that standards are usually observed in the design and 

construction of any building, what can be further examined is 

the juxtaposition of several buildings and their impact on the 

use of natural energy, such as wind and solar. Be. Therefore, 

the study of a single building alone cannot provide a correct 

understanding of the state of energy demand as well as 

possible optimizations in urban areas. 

Bahgat et al. [21] Presented a classification based on the 

urban characteristics of open spaces (urban valley urban 

pattern, building distribution, and outdoor shape) and energy 

consumption and thermal comfort, which also took into 

account the effect of vegetation and complementary 

materials. Also, the optimal value of the mentioned features 

was developed to achieve the desired urban features. Urban 

characteristics of open spaces and their optimal values in the 

five main urban patterns of residential complexes (block, 

staircase, courtyard, staircase, and linear) in two climatic 

regions, hot, dry, and hot humid, which can be used as a guide-

based urban model. Used energy and comfort. Urban planners 

and planners can use this to select the most appropriate 

urban features according to their preferred weather 

conditions and urban patterns in residential complexes (such 

as block, stair, court, stair, and linear). Urban valley, density, 

distribution of buildings, and the shape of space and their sub-

characteristics help to achieve energy-efficient and 

comfortable outdoor spaces. Determining these features by 

observing the values according to the urban design guide, 

which is based on studies conducted in this field, will 

guarantee welfare and comfort. In this paper, the effect of 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

24 

 

these factors was examined by quantitative and specific 

criteria. Reinhart et al. [22] Reviewed various building energy 

modeling methods. Their findings indicate that significant 

progress has recently been made toward the development of 

simulation workflows to estimate the overall energy 

consumption of operational buildings across neighborhoods. 

Given the insights that can be gained from such simulations 

for planning, design, and policy decisions, the level of effort 

required to set up and implement such models seems 

justifiable. However, several challenges remain for UBEM 

(Urban Building Energy Modelling) to differentiate itself as a 

reliable urban planning tool. The greatest residual 

uncertainty for UBEM simulations is related to the precise 

definition and description of ancient types that reliably 

represent a building warehouse. Due to the very limited 

access to building energy consumption measurements and 

also the general lack of knowledge about the thermal 

properties of buildings, it is often not possible to estimate the 

simulation uncertainty nor to calibrate a UBEM to reduce the 

error. To address this problem, model makers need access to 

building energy audit data as well as measured energy 

consumption in selected and audited buildings. While privacy 

concerns often prevent companies from sharing such 

datasets, some companies have begun to build in-house 

calibrated UBEMs to predict future demand profiles. The 

resulting archetype patterns do not violate anyone's privacy 

and can, therefore, be shared with the public. Some city and 

state governments, representing another key stakeholder 

group, have already enacted laws requiring the use of building 

energy from selected types of buildings to make them public. 

Franco et al. [23] Examined India as the world's fastest-

growing economy and home to nearly one-fifth of the world's 

population to highlight the importance of urbanization to 

energy consumption. Urbanization improves the quality of 

life of the people and, at the same time, promotes economic 

growth. However, it also increases energy consumption and 

can cause an energy crisis. Urbanization also has a significant 

effect on carbon dioxide (CO2) emissions. They empirically 

examined the temporal, dynamic, and causal relationships 

between urbanization, energy consumption, and emissions. 

Increased energy consumption and greenhouse gas emissions 

are also being considered in the context of rapid urbanization. 

To address these problems, the study recommends a set of 

measures and a set of strategies, including measures to 

reduce energy intensity and emission intensity through 

continuous monitoring, information feedback systems, the 

introduction of industrial energy quota management, and 

incentives for facilities. Energy efficiency is turning off 

inefficient devices. Installation and commissioning of smart 

residential buildings. Reducing distribution and transmission 

losses by investing in smart grids is also highly recommended. 

Hachem et al. [24] Presented a study of ways to increase 

energy efficiency in multi-story residential buildings. 

Montreal, Canada, was selected for this study. Energy 

performance is measured by the balance between consumer 

demand and electricity generation using integrated PV 

systems. In this study, the focus was on increasing electricity 

production by solar cells. In this study, buildings were 

considered to have very high energy efficiency and comply 

with the principles of passive solar design. The buildings 

under study included - low-rise (3-5 floors), medium (6-9 

floors), and high (up to 12 floors), with eight apartments on 

each floor. In addition to the roof, PV was used in some of the 

facades. The simulation results using the Energy Plus building 

simulation program showed that the apartments are 

generally very efficient in terms of cooling and heating, but 

their use of active solar energy is limited. In this study, they 

concluded that a three-story building could generate about 96 

percent of its total energy consumption if the roof design was 

optimized for solar energy production. On more than 3 floors, 

other measures are needed to increase energy production. 

