Potential Benefits of Thermal Insulation in Public Buildings: Case of a University Building

Abstract

Global energy demand continues to rise due to advances in both developed and developing countries. Energy-efficient technologies and eco-friendly policies have been insufficient to counterbalance the increasing demand and, thus, the national strategies of many countries have been shaped by energy conservation considerations. Buildings are responsible for more than one third of the global final energy consumption and the energy use in buildings is expected to grow more than 40% in the next 20 years. Even though the energy-efficient retrofits and thermal insulation of the building envelope have been widely studied in academia, the case of existing public buildings has been largely neglected. To fill the gap, this study investigates the thermal insulation of existing public buildings and unveils its potential benefits. An administrative building of a public university has been the subject of financial analysis to observe the feasibility of insulation applications and to identify the most feasible insulation application. The results reveal that (i) the most feasible application depends considerably on the financial scenarios and (ii) the feasibility of insulation applications is greatly influenced by the building geometry. This study contributes to the literature by demonstrating the feasibility of energy retrofits in an administrative public building and proposing an alternative way to achieve national energy efficiency objectives.

1. Introduction

Rapid industrialization in recent decades has greatly accelerated the use of fossil fuels. Deriving the majority of energy consumption from nonrenewable energy sources leads to an undesired condition for the environment, emphasizing the need to reduce nonrenewable energy consumption on the global scale [1]. Even though the technological advancements and encouraging policies have gradually enhanced the efficiency of energy end-use services, the increasing demand for energy services has not been counterbalanced [2].

Achieving carbon neutrality by 2050 necessitates efficiency and a reduction in energy demand to ensure flexible selection of the available decarbonization options that avoid social and environmental side-effects [3]. Aside from benefitting the mitigation of climate change and national security of energy supply, energy savings owing to the conservation of energy can provide improvements in local pollution, productivity, competitiveness of companies, household energy expenditure, and health of building occupants [2].

Energy use in buildings and building construction sectors corresponds to more than one third of global final energy consumption and is responsible for nearly 40% of total (both direct and indirect) CO₂ emissions [4]. Furthermore, the energy demand of buildings is expected to grow by more than 40% in the next 20 years [5] due to urbanization and climate change, such as global warming and extreme weather events [6]. Therefore, providing energy-efficient buildings would be critical for the prevention of the increase in the energy demand.

The measures to achieve energy efficiency in buildings can be divided into two categories, namely soft and hard measures. The former implies education and behavior changes, while the latter contains investment in energy efficiency including equipment upgrades [7]. In spite of their high initial costs, the hard measures are especially effective for limiting energy consumption in buildings by means of well-proven solutions such as thermal insulation, the use of efficient glazing, the elimination of thermal bridges, and the installation of efficient heating/cooling generation and distribution systems [8].

The achievement of energy efficiency in new buildings has received a great deal of attention using a multidisciplinary approach throughout the life cycle including the pre-building, building, and post-building phases [9]. Equally important is the case of existing buildings where poor thermal properties lead to high energy demand [10]. In this direction, the trend toward re-engineering or retrofitting existing buildings has accelerated in recent years. Energy-efficient retrofits cover the improvement in the building envelope through building-integrated renewable energy technologies, climate control strategies, and insulation [11].

The renovations in buildings with structural vulnerability need to consider both the seismic and energy retrofitting concurrently. Especially in regions with seismic hazard, the interventions should address seismic and energy performance for buildings not designed to modern standards. The types of integrated retrofitting solutions proposed in the literature include (i) exoskeleton interventions, (ii) enhancements in envelope elements to achieve better energy/seismic performance, and (iii) replacements of envelope elements by higher-performance elements [12].

This study examines the potential benefits of energy-efficient retrofits, more specifically, the thermal insulation of existing public buildings. An administrative building in Sakarya University of Applied Sciences was subjected to investigation. The financial analysis of thermal insulation considered the cost of insulation application and potential savings owing to the reduction in annual energy requirements. Financial parameters were calculated to observe the feasibility of insulation applications on existing public buildings and to identify the optimum insulation application. Scenario analysis was conducted to pay regard to the probable deviations in inflation and interest rates.

This paper is organized as follows: Section 1 presents the motivation of this study and summarizes previously conducted studies on energy efficiency in buildings; Section 2 illustrates the flowchart of methodology and explains the steps in detail; Section 3 introduces and discusses the results; and Section 4 emphasizes main observations, clarifies the contribution to the literature, and proposes future studies.

1.1. Role of Energy Efficiency in the National Strategies

The oil crisis in the early 1970s brought about the emergence of conservation of energy and energy efficiency as the key pillars of national energy policies [13]. Countries from all over the world started to shape their national energy policies in compliance with these energy conservation considerations [14]. These policies have been especially effective in Europe, where the European Union has been the tower of strength. The Member States have been motivated to join the energy efficiency movement.

A critical part of the European Union climate and energy strategies is to decrease the energy requirement of buildings through the implementation of energy efficiency policies. The concept of energy efficiency first appeared in the European Union energy policy agenda in the 1970s and gradually gained importance with the increasing concern for global energy and climate priorities [15]. The Paris Agreement in December 2015 accelerated the attempts to mitigate the effects of global warming and climate change [16].

Energy efficiency has been proposed as a way to promote sustainability and competitiveness of the European economy. It is recognized as a cost-effective solution to concurrently enhance the security of supply and contribute to the energy and climate objectives. The European Union has set the target to achieve an energy efficiency of 32.5% by 2030. The National Energy Efficiency Action Plans of the Member States involve radical energy efficiency measures to accomplish the national energy efficiency objectives [7].

