Maintenance as an Opportunity to Improve Residential Buildings’ Energy Efficiency: Evaluation of Life-Cycle Costs

Abstract

Maintenance is crucial for the durability of the existing building stock and should be perceived as an opportunity to improve the built environment. The implementation of thermal retrofitting measures to the building’s envelope enhances global energy performance, which is economically and environmentally beneficial. Building-related energy consumption during the operation phase is key to tackling carbon neutrality and climate change. Introducing thermal retrofitting within the context of maintenance planning can be cost-optimizing, as it reveals the technical–economic synergy between building pathology and energy efficiency. Maintenance activities and energy demand throughout the building’s service life influence life-cycle costs (LCCs). Decision-making based on LCC awareness is an advantage for owners. This study discusses the impact of implementing an optimal retrofitting solution (ORS), according to different maintenance strategies, on the LCC of an existing single-family home. The ORS comprises the following measures: adding an external thermal insulation composite system (ETICS) to external walls, extruded polystyrene (XPS) panels to the roof, and replacing the existing windows with others with improved thermal performance. The three maintenance strategies involve different complexity levels, concerning the type, number and timing of activities. Moving beyond isolated assessments, this study develops an integrated framework that bridges based on two existing background methodologies, involving optimal thermal retrofitting and condition-based maintenance planning, which, combined with new research, enable the assessment of maintenance, energy and global LCC for a time horizon of 100 years. The evaluation of energy-related LCC is based on simulations. The results indicate that these costs represent the majority of the global LCC. The ORS has a considerable positive