The implementation of PV systems in 50% of the southern 

facade and 80% of the eastern and western facades, in 

addition to the advanced design of the roof surface (folding 

plate), allows the production of electricity up to 90% of the 

energy consumption of a 4-story building. This study shows 

that investing in advanced facade design (such as folding 

curtain walls) can significantly increase electricity generation 

and approach zero and surplus net energy status in buildings 

with eight floors. 

Choi et al. [25] Studied the energy consumption 

characteristics of high-rise apartment buildings through a 

series of case studies and resident surveys. They reached the 

following conclusions: (1) High-rise apartment buildings can 

be classified based on residential or mixed-use residential 

buildings and the form of the building. (2) In assessing the 

characteristics of electricity consumption based on building 

use, residents of mixed-use apartments showed more active 

heating management behavior and adjusted their indoor stay 

more actively, but they consumed more electricity, especially 

in summer than those Who live in public residential 

apartments. (3) For the characteristics of electrical energy 

consumption, according to the shape of the building, plate 

buildings consume less energy than tower-type buildings. 

And the latter consumed 1.48 times more electricity than the 

former in common areas. (4) When evaluating the 

characteristics of liquefied natural gas consumption 

according to the shape of the building, it can be seen that plate 

buildings consume 10% more gas than high-rise buildings. (5) 

CO2 in mixed-use buildings is higher than emissions in public 

residential buildings. 

Tereci et al. [26] Examined the effects of urban 

configuration, building typology, and building standards on 

energy consumption. They concluded that the density and 

material of the building cover have a significant impact on the 

energy performance of the town and should be given special 

attention in the urban design process. One of the most 

important factors in the energy demand of buildings is their 

arrangement. They looked at this and found, for example, that 

a row house in the middle of a block needed 17 percent less 

heating than a corner house. In addition, the location of the 

yards is important; Yard forms lead to so much mutual 

shading between buildings that the most deprived 

apartments with very low solar benefits require up to 80% 

more heating. If the glazing ratio increases in all facades, the 

heating demand usually increases by 10 to 20%, while the 

changes in the southern façade alone do not have a significant 

effect on the heating demand due to the balancing of profits 

and losses. In heating-dominated climates, the combined 

demand for heating and cooling energy increases slightly with 

increasing site density (6%). In climates with comparable 

heating and cooling energy demand, the optimal site density 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

25 

 

between completely shadowless open spaces and high 

density There is a site. For a given fixed-size metropolitan 

area, multi-family homes have the lowest initial energy 

demand and CO2 per capita, while single-family homes have 

the highest. Due to low density and fewer people in single-

family urban areas, absolute energy consumption and 

greenhouse gas emissions are the lowest for this urban 

structure. In general, it can be said that the results of their 

work showed that depending on the prevailing heating or 

cooling needs, the shape of the building blocks, as well as the 

appropriate type of material, will be different and for the 

construction of neighborhoods or residential complexes 

should be considered these Topics to be considered. 

Dorer et al. [27] showed in their research that for 

buildings in an urban environment (compared to 

independent buildings), urban microclimate can have a 

significant effect on heat exchange and, thus, on the energy 

demand of buildings, depending on the geometry and 

structure of the building. In the case of the presented street 

valley, the effects of solar radiation and high waves had the 

greatest impact, followed by the effects of UHI and convective 

heat exchange on both the surface and the shear layer of the 

valley to free flow. To model the climate of larger urban areas, 

a multidimensional approach was proposed, ranging from 

meteorological scale models to precise modeling of radiant 

heat exchange and convection at the micro scale, with links to 

individual buildings and surface elements in building energy 

simulation It covers the city. The results of their research also 

confirmed the importance of how buildings are located in an 

urban area. 