The main piece of European Union legislation that imposes binding measures for the Member States to reach the objectives is the Energy Efficiency Directive (2012/27/EU) [17]. The Directive covers a number of binding measures including energy efficiency policies, the provisions on the setting of energy efficiency targets, and legal obligations to establish energy conservation schemes in Member States. It instructs the Member States to draft national energy efficiency action plans proposing a structural framework and an implementation methodology on energy efficiency [7].

The instructions of the directive have encouraged the Member States to develop energy efficiency policies. To illustrate, Italy promoted financial incentives to renovations and gave tax credits up to 110% of the intervention value [18]. Even though the binding measures are not applicable to the United Kingdom after leaving the European Union on the Brexit deal, it still follows through the international commitments. The United Kingdom aims to cut carbon emissions to combat climate change with the recent strategy “the Clean Growth Strategy: Leading the way to a low carbon future” [7].

To harmonize with the Energy Efficiency Directive, Turkish officials also implemented a policy, namely the National Energy Efficiency Action Plan (NEEAP). Within this context, the goals of the NEEAP were also included in the National Energy and Mining Policy issued by the Ministry of Energy and Natural Resources (MENR). The action plan, which was implemented in the period of 2017–2023, contained 55 actions defined under six categories, namely transport, industry and technology, buildings and services, energy, agriculture, and cross-cutting areas [19].

The primary energy consumption of Türkiye was 147.2 Mtoe in 2020 and is expected to reach up to 205.3 Mtoe by 2035. The shares of fossil resources and renewable energy sources in primary energy consumption in 2020 were 83.3% and 16.7%, respectively. The final energy consumption, which was 105.5 Mtoe in 2020, is expected to move up to 148.5 Mtoe by 2035. As of 2020, residential buildings were responsible for 24.5% of the total final energy consumption [20].

With the help of measures taken in the 2000–2020 period, Türkiye could reduce the energy intensity by 25%, which was still less than the 28%–36% reduction achieved by developed countries, namely France and Germany. The objective was indicated as the reduction in the energy intensity by 35.3% in the 2020–2035 period. It was also stated that meeting the objective would require a major transformation in all sectors and a systematic approach unlike that which had been previously followed [20].

1.2. Previous Studies on Energy Efficiency in Buildings

Energy efficiency has been an attractive topic in academia for decades. Researchers have conducted numerous studies to promote energy efficiency, especially in buildings, where energy use accounts for a considerable part of the global primary energy consumption. The topic has been mainly investigated through the following aspects: evaluation of the accuracy and optimality of national standards, prediction of building energy consumption, review and classification of energy efficiency measures, and analysis of the impact of energy efficiency measures.

A number of studies have questioned the accuracy and optimality of national standards. Caglayan et al. [21] examined the optimality of the limits stated in the Turkish national standard for thermal insulation requirements. Hussein et al. [22] assessed the benefits of an updated building energy code. They focused on the heat transfer coefficient of the building envelope to reduce the future energy demand. He et al. [23] analyzed the impact of upgrading the ASHRAE 90.1–2016 to 2019 in sixteen climate zones in the United States. Wang et al. [24] calculated the difference between the actual energy use and regulated energy consumption by design standards for residential buildings in China.

Multiple studies have attempted to predict the energy consumption of buildings. Runge and Zmeureanu [25] reviewed studies that had utilized artificial neural networks to forecast building energy use and demand. Le et al. [26] forecasted the heating load of buildings’ energy efficiency by developing four artificial intelligence techniques including the combination of the artificial neural network with artificial bee colony optimization, particle swarm optimization, the imperialist competitive algorithm, and the genetic algorithm. Pham et al. [27] utilized machine learning algorithms to predict the short-term energy consumption in an hourly resolution in several buildings.

Certain studies have reviewed and classified the energy efficiency measures utilized in the literature. Belussi et al. [28] summarized the state of the art of zero-energy building performances and related technical solutions. Lidelöw et al. [29] performed a literature review of the energy efficiency measures for heritage buildings. Farzaneh et al. [30] reviewed the application of artificial intelligence technologies in smart buildings to decrease energy consumption through better control, improved reliability, and automation. Nair et al. [31] reviewed the energy efficiency retrofit measures and revealed the technical challenges and possibilities.

Several studies have focused on the impact of energy efficiency measures on building energy efficiency. Serale et al. [32] highlighted the application of model predictive control in improving energy efficiency in buildings. Bughio et al. [33] investigated the influence of passive energy efficiency measures on the cooling energy demand. Chippagiri et al. [34] tested the effects of sustainable prefabricated wall technology on energy consumption. The peak cooling load was reduced by six times. Meena et al. [35] assessed the potential of utilizing solar energy for water heating. Albatayneh et al. [36] investigated the shading effect of solar photovoltaic rooftop panels on the roof surface.

Researchers have paid great attention to the thermal insulation of the building envelope, but relatively few studies have specifically addressed the case of existing public buildings. On the government side, officials have frequently encouraged private home owners to pursue energy efficiency. The issue seems to have been neglected for public buildings that account for a significant portion of the total building stock. Based on the fact that meeting the national energy objectives requires a systematic approach unlike that previously followed, this study considers promoting the energy efficiency of public buildings as an alternative path to decrease the total energy consumption and to realize the national strategy in energy efficiency.

2. Research Methodology

2.1. The Building Profile

The profile of the aforementioned building and its floor plan are shown in Figure 1. It is a four-story university building located next to the Sapanca lake in the city of Sakarya, Türkiye. The building currently belongs to Sakarya University of Applied Sciences and is labeled as the T2 building. The building comprises various units including the office of the rectorate, dean’s office, registrar’s office, directorate of information technologies, department of civil engineering, and conference hall. The building has a total area of 4486 m² and a gross volume of 16,140 m³. The areas of the windows are 167 m², 134 m², 7.2 m², and 10 m² in the south, north, east, and west directions, respectively.