Hong et al. [28] examined the wind environment of the 

pedestrian surface and the thermal comfort around the 

buildings, and the wind pressure on the facade with 

numerical studies by SPOTE. It is generally assumed that 

apartments in individual buildings experience better 

ventilation with the experience of wind deflection on one 

facade and separation of airflow on the other. However, when 

buildings are grouped in different configurations, the airflow 

depends on the type of arrangement and their interactions: 

including the different patterns of building layout and 

arrangement of trees, as well as the orientation of the building 

according to the wind. From the simulated results, it is 

concluded that the high views of the building, which are 

parallel to the prevailing wind direction, can accelerate the 

horizontal eddy airflow at the edges, where such a flow can 

enhance the convective exchange efficiency of hot air. Low 

altitude and cold weather at high altitudes and a pleasant 

windy environment and thermal comfort are achieved at the 

pedestrian level. In addition, it has been observed that 

configurations with a square central space articulated by 

buildings and oriented towards the prevailing wind can be 

exposed to airflow and improve air movement. They 

quantitatively evaluated the outdoor wind environment and 

thermal comfort of the pedestrian surface around six 

hypothetical building design patterns and tree arrangements. 

From another perspective, it reflects the significant impact of 

architectural design and tree planting on the 

microenvironment around buildings. It also emphasizes the 

importance of micro-climate design, for example, conducting 

an environmental assessment of the options available in the 

building design phase and greening the landscape in a 

residential area. In addition, a pleasant outdoor heating 

environment with the shading of trees and buildings can be 

used as an additional criterion for assessing the energy 

efficiency of residential buildings. This article, with the 

approach of numerical studies, showed that the interactions 

of adjacent buildings in the designs should be considered and 

the best layout should be determined according to the 

intended conditions and objectives. 

Faizi et al. [29] Examined the orientation of the building 

as one of the most important factors affecting the rate of 

direct energy absorption. They analyzed this issue with 

Ecotect software for four types of residential buildings in 

Mehr housing complexes in Tehran, Iran, where shadows, 

solar radiation, access to light, and thermal simulation were 

analyzed. The results showed that the type 1 building (Length 

width ratio and length orientation in the north direction) has 

the best performance in terms of shade and type 2 (With an 

approximately equal length and width and an angle of 30 

degrees to the north) has the best in terms of solar radiation. 

On the other hand, buildings with a large surface area of 

translucent layers, such as windows in the south and east, can 

use more daylight to penetrate during the day. In addition, 

they made the following conclusions regarding the best 

placement model: 

• Lowest width-to-length ratio along the north 

• Having the maximum level of south-facing walls 

• Design the most transparent layers in the south, east, west, 

and north. In lateral order 

• They also suggested genres for different sections 

3. Methodology 

In this study, several different residential sites have been 

considered to simulate the energy model used. A solar 

thermal system is used in each case to supply the energy 

demand of domestic hot water. The demand-side simulation 

is done using Design Builder software, and the supply-side 

simulation is done using T-Sol software. The location of each 

building type is Edmonton, Alberta, Canada. Figure 1 shows 

the location of Edmonton City.  

 

 

Figure 1. Location of Edmonton city 

 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

26 

 

The climate in Alberta has three different regions. The 

northern part of Alberta is located in region 1, the middle part 

is located in region 2, and the southern part is in region 4. The 

city of Edmonton is located in zone 2, where the climate is 

usually cold and dry. Also, the wind speed is severe through 

the winter. So, the main design priorities conclude in 

protecting from cold air and wind during cold seasons and 

using natural ventilation in summers. The procedures done in 

this study are visible in Figure 2. As is shown, the study 

includes two sides of HVAC and solar systems. Each will be 

discussed further. 

3.1 Demand side 

Five different residential sites are considered; each has 

different properties in some categories, including shape, 

height, width, and total site area.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
Figure 2. Basic schematic of the current study 

However, the base architecture of every building at each 

site is the same to distinguish the reason for different energy 

answer characteristics based on the above categories after 

simulation. A total number of 320 identical residential units 

are considered at each site. Every single unit is either 141 m2 

or 148 m2, and 8 units are used to form a floor of residential 

buildings. The staircase area is 18 m2, and there are two sets 

of voids placed in each building, which are 10.43 m2 in case of 

area. There are four windows located at each orientation of 

each unit to gain the maximum passive solar energy needed. 