Figure 1. The profile and floor plan of T2 building.

The construction of the building was completed on 1 March 2011. The reinforced concrete building was designed and constructed in accordance with the Turkish Earthquake Code (TEC) 2007 [37]. The history of code revisions shows that the earthquakes in Turkey and the code revisions occur at similar times. The code came into force after the Great Marmara Earthquake on 17 August 1999. The earthquake caused a financial cost of USD 1.1–4.5 billion and a loss of approximately 25,000 lives [38]. Sakarya was categorized in the first seismic zone in TEC 2007. The building was designed according to an effective ground acceleration coefficient of 0.40 and building importance factor of 1.4. The building has had no structural damage. Therefore, this study focuses solely on the energy retrofitting.

2.2. The Flowchart of Research Methodology

The flowchart of the research methodology is illustrated in Figure 2. It is composed of a total of four phases, including the (i) thermal insulation options, (ii) annual energy requirement, (iii) life cycle costing analysis, and (iv) alternative design evaluation. In the first phase, thermal insulation options were determined. Insulation application included insulation of the exterior walls and insulation of the ceiling. It was assumed that the exterior walls would be insulated with expanded polystyrene (EPS). The lack of an inclined roof (a non-heated attic with sloping roof pitches) made extruded polystyrene (XPS) the only applicable insulation material to be applied on the ceiling. The costs of the insulation applications were determined by taking offers from companies for each insulation thickness (from 0 to 20 cm). The annual energy requirement of the building was calculated in the second phase. Space heating was calculated for the uninsulated and insulated cases to observe the potential saving. The calculations were based on the national standard, Turkish Standard (TS) 825 [39], which mainly considered the building geometry and climate.

Figure 2. Flowchart of research methodology.

The third phase involved the life cycle costing analysis and detection of the optimum insulation thickness. A cash flow diagram was generated for each insulation alternative. The cash flow diagram covered the cost of investment and annual savings obtained in the following years. Financial parameters were determined for different scenarios of inflation and interest rates. The insulation alternative resulting in the greatest net saving was regarded as the optimum alternative. In the fourth phase, focus was placed on discovering the changes in results if the building had an inclined roof. The presence of a non-heated attic with sloping roof pitches would enable the application of alternative insulation materials such as stone wool on the ceiling. This could consequently lead to the achievement of greater financial parameters and different optimum thicknesses.

2.3. Determination of Thermal Insulation Options

The most common way of applying thermal insulation on existing buildings is to insulate the exterior walls and ceiling [21]. EPS is the most preferred insulation material for the exterior walls. Nevertheless, the situation is quite different for the ceiling. The preferred insulation material largely depends on the presence of the inclined roof. In case of the inclined roof, it would be possible to apply a variety of materials and the insulation material would be simply spread over the ceiling. The lower cost of stone wool makes it the most appropriate material for inclined roofs. The lack of the inclined roof restricts the types of applicable materials because the insulation material is applied on the interior side of the ceiling. XPS is the most commonly used material in this case. A cross-section of the insulated building envelope is presented in Figure 3. The area of both the ceiling and basement is 1040 m². The areas of the infilled and reinforced concrete walls are 1190 m² and 876 m², respectively.

Figure 3. Cross-section of the building envelope.

2.4. Calculation of Annual Energy Requirement

The annual energy requirement was calculated by using the national standard TS 825 “thermal insulation requirements for buildings” published by the Turkish Standards Institute [39]. The standard mainly considers the building geometry and climate properties. Cities in Türkiye are categorized into four climate regions including region 1, region 2, region 3, and region 4. Sakarya belongs to region 2 in this category, where region 1 represents the warmest and region 4 covers the coldest cities. The yearly heating degree-days of Sakarya was calculated as 2154 for a base temperature of 19.5 °C [40].

The annual heating energy consumption (Q_year) is equal to the sum of monthly heating energy consumptions (Q_m).

$$Q_{year}=\sum Q_m$$

(1)

$$Q_m=\left[H\ast \left({\theta }_{in}-{\theta }_{out}\right)-\eta \ast \left({\phi }_{in}+{\phi }_s\right)\right]\ast t$$

(2)

The specific heat loss (H) of the building equals to the sum of the heat losses caused by conduction and convection (H_tr) and ventilation (H_ven).

$$H=H_{tr}+H_{ven}$$

(3)

H_tr is obtained as follows:

$$H_{tr}=\sum A\ast U=U_{ew}\ast A_{ew}+U_{gl}\ast A_{gl}+U_{ed}\ast A_{ed}+U_{ce}\ast A_{ce}+\left(0.5\right)\ast U_{fl}\ast A_{fl}$$

(4)

A and U represent the area and heat transfer coefficient, respectively. In the case of an inclined roof, U_ce ∗ A_ce is multiplied by 0.8.

According to the national standard, the heat loss due to thermal bridges is calculated separately. In this study, it was assumed that necessary precautions had been taken to prevent the occurrence of thermal bridges.

H_ven is calculated as follows:

$$H_{ven}=\left(0.264\right)\ast n_a\ast V_{gross}$$

(5)

V_gross is the gross building volume and n_a is the air changing volume. n_a was taken as 0.8 for natural ventilation.