The basic architecture plan is shown in Figures 3-9 show the 

site view of each type of building and arrangement. The sites 

are categorized as Skyscraper, linear, mixed, towers, and 

surroundings. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

27 

 

 
Figure 3. The basic architecture of each floor 

 

 
Figure 4. Detailed quarter of each floor 

 

 

 
Figure 5. Skyscraper type 

 

 

 
 

Figure 6. Linear type 

 

 

 
 

Figure 7. Mixed type 

 

 
Figure 8. Towers type 

 

 

 
Figure 9. Surround type 

 

 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

28 

 

3.2 Design builder 

To calculate the energy use of each scenario, all 
mechanical and electrical simulations should be done to 
measure the related loads and then the heating and cooling 
design. Heating and cooling loads include heat transfer to or 
from one or more unconditioned zones to the conditioned 
zone through the building envelope, walls, ceiling, floor, 
doors, and windows. They also include infiltration, internal 
heat gains and losses, hot water gains and losses, solar gains, 
ventilation, etc. There are numerous types of heating and 
cooling systems to use in different kinds of buildings. The 
most common system is a boiler for heating and a chiller for 
cooling. Also, considering the usage of the building, which is 
residential in this case, scheduling is crucial in different parts 
of the system, including occupancy, HVAC, lighting, etc. [30]. 

𝑄𝐻𝑊 = 𝑐𝑝𝜌𝐻𝑊�̇�𝐻𝑊(𝑇𝐻𝑊 − 𝑇𝐶𝑊)/1000                                      (1) 

𝑄𝑆𝐻 =
𝑈𝐴̅̅ ̅̅ (𝑇𝑅−𝑇𝐴)

1000
                                                                                  (2) 

Equations 1 and 2 illustrate the loads calculated where cp is 
the specific heat coefficient (J/kg.K), ρ is density (kg/m3), V is 
the volumetric flow rate (m3/h), T is the temperature (K), U is 
the overall heat transfer coefficient (W/K.m2), and A is the 
area (m2). Subscripts HW, SH, CW, R, and A mean hot water, 
space heating, cold water, room, and ambient, respectively. 

3.3 T*Sol modelling  

To simulate the solar energy parts of the alternatives 
used in the study, a dynamic simulation is needed. T*Sol 
software is a program that allows one to accurately calculate 
the yield of a solar thermal system dynamically over the 
annual cycle. T*Sol can optimally design solar thermal 
systems, dimension collector arrays, and storage tanks. The 
software is vastly used by researchers and designers in 
numerous studies and also experimental projects. In T*Sol, 
calculations are performed based on the balance of energy 
flows and provide yield prognoses according to the hourly 
meteorological data provided. The solar collector used is a flat 
plate type, and thus, the equations will be as follows [31]. 

𝑆 = 𝐼𝑏𝑅𝑏(𝜏𝛼)𝑏 + 𝐼𝑑(𝜏𝛼)𝑑
(1+cos 𝛽)

2
+ (𝐼𝑏 + 𝐼𝑑)(𝜏𝛼)𝑔𝜌𝑔

(1+cos 𝛽)

2
           (3) 

𝐹𝑠𝑜𝑙 = 1 −
𝑄𝑎𝑢𝑥

𝑄𝑟𝑒𝑞
                                                                                     (4) 

𝑄𝑐 = 𝐴𝑐𝐹𝑅[𝐼𝑐(𝜏𝛼) − 𝑈𝑐(𝑇𝑖 − 𝑇𝑎)]                                                  (5) 

𝜂 = 𝐹𝑅(𝜏𝛼) − 𝐹𝑅𝑈𝑐(
𝑇𝑖−𝑇𝑎

𝐺𝑡
)                                                               (6) 

Where S, Q, η, F, I, R, τ, α, β, FR, and Gt are solar energy flux 
collected (W/m2), heat output (W), collector efficiency, solar 
fraction, solar radiation intensity (W/m2), fraction cosθ.cosβ 
Transmissivity factor, absorptivity factor, tilt angle (°), heat 
removal factor, and solar irradiance at the collector plane, 
respectively. Subscripts b, d, g, sol, aux, req, c, i and a means 
beam, diffuse, ground-reflected, solar, auxiliary, required, 
collector, incoming, and ambient. 

�̇� = �̇�(ℎ𝑜 − ℎ𝑖)                                                                                 (7) 

Equation 7 demonstrates energy conservation in the solar 

system. Where Q, m, ho, and hi are heat rates transferred to 

the working fluid (W), flow rate (kg/s), and outgoing and 

incoming fluid enthalpy (J/kg), respectively [31]. 

 

 

3.4 PSI method 

Because buildings may be ranked differently for different 

parameters, the PSI method is used to implement weighting 

and rank all choices accordingly [32]. Equations 8 to 12 

illustrate normalized data, standard data deviation, deviation 

difference, parameter weight, and, finally, weighted data. 