The monthly average heat gain (φ_in) is equal to

$${\phi }_{in}\le 5\ast A_n$$

(6)

A_n is the building usage area.

$$A_n=\left(0.32\right)\ast V_{gross}$$

(7)

The monthly average solar energy gain (φ_s) is equal to

$${\phi }_{s,j}={\sum }_k{r}_j\ast G_j\ast I_{j,k}\ast A_{gl,k}$$

(8)

r is the monthly average shading factor of the transparent surfaces, A_gl,k is the total glazing area in direction k, and G is the solar energy permeation factor of the transparent elements. r was considered as 0.8 for detached buildings. The monthly average solar radiation intensities (I_j,k) are given in Table 1 [39].

Table 1. Monthly average solar radiation intensities (W/m²).

Solar Radiation	Months
	January	February	March	April	May	June	July	August	September	October	November	December
Isouth	72	84	87	90	92	95	93	93	89	82	67	64
Inorth	26	37	52	66	79	83	81	73	57	40	27	22
Ieast/west	43	57	77	90	114	122	118	106	81	59	41	37

Solar energy permeation factor (G) is equal to

$$G_j=F_w\ast g_{┴}$$

(9)

F_w is the correction factor for windows and g_┴ is the solar energy permeation factor measured under laboratory conditions for the rays striking the surface vertically. F_w was assumed as 0.8 and g_┴ was considered as 0.75 for colorless glass.

The monthly average usage factor of heat gain (η) is equal to

$$\eta =1-e^{(-1/GLR)}$$

(10)

GLR is the gain/loss ratio and is equal to

$$GLR=\frac{\left({\phi }_{in}+{\phi }_s\right)}{H\ast \left({\theta }_{in}-{\theta }_{out}\right)}$$

(11)

The GLR formula in Equation (11) is inserted in Equation (10) and η becomes

$$\eta =1-e^{\left(\frac{H\ast \left({\theta }_{out}-{\theta }_{in}\right)}{\left({\phi }_{in}+{\phi }_s\right)}\right)}$$

(12)

The monthly average indoor temperature (θ_in) is assumed as 20 °C in the national standard. The monthly average outdoor temperatures (θ_out) are presented in Table 2. Having a GLR value equal to or greater than 2.5 implies that no heat loss occurs in the corresponding month.

Table 2. Monthly average outdoor temperatures (°C).

Month	Region 1	Region 2	Region 3	Region 4
January	8.4	2.9	−0.3	−5.4
February	9.0	4.4	0.1	−4.7
March	11.6	7.3	4.1	0.3
April	15.8	12.8	10.1	7.9
May	21.2	18.0	14.4	12.8
June	26.3	22.5	18.5	17.3
July	28.7	24.9	21.7	21.4
August	27.6	24.3	21.2	21.1
September	23.5	19.9	17.2	16.5
October	18.5	14.1	11.6	10.3
November	13.0	8.5	5.6	3.1
December	9.3	3.8	1.3	−2.8

2.5. Limitations of the National Standard

The national standard requires that when the whole or independent parts of existing buildings are subjected to substantial repair or amendment, the resulting heat transfer coefficients of the exterior wall (U_ew), ceiling (U_ce), basement (U_bs), and glazing (U_gl) should be equal to or smaller than the limiting values indicated in the standard (Table 3). As the insulation is implemented to the exterior wall and ceiling, the resulting heat transfer coefficients (U_ew and U_ce) need to be less than 0.60 and 0.40 W/m²K, respectively.

Table 3. Limiting heat transfer coefficients for existing buildings (W/m²K) [39].

Region	Uew	Uce	Ubs	Ugl
Region 1	0.70	0.45	0.70	2.40
Region 2	0.60	0.40	0.60	2.40
Region 3	0.50	0.30	0.45	2.40
Region 4	0.40	0.25	0.40	2.40

The heat transfer coefficients of the insulated building are summarized in Table 4. The coefficients that satisfy the standard limits are colored in gray. The EPS insulation applied to the exterior walls needs to satisfy the requirements of the standard for both the infilled and reinforced concrete (RC) walls. Thus, the minimum applicable insulation thickness of EPS on exterior walls is 5 cm. A minimum XPS thickness of 8 cm can satisfy the requirements for the ceiling. This results in 17 insulation alternatives for the exterior walls (none or 5–15 cm) and 14 insulation alternatives for the ceiling (none or 8–20 cm), the combination of which leads to a total of 238 different insulation applications.

Table 4. Heat transfer coefficients of insulation applications.

Uew Coefficient (W/m2K)				Uce Coefficient (W/m2K)
Thickness		Infilled Wall	RC Wall	Thickness		Ceiling
Thickness of EPS insulation on the exterior wall (cm)	0	1.670	3.239	Thickness of XPS insulation on the ceiling (cm)	0	2.479
	1	1.102	1.620		1	1.451
	2	0.838	1.107		2	1.026
	3	0.676	0.841		3	0.793
	4	0.576	0.678		4	0.647
	5	0.488	0.568		5	0.546
	6	0.428	0.489		6	0.472
	7	0.381	0.429		7	0.416
	8	0.344	0.382		8	0.372
	9	0.313	0.344		9	0.336
	10	0.287	0.314		10	0.307
	11	0.266	0.288		11	0.282
	12	0.247	0.266		12	0.261
	13	0.231	0.247		13	0.243
	14	0.216	0.231		14	0.227
	15	0.204	0.217		15	0.213
	16	0.193	0.204		16	0.201
	17	0.183	0.193		17	0.190
	18	0.173	0.183		18	0.180
	19	0.165	0.174		19	0.171
	20	0.158	0.165		20	0.163

2.6. Life Cycle Costing Analysis

The financial benefits of 238 different insulation applications were determined based on the life cycle costing analysis. From the financial perspective, insulation application implies an initial cost and annual savings in the following years. The initial cost is the cost of implementing insulation, which can be subdivided into the material cost, auxiliary item cost, and application cost. The initial cost was determined by taking offers from construction companies. Annual savings occur due to the decrease in the annual energy requirement. The annual saving is equal to the difference between the annual energy requirement of the uninsulated and insulated building.

A cash flow diagram was created for each insulation application. The diagram considered a period of 20 years in line with the assumptions made in the literature [21]. Financial parameters such as the net savings (NS), internal rate of return (IRR), savings-to-investment ratio (SIR), and payback period (PBP) were calculated for each insulation application to discover the potential benefits of insulation applications and determine the optimum alternative. Scenario analysis was conducted to observe the effect of changes in inflation and interest rates on the financial parameters and optimum insulation alternative.

NS measures the cost effectiveness of the benefits to be achieved from the investments. It is obtained by subtracting the present value of investment costs from the present value of the savings.

$$NS={\sum }_{t=0}^N\frac{S_t}{{\left(1+i\right)}^t}-\frac{{Inv}_t}{{\left(1+i\right)}^t}$$

(13)

where S is the saving, Inv is the investment, i is the interest rate, t is the time, and N is the period of the study, which was assumed as 20 years.

IRR represents the annual rate of return to be earned on a project. It is equal to the discount rate that makes the net present value of a project zero.

$$0={\sum }_{t=0}^N\frac{S_t}{{\left(1+IRR\right)}^t}-\frac{{Inv}_t}{{\left(1+IRR\right)}^t}$$

(14)

SIR is the ratio of the net present value of the savings to the net present value of the investment. It should be greater than 1.0 to be considered as an alternative and regarded as cost-effective.

$$SIR=\frac{\sum _{t=0}^N\frac{S_t}{{\left(1+i\right)}^t}}{\sum _{t=0}^N\frac{{Inv}_t}{{\left(1+i\right)}^t}}$$

(15)

PBP shows the minimum time satisfying the condition that cash inflows offset the investment costs.

2.7. Evaluation of Alternative Design

The university building under investigation had no inclined roof and, thus, the insulation implementation on the ceiling was restricted to XPS insulation on the interior side. In an attempt to observe the effect of the building geometry (presence of the inclined roof) on the results, the process was repeated with the assumption that the building had an inclined roof. The presence of the non-heated attic with sloping roof pitches could enable the application of alternative insulation materials such as stone wool on the exterior side, which would lead to a significant decrease in the initial cost. The probable changes in the financial parameters and optimum insulation alternative were noted.

3. Research Results and Discussion

3.1. Annual Energy Requirement and Saving

The annual energy requirement and saving are summarized in Table 5 and the annual energy requirement is graphically presented in Figure 4. Each cell in the table is composed of the values where the upper represents the annual energy requirement and the lower stands for the annual energy saving. The annual energy requirement of the uninsulated building (the current form) is 615,056 kWh/year. Insulating the building according to the minimum thicknesses that satisfy the standard limitations decreases the annual energy requirement to 259,360 kWh/year, providing a saving of 57.8%. Increasing the insulation thicknesses can increase the saving amount up to 66.4%. Nevertheless, it should be noted that the increasing insulation thickness also results in a greater initial cost and, thus, does not guarantee better financial results.

Table 5. Annual energy requirement/saving (kWh/year).