𝑅𝑖𝑗 =
𝑥𝑖𝑗

𝑥𝑗
𝑚𝑎𝑥                                                                                              (8) 

𝑃𝑉𝑗 = ∑ [𝑅𝑖𝑗 − �̅�𝑗]
2𝑁

𝑖=1                                                                        (9) 

 

𝜑𝑗 = 1 − 𝑃𝑉𝑗                                                                                          (10)  

      

𝜔𝑗 =
𝜑𝑗

∑ 𝜑𝑗
𝑀
𝑗=1

                     (11) 

 

𝐼𝑗 = ∑ (𝑅𝑖𝑗 × 𝜔𝑗)𝑀
𝑗=1                                                                          (12) 

 
 
4. Results and discussion 

4.1 Design builder 

The simulations are done using logical assumptions at 

different parts of the software. Four people in each apartment 

unit are considered. Their occupancy schedule is defined to be 

present early morning, late afternoon, and nighttime. 

Temperature preferences are indicated in Table 1.  

Table 1. Temperature assumptions 

 

Figure 10 shows the external walls consisting of 30 mm 

brick, 30 mm cement, 350 mm masonry, 50 mm polyurethane 

foam, and 50 mm gypsum plasterboard which leads to an R-

value of 3.066 m2-K/W. Also, the top floor's roof consists of 20 

mm bitumen, 150 mm MW glass wool, 200 mm air gap, and 

13 mm plasterboard which leads to an R-value of 4.162 m2-

K/W. 

 
Figure 10. External walls structure 

 

Heating 
set point °C 

Heating 
set back °C 

Cooling 
set point °C 

Cooling 
set back °C 

22 18 25 30 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

29 

 

Windows are double glazed 2×3 mm + 6 mm air gap with 

no shading and are defined into two groups of 1.5 m and 3 m 

in length. Lighting is considered to be 7.5 W/m2 in all areas 

while the working plane height is considered to be 0.8 m from 

the floor. The lighting schedule is also considered when 

needed. An HVAC system is considered for all buildings. Four-

pipe fan coils, shaped like Figure 11, are used in each 

conditioning zone. Heating is supported by a boiler(s), while 

cooling is supported by an air-cooled chiller(s). Mechanical 

and natural ventilation, domestic hot water, and control 

systems are other parts of the HVAC system. Based on the 

HVAC schedule, when there is low occupancy, the HVAC 

system reduces to 50% of the maximum capacity.  

The heating and cooling loads of each building type are 

calculated. All other assumptions are considered with the 

energy code of Canada and the software default values. 

According to Figure 12, it can be seen that the heating load is 

the highest in the case of towers, followed by skyscrapers.  

 

 
Figure 11. HVAC system diagram 

 

 

Figure 12. Heating and cooling loads 

 

The reason for this issue is the benefit of these two plans 

from sunlight. It is clear that the middle and back faces of the 

towers receive the least radiation. The proximity of the 

towers together helps to reduce the heating requirement to 

some extent, but benefiting from the energy of the sun's 

radiation is more effective. The next rank is the cooling load 

of the linear and surrounding arrangement, which is almost 

equal to each other due to the same number of floors and the 

shape of the buildings. The advantage of these two structures 

compared to towers and skyscrapers is mainly due to the 

ability to receive more energy from the sun; In addition, the 

neighborhood of the building also has a positive effect. The 

combined mode has the lowest cooling load among these 5 

modes. This arrangement has the advantages of towers and 

linear arrangement together. In this way, the combination of 

four buildings with a lower height in one row and two towers 

in the other row keeps the amount of solar energy received by 

all buildings at an optimal level, and their proximity also 

reduces cooling energy demand compared to a skyscraper.  

According to Figure 12, regarding the required cooling 

load, the arrangement in the form of towers requires more 

energy. After that, the environmental arrangement and in the 

next ranks are linear, combined, and skyscrapers. In a 

skyscraper, since there is only one roof, much less heat is 

absorbed through it than in other cases. Also, due to its height, 

during the day, more shade is created on its lower floors on 

the north side, and this also helps to reduce the need for 

cooling. In the linear layout, even though more roof surface is 

exposed to sunlight, the shading of nearby buildings protects 

many surfaces from direct radiation and reduces the need for 

cooling. In the combined mode, both the roof level is lower 

than the linear one, and we have almost the same shading 

effect compared to the linear one, and for this reason, the 

cooling load was the lowest in this mode. In the 

environmental arrangement, unlike the linear arrangement, 

more parts face direct radiation, and therefore the effect of 

the proximity of the buildings is less than in other cases, 

which has increased the need for cooling. Arrangement in the 

form of towers, although the roof area is less than the ambient 

condition, the side surfaces are more exposed to direct 

radiation, and for this reason, it requires more energy for 

cooling. 