		Exterior Wall Insulation Thickness (cm)
		0	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
Ceiling Insulation Thickness (cm)	0	615,056 0	387,987 227,069	379,657 235,399	373,268 241,788	368,210 246,846	364,107 250,950	360,710 254,346	357,852 257,205	355,413 259,643	353,308 261,748	351,473 263,583	349,858 265,198	348,427 266,630	347,149 267,907	346,001 269,055	344,965 270,092	344,024 271,032
	8	481,319 133,737	259,360 355,696	251,509 363,547	245,501 369,555	240,754 374,303	236,908 378,149	233,728 381,328	231,056 384,000	228,778 386,278	226,814 388,243	225,102 389,954	223,597 391,459	222,264 392,793	221,074 393,982	220,006 395,050	219,042 396,014	218,168 398,909
	9	479,072 135,984	257,282 357,775	249,441 365,615	243,440 371,616	238,700 376,357	234,859 380,197	231,684 383,372	229,016 386,041	226,742 388,315	224,780 390,276	223,071 391,985	221,568 393,488	220,237 394,819	219,049 396,007	217,983 397,073	217,021 398,036	216,148 400,572
	10	477,220 137,836	255,569 359,487	247,737 367,319	241,743 373,313	237,008 378,049	233,172 381,885	230,001 385,056	227,335 387,721	225,064 389,992	223,105 391,951	221,398 393,658	219,898 395,159	218,568 396,488	217,382 397,674	216,317 398,739	215,356 399,700	214,484 401,966
	11	475,667 139,389	254,135 360,922	246,309 368,747	240,321 374,736	235,590 379,466	231,758 383,299	228,590 386,466	225,928 389,129	223,659 391,398	221,702 393,355	219,997 395,060	218,498 396,559	217,170 397,887	215,985 399,071	214,921 400,135	213,961 401,095	213,090 403,151
	12	474,346 140,710	252,915 362,142	245,095 369,961	239,112 375,945	234,385 380,672	230,556 384,501	227,391 387,666	224,731 390,326	222,464 392,593	220,509 394,548	218,805 396,251	217,308 397,749	215,981 399,075	214,797 400,259	213,735 401,321	212,776 402,281	211,906 404,170
	13	473,208 141,848	251,865 363,192	244,050 371,006	238,071 376,985	233,347 381,709	229,521 385,535	226,359 388,698	223,701 391,355	221,436 393,621	219,482 395,574	217,780 397,276	216,284 398,772	214,958 400,098	213,776 401,281	212,714 402,342	211,756 403,301	210,886 405,056
	14	472,218 142,838	250,952 364,105	243,142 371,915	237,166 377,890	232,445 382,611	228,622 386,435	225,461 389,595	222,805 392,251	220,542 394,515	218,590 396,467	216,889 398,167	215,394 399,663	214,069 400,987	212,887 402,169	211,826 403,230	210,869 404,187	210,000 405,834
	15	471,349 143,707	250,150 364,906	242,344 372,712	236,372 378,684	231,654 383,402	227,832 387,224	224,674 390,382	222,019 393,037	219,757 395,299	217,806 397,250	216,107 398,950	214,612 400,444	213,289 401,768	212,108 402,949	211,048 404,009	210,091 404,966	209,223 406,522
	16	470,580 144,476	249,441 365,615	241,639 373,417	235,669 379,387	230,954 384,103	227,134 387,922	223,977 391,079	221,324 393,732	219,063 395,993	217,114 397,943	215,415 399,642	213,921 401,135	212,598 402,458	211,418 403,638	210,358 404,698	209,402 405,654	208,535 407,135
	17	469,895 145,162	248,809 366,247	241,010 374,046	235,043 380,013	230,330 384,727	226,512 388,544	223,357 391,700	220,705 394,351	218,445 396,611	216,496 398,560	214,798 400,258	213,306 401,751	211,983 403,073	210,804 404,253	209,745 405,312	208,789 406,268	207,922 407,684
	18	469,280 145,777	248,243 366,813	240,447 374,610	234,482 380,574	229,770 385,286	225,954 389,102	222,800 392,256	220,150 394,907	217,891 397,166	215,943 399,114	214,246 400,811	212,754 402,303	211,432 403,624	210,253 404,804	209,194 405,862	208,239 406,817	207,372 408,179
	19	468,725 146,331	247,732 367,324	239,939 375,118	233,976 381,080	229,266 385,790	225,451 389,605	222,298 392,758	219,649 395,407	217,391 397,665	215,444 399,613	213,747 401,309	212,256 402,800	210,935 404,122	209,756 405,300	208,698 406,358	207,743 407,313	206,877 408,179
	20	468,222 146,834	247,269 367,787	239,478 375,578	233,517 381,539	228,809 386,247	224,995 390,061	221,844 393,213	219,195 395,861	216,938 398,118	214,992 400,065	213,296 401,761	211,805 403,251	210,484 404,572	209,306 405,750	208,249 406,808	207,294 407,762	206,428 408,628

Figure 4. Graphical presentation of annual energy requirement.

3.2. Cost of Insulation

The insulation cost was determined by receiving offers from construction firms (Table 6). The cost of an insulation application includes the cost of material, auxiliary items, and application. It was initially assumed that EPS insulation would be applied on the exterior walls and XPS insulation would be applied on the interior side of the ceiling. In order to evaluate the changes in case of the inclined roof, the cost of stone wool application on the exterior side of the ceiling was also obtained. As the stone wool is simply spread over the ceiling, the cost only includes the cost of the material. It does not necessarily require auxiliary items and the application cost becomes negligible. It was observed that the presence or lack of the inclined roof caused a considerable difference in the cost of insulation application on the ceiling and consequently in the initial cost.

Table 6. Cost of insulation applications (USD/m²).

Thickness (cm)	Expanded Polystyrene (EPS)				Extruded Polystyrene (XPS)				Stone Wool
	Mat.	Aux.	App.	Total	Mat.	Aux.	App.	Total
1	0.68	2.57	3.90	7.15	1.17	2.57	3.90	7.64	0.43
2	1.35	2.57	3.90	7.82	2.34	2.57	3.90	8.81	0.86
3	2.02	2.57	3.90	8.49	3.51	2.57	3.90	9.98	1.29
4	2.70	2.57	3.90	9.17	4.69	2.57	3.90	11.16	1.72
5	3.38	2.63	3.90	9.91	5.85	2.63	3.90	12.38	2.15
6	4.05	2.63	3.90	10.58	7.02	2.63	3.90	13.55	2.58
7	4.72	2.67	3.95	11.34	8.20	2.67	3.95	14.82	3.01
8	5.40	2.67	4.00	12.07	9.36	2.67	4.00	16.03	3.44
9	6.07	2.72	4.00	12.79	10.54	2.72	4.00	17.26	3.87
10	6.74	2.72	4.00	13.46	11.70	2.72	4.00	18.42	4.30
11	7.43	2.92	4.05	14.40	12.87	2.92	4.05	19.84	4.73
12	8.10	2.92	4.05	15.07	14.05	2.92	4.05	21.02	5.16
13	8.77	2.95	4.05	15.77	15.21	2.95	4.05	22.21	5.59
14	9.44	2.95	4.15	16.54	16.39	2.95	4.15	23.49	6.02
15	10.12	3.03	4.15	17.30	17.56	3.03	4.15	24.74	6.45
16	10.79	3.03	4.15	17.97	18.73	3.03	4.15	25.91	6.88
17	11.46	3.06	4.25	18.77	19.90	3.06	4.25	27.21	7.31
18	12.13	3.12	4.25	19.50	21.07	3.12	4.25	28.44	7.74
19	12.82	3.15	4.35	20.32	22.24	3.15	4.35	29.74	8.17
20	13.49	3.15	4.35	20.99	23.41	3.15	4.35	30.91	8.60

3.3. Cash Flow Diagrams

A cash flow diagram was generated for each insulation application and Table 7 illustrates the diagrams of certain applications for an inflation and interest rate of 15% and 17%, respectively. The annual savings were calculated based on the assumption that the cost of natural gas was 0.026 USD/kWh in the base year and would increase in harmony with the inflation rate. Financial parameters indicated the financial feasibility of insulation applications in existing public buildings. The cases showed that NS values were clearly positive, IRR values were mostly greater than 30%, SIR values were greater than 2, and PBP values were less than 7 years.

Table 7. Cash flow diagram of certain insulation applications (USD).

Insulation	Year							NS (USD)	IRR (%)	SIR (-)	PBP (Years)
	0	1	2	5	13	17	20
Wall: none Ceiling: 8 cm	−16,672	3867	4447	6763	20,688	36,184	55,031	39,718	37.55	3.38	5–6
Wall: 5 cm Ceiling: 8 cm	−37,140	10,284	11,827	17,987	55,024	96,237	146,364	112,838	42.30	4.04	4–5
Wall: 5 cm Ceiling: 20 cm	−52,612	10,634	12,229	18,599	56,894	99,508	151,339	102,464	34.30	2.95	6–7
Wall: 6 cm Ceiling: none	−21,854	6806	7827	11,904	36,414	63,689	96,863	77,401	45.88	4.54	3–4
Wall: 8 cm Ceiling: 15 cm	−50,664	11,085	12,748	19,388	59,310	103,733	157,764	110,996	36.13	3.19	5–6
Wall: 9 cm Ceiling: 8 cm	−43,101	10,933	12,573	19,123	58,497	102,311	155,603	116,344	39.86	3.70	4–5
Wall: 9 cm Ceiling: 20 cm	−58,573	11,278	12,970	19,725	60,340	105,534	160,504	105,895	33.24	2.81	6–7
Wall: 12 cm Ceiling: 15 cm	−56,852	11,429	13,144	19,990	61,150	106,951	162,660	109,824	34.19	2.93	6–7
Wall: 18 cm Ceiling: 20 cm	−72,438	11,762	13,526	20,572	62,930	110,065	167,395	99,091	29.79	2.37	7–8
Wall: 19 cm Ceiling: 14 cm	−66,400	11,686	13,439	20,439	62,525	109,356	166,317	104,023	31.37	2.57	6–7

NS values of all insulation applications are summarized in Table 8 and Figure 5 for an inflation and interest rate of 15% and 17%, respectively. The insulation alternative with the greatest NS value is regarded as the optimum alternative. It is observed that insulating the building with minimum insulation thicknesses satisfying the standard limits could provide a saving of USD 112,838. However, greater savings could be attained by increasing the thicknesses of insulation materials. The optimum insulation application is identified as the application of 9 cm EPS on the exterior walls and 8 cm XPS on the ceiling, which results in a saving of USD 116,344.

Table 8. Net saving of insulation alternatives (USD).

		Exterior Wall Insulation Thickness (cm)
		0	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
Ceiling Insulation Thickness (cm)	0		75,275	77,401	78,523	79,143	79,384	79,429	78,709	78,351	77,790	76,971	76,078	75,295	74,179	73,153	71,912	70,922
	8	39,718	112,838	114,762	115,723	116,212	116,344	116,299	115,500	115,074	114,454	113,583	112,643	111,819	110,666	109,606	108,335	108,169
	9	39,389	112,438	114,358	115,316	115,802	115,932	115,884	115,084	114,657	114,035	113,163	112,222	111,397	110,243	109,183	107,911	107,594
	10	38,957	111,947	113,863	114,819	115,303	115,431	115,382	114,580	114,151	113,529	112,656	111,714	110,889	109,734	108,672	107,400	106,969
	11	38,139	111,080	112,993	113,946	114,428	114,554	114,504	113,701	113,271	112,648	111,774	110,832	110,005	108,850	107,788	106,516	105,996
	12	37,472	110,370	112,281	113,231	113,712	113,837	113,785	112,981	112,551	111,927	111,052	110,109	109,283	108,127	107,065	105,791	105,202
	13	36,708	109,569	111,477	112,426	112,906	113,029	112,977	112,172	111,741	111,116	110,241	109,297	108,470	107,314	106,251	104,978	104,332
	14	35,797	108,626	110,532	111,480	111,958	112,081	112,027	111,221	110,789	110,164	109,288	108,345	107,517	106,360	105,297	104,023	103,331
	15	34,868	107,668	109,573	110,519	110,996	111,118	111,063	110,257	109,824	109,199	108,322	107,378	106,550	105,393	104,330	103,056	102,326
	16	33,968	106,743	108,646	109,591	110,067	110,188	110,133	109,326	108,893	108,267	107,390	106,445	105,617	104,460	103,396	102,122	101,360
	17	32,909	105,661	107,563	108,507	108,982	109,102	109,047	108,239	107,806	107,179	106,302	105,357	104,529	103,371	102,307	101,033	100,244
	18	31,894	104,625	106,526	107,469	107,943	108,063	108,006	107,198	106,764	106,137	105,260	104,315	103,486	102,328	101,264	99,990	99,178
	19	30,768	103,481	105,381	106,323	106,796	106,915	106,858	106,050	105,616	104,989	104,111	103,166	102,336	101,178	100,114	98,839	97,818
	20	29,768	102,464	104,362	105,304	105,777	105,895	105,838	105,029	104,594	103,967	103,089	102,143	101,314	100,156	99,091	97,816	96,795

Figure 5. Graphical presentation of net saving.