 

 

 

 



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30 

 

Figures 13 to 17 illustrate the amount of each fuel and 

each heating or cooling gain of each building during the year. 

As shown, the amount of gas used for heating is reduced 

during warmer seasons. Where the electricity demand for 

cooling increases in the same period. The amount of heating 

needed is much more than the amount of cooling during the 

year because of the location of the project, which has a cold 

climate. Towers and mixed-type need higher values of heating 

in cold climates. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figures 13 to 17 also show the gains of each type, and it 

is obvious that the heating procedure is positive during the 

year. On the other hand, ventilation and infiltration cause a 

negative external air to gain all year. This means that the 

possibility of natural ventilation, especially in summer, is 

available, which is considered in this study. Also, the passive 

solar gain from exterior widows causes less heating needed in 

temperate months of the year. Thus, having air-sealed 

windows with no shading in most of the living areas of each 

apartment could help the heating load needed throughout the 

year; which is also considered. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A 

 

B 

 

Figure 13. Fuels (A) and heat gains (B) of Skyscraper type 

 

 

A 

 

B 

 

Figure 14. Fuels (A) and heat gains (B) of Mix type 

 

 

A 

 

B 

 

Figure 15. Fuels (A) and heat gains (B) of Linear type 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

31 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

4.2 T*Sol 

In the present study, five alternatives are simulated, and 

assumptions are indicated in Table 2. As shown in Figure 18, 

flat plate collectors are used alongside two storage tanks with 

volumes of 182 and 29 m3 and a natural gas-burning boiler. 

The working fluid in the collector loop is a mixture of 60% 

water and 40% ethylene-glycol. The space heating working 

fluid temperature is 40 °C before heat exchange and 25°C 

after heat exchange. The windows' heat flux is considered 5 

W/m2. First, the maximum solar fraction is calculated based 

on the space heating loads. Table 3 shows the value of solar 

fraction for different options. As it is known, skyscrapers have 

the highest amount.  This is because in a skyscraper that has 

a higher height, more levels of sunlight are received, and there 

is no building in its vicinity. After that, the linear, 

environmental, and combined models have the same values, 

and the towers have a lower solar fraction than the others. In 

this way, for providing heat, the skyscraper can have better 

potential and the others are in the next category. However, 

the problem is that to achieve this fraction, a larger surface is 

needed to install the collectors. The maximum solar fraction 

is yielded when there is enough surface area to accommodate 

the solar collectors. The collector required for this purpose is 

also calculated. This can be seen in Table 4.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 18. Schematic of the solar system used 

 

In this table, the level of the collector needed to achieve 

the maximum fraction is stated: the skyscraper needs the 

highest amount, and then the towers and other buildings are 

placed with almost the same values. In terms of feasibility, the 

level that the building can provide for the installation of 

collectors is important. In this article, the collectors that can 

be installed on the roof are desired, and therefore, the roof 

surface of the buildings is the available space for this work. It 

is clear that the skyscraper, despite having relatively higher 

potential, does not give many possibilities to use this potential 

 

A 

 

B 

 

Figure 16. Fuels (A) and heat gains (B) of Surround type 

 

 

A 

 

B 

 

Figure 17. Fuels (A) and heat gains (B) of Towers type 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

32 

 

due to having only one roof. Based on the structure of each 

building type, the maximum area possible for each case is 

calculated by the surface area of the rooftop. Available surface 

values for installing solar collectors are listed in Table 5. As 

expected, horizontal arrangements have the largest roof 

areas, followed by the combined towers and skyscrapers. The 

above contents are summarized in Figures 19 and Figure 20.  

 

 
Figure 19. Solar fraction based on the areas possible and needed 

 

 

 

Figure 20. Collector efficiency based on the areas possible and 

needed 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Based on both area values above for each case, the space 

heating solar fraction for each case is calculated and shown in 

Figure 19. In this Figure, the maximum amount of solar 

fraction and the amount that can be achieved based on the 

roof surface of different situations are drawn. According to 

Figure 19, it can be seen that these two values are very close 

in the linear and surrounding states, and the maximum 

amount of energy can be absorbed by the solar collectors. 