3.4. Scenario Analysis and Optimum Insulation Thickness

Generation of the cash flow diagrams for each insulation application was repeated for varying interest and inflation rates. The analysis included a total of nine different scenarios, where the interest and inflation rates varied between 15–19% and 13–17%, respectively. The optimum insulation application was noted for each scenario and the financial results of these optimum thicknesses are presented in Table 9. The optimum EPS thickness on the exterior walls changed between 7 and 10 cm, while the optimum XPS thickness on the ceiling in all scenarios was 8 cm, which corresponded to the minimum insulation thickness satisfying the standard limits. Financial parameters of optimum insulation applications demonstrated the profitability of these public investments. The NS values ranged between USD 74,707 and 182,503, IRR values were more than two times the interest rates, SIR values were mostly greater than 3 and went up to 5, and the PBP values were only 4–5 years.

Table 9. Scenario analysis of financial parameters.

No	Interest Rate	Inflation Rate	Optimum Thickness		Financial Parameters
			Wall	Ceiling	NS (USD)	IRR	SIR	PBP
1	%15	%13	9 cm	8 cm	118,680	37.89%	3.75	4–5 years
2	%15	%15	10 cm	8 cm	147,259	39.24%	4.31	4–5 years
3	%15	%17	10 cm	8 cm	182,503	41.21%	5.10	4–5 years
4	%17	%13	8 cm	8 cm	94,015	38.57%	3.26	4–5 years
5	%17	%15	9 cm	8 cm	116,344	39.86%	3.70	4–5 years
6	%17	%17	10 cm	8 cm	143,982	41.21%	4.24	4–5 years
7	%19	%13	7 cm	8 cm	74,707	39.24%	2.86	4–5 years
8	%19	%15	8 cm	8 cm	92,401	40.54%	3.22	4–5 years
9	%19	%17	9 cm	8 cm	114,074	41.83%	3.65	4–5 years

3.5. Case of the Inclined Roof

Investigation of the financial feasibility and the optimization process were repeated for the case of the inclined roof, and changes in the financial parameters and optimum insulation thicknesses were observed (Table 10). The optimum thickness of EPS insulation remained the same as expected. However, the notably lower cost of stone wool application increased the optimum insulation thickness applied on the ceiling to 10–14 cm. Financial parameters were also influenced by the reflections of this situation on the cash flow diagram. NS values had an increase of approximately 20%, IRR values became greater than 50%, SIR values had an increase of more than 50%, and PBP became less than 4 years.

Table 10. Optimum insulation thickness in case of the inclined roof.

No	Interest Rate	Inflation Rate	Optimum Thickness		Financial Parameters
			Wall	Ceiling	NS (USD)	IRR	SIR	PBP
1	%15	%13	9 cm	11 cm	142,007	50.25%	5.53	3–4 years
2	%15	%15	10 cm	12 cm	172,673	50.51%	6.20	3–4 years
3	%15	%17	10 cm	14 cm	210,586	51.68%	7.18	3–4 years
4	%17	%13	8 cm	10 cm	115,587	52.24%	4.93	3–4 years
5	%17	%15	9 cm	11 cm	139,504	52.24%	5.45	3–4 years
6	%17	%17	10 cm	12 cm	169,154	52.49%	6.10	3–4 years
7	%19	%13	7 cm	10 cm	94,948	53.90%	4.40	3–4 years
8	%19	%15	8 cm	10 cm	113,861	54.23%	4.87	3–4 years
9	%19	%17	9 cm	11 cm	137,072	54.22%	5.37	3–4 years

4. Conclusions

This study discovered the potential benefits of insulation application in existing public buildings. Insulation applications satisfying the standard limits were considered as the alternatives and the optimum alternative was determined through the life cycle costing analysis with different scenarios of inflation and interest rates. Changes in the optimization process were observed for the case of an alternative building geometry. The findings show that

• The optimum insulation application depends considerably on the scenario of the inflation and interest rates;
• Benefits of the insulation application are greatly influenced by the building geometry, more specifically, the presence of the inclined roof.

Cash flow diagrams generated under different economic scenarios demonstrated the profitability of thermal insulation in public buildings. The diagrams of optimum applications produced NS values greater than zero, IRR values greater than the interest rates, SIR values greater than one, and payback period less than five years. The financial results (and thus the optimum insulation alternatives) varied with the scenario of the inflation and interest rates. It was observed that the presence of the inclined roof could provide even better financial results as it enabled the use of alternative cost-effective insulation materials on the ceiling.

Governments encourage their citizens to invest in energy conservation instruments in an attempt to actualize the national energy strategies focusing on decreasing the energy requirement and greenhouse gas emissions. These attempts are not perfectly effective, as convincing home owners for such investments requires raising awareness of the life cycle costing concept where the benefits are obtained in the course of time. This study demonstrates the profitability of thermal insulation in existing public buildings, which can be achieved with the governments’ own initiatives. Investing in the thermal insulation of public buildings should be considered as an alternative path for governments to achieve the objectives of their national energy strategies.

This study examined the financial feasibility of thermal insulation for an administrative university building. The results cannot be generalized for residential buildings or other types of public buildings such as hospitals. This is mainly because the calculation of the annual energy requirement changes according to the building functionality. To illustrate, the monthly average indoor temperature (θ_in) is taken as 19 °C, 20 °C, and 22 °C for residential buildings, education buildings, and hospitals, respectively. The changing energy calculation method in the national standard necessitates repetition of the analysis for the other building types. Yet, the analysis provided with this demonstrates the potential benefits of energy efficiency measures in public buildings.

The illustrated optimization process can be repeated for existing public buildings in other cities or countries to observe the changes in potential benefits. The results may change with respect to the building geometry, building functionality, standard limitations in the corresponding country, availability and cost of insulation materials, and climate properties. The identified optimum insulation alternative and financial benefits can be compared to investigate potential differences across cities/countries and the reasons behind these differences can be discussed. Country-specific suggestions can be provided to promote energy efficiency and enhance the return on investment in corresponding countries.