However, the distance between these two values is less in the 

compound and towers and is very large in the skyscraper. 

Also, Collector efficiency based on the areas possible and 

needed is shown in Figure 20, in which trends are as expected.  

Because of the reduction of collector efficiency by 

increasing solar fraction, the optimum amounts possible 

could be calculated considering the importance of each 

parameter to the decision-makers. Adding heating and 

cooling loads to the decision-making procedure chooses 

between scenarios even harder. A PSI method of 

mathematical optimization is considered to choose the 

building type correctly. The method automatically calculates 

the best weighting possible for each parameter and then 

ranks the choices accordingly. The parameters consist of 

heating load, cooling load, solar fraction, and collector 

efficiency. The first two parameters are cost values, and the 

latter are gain parameters. So, in order to correctly use the 

mathematical method, solar fraction and collector efficiency 

are changed to be cost parameters in the program. 

Tables 6 to 10 indicate the cost, normal, PV, weight, and 

result matrices, where parameters of heating load (HL), 

cooling load (CL), cost of collector efficiency (1-CE), and the 

cost of solar fraction (1-SF) are located in columns, and 

building types of sky scrapper (SS), mix (MI), towers (TO), 

linear (LI), and surround (SU) are located in rows. The 

amounts stated are calculated with equations 8 to 12. As can 

be seen in Table 10, the skyscraper has won the first rank. 

After that, there are, in order, the mixed arrangement, linear, 

towers, and surround. Based on this; by weighting the criteria 

in the multi-criteria ranking and the results, the skyscraper is 

selected as the optimal option.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 2. T*sol software assumptions 

Consumption 

usage 

Hot water 

temperature 
Location Climate 

Mean Outside 

temperature 

Min outside 

temperature 

Residential 50 °C 
Edmonton, AB, 

Canada 
Cold 2°C -35.64°C 

 

Table 3. Maximum solar fraction 

Building type Sky Scrapper Mixed Towers Linear Surround 

Solar fraction (%) 26.9 25.2 24.8 25.2 25.2 

 

Table 4. Collector area needed to yield maximum solar fraction 

Building type Sky Scrapper Mixed Towers Linear Surround 

Collector Area Needed (m2) 12865 9752 10413 9878 9878 

 

Table 5. Maximum area possible for the installation of collectors 

Building type Sky Scrapper Mixed Towers Linear Surround 

Collector Area Possible (m2) 1157.75 6947 4631 9262 9262 

 



R. Zahedi et al. /Future Sustainability                                                                                   February 2025| Volume 03 | Issue 01 | Pages 21-35 

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Table 6. Cost matrix 

 

Table 7. Normal cost matrix 

 

Table 8. PV cost matrix 

 

Table 9. Result weight matrix 

Weight 
Matrix 

HL CL 1-CE 1-SF 

0.251 0.250 0.247 0.252 

 

Table 10. Result matrix 

Gain 
Rank 

Result 
Matrix 

HL CL 1-CE 1-SF Sum 

1 SS 0.25 0.227 0.209 0.245 0.93 

2 MI 0.24 0.23 0.241 0.25 0.96 

4 TO 0.25 0.25 0.23 0.252 0.98 

3 LI 0.24 0.235 0.247 0.25 0.97 

5 SU 0.24 0.248 0.247 0.25 0.98 

 

Although, decision makers can have different weighting 

preferences considering the location of the project or fuel-

related and renewable energy policies. Thus, different 

weightings can also be considered. The choice of one could be 

the most important of heating load and solar fraction. The 

results are calculated in Tables 11 and Table 12. As can be 

seen in Table 12, the ranking has been changed, and the 

skyscraper is second. The first ranks belong to the mixed 

arrangement. Others also changed and respectively are linear, 

surround, and towers. It shows that according to the 

condition and priorities in a different situation, in which 

weights are different, rankings can vary. But by comparing 

Table 10 and Table 12 we can see that the two first rankings 

are similar, but the order is changed which shows that those 

are most probably the best options. 

Table 11. Preference weight matrix 

Weight 
Matrix 

HL CL 1-CE 1-SF 

0.5 0.1 0.1 0.3 

 

Table 12. Preference result matrix 

Rank 
Result 
Matrix 

HL CL 1-CE 1-SF Sum 

2 SS 0.49 0.0907 0.0843 0.292 0.96 

1 MI 0.47 0.0922 0.0975 0.298 0.959 

5 TO 0.5 0.1 0.0932 0.3 0.993 

3 LI 0.48 0.0941 0.1 0.298 0.969 

4 SU 0.48 0.0993 0.1 0.298 0.974 

 

5. Conclusions 

In this paper, the issue of energy in the building was 

investigated. As one of the largest energy consumers and 

greenhouse gas emitters, the residential sector needs special 

attention in terms of improving the energy consumption 

situation. Considering the general trend of the world towards 

the rapid growth of urbanization, which will mainly be in 

residential complexes, the examination of these complexes 

has become one of the important matters in the field of 

energy. In line with the present article, the literature on the 

subject was reviewed and the various trends that were 

noticed by the researchers in the design and implementation 

of the different schemes for complexes were examined. In 

general, most researchers confirmed that residential 

complexes are better than detached houses. They also 

mentioned the use of solar energy as a good solution to reduce 

the need for fossil fuel consumption. To improve the 

conditions of energy consumption in buildings, there are 

various solutions of passive and active methods that can be 

improved to a great extent by using them. In this article, more 

than the factors involved in architecture, the focus has been 

on examining the effect of different types of arrangements on 

each other. The city of Edmonton, which is located in region 2 

according to the ASHRAE classification, was chosen for 

modeling. This region has a cold and dry climate. Also, the 

wind speed is strong in winter. Therefore, the main priorities 

of the design are to protect the cold air and wind in the cold 

Decision 
cost Matrix 

HL CL 1-CE 1-SF 

SS 3620 1666.93 0.741 0.731 

MI 3460 1693.13 0.857 0.748 

TO 3670 1837.31 0.819 0.752 

LI 3495 1728.2 0.879 0.748 

SU 3495 1824.72 0.879 0.748 

Max 3670 1837.31 0.879 0.752 

Normal 
Cost Matrix 

HL CL 1-CE 1-SF 

SS 0.986 0.907 0.843 0.972 

MI 0.943 0.922 0.975 0.995 

TO 1.000 1.000 0.932 1.000 

LI 0.952 0.941 1.000 0.995 

SU 0.952 0.993 1.000 0.995 

Mean 0.967 0.953 0.950 0.991 

PV 
Matrix 

HL CL 1-CE 1-SF 

SS 0.000 0.002 0.011 0.000 

MI 0.001 0.001 0.001 0.000 

TO 0.001 0.002 0.000 0.000 

LI 0.000 0.000 0.003 0.000 

SU 0.000 0.002 0.003 0.000 

Sum 0.002 0.007 0.017 0.000 Sum 

1-
PV 

0.998 0.993 0.983 1.000 3.973 



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34 

 

seasons and to use natural ventilation in the summer. These 

are considered in the modeling. In addition, to actively use 

solar energy, the usability and improvement rate of solar 

collectors were also analyzed. Therefore, five types of 

arrangement linear, towers, mixed, skyscraper, and 

surrounding were proposed, which did not differ from each 

other in terms of interior design and cooling and heating 

systems, and the only difference was in the number of floors 

and their arrangement together. These options were modeled 

with relevant details in design builder software and the 

results were investigated. Also, modeling of the use of solar 

collectors was done with the help of T*sol software. The 

results showed that, for example, the skyscraper option, 

although it has a favorable situation in terms of the required 

cooling load and also the potential of receiving solar energy, 

due to the lack of roof surface that can be used for installing 

collectors, it cannot use a large part of this energy, Of course, 

it is clear that this is inevitable in engineering matters and it 

is very difficult or even impossible to optimize all the different 

criteria, including economic, environmental, operational 

capability, etc. For this reason, since the problem of 

determining the optimal option is a multi-criteria problem, to 

compare the options, the PSI optimization method with two 

weighting methods was used. The results indicated that the 

first two options are skyscrapers and mixed, and other 

options are in the next categories. Therefore, it can be 

recommended that the builders of the complex choose one of 

the two layout types. 

Ethical issue 
The authors are aware of and comply with best practices in 
publication ethics, specifically with regard to authorship 
(avoidance of guest authorship), dual submission, 
manipulation of figures, competing interests, and compliance 
with policies on research ethics. The authors adhere to 
publication requirements that the submitted work is original 
and has not been published elsewhere. 

Data availability statement 
The manuscript contains all the data. However, more data will 

be available upon request from the authors. 

Conflict of interest 

The authors declare no potential conflict of interest. 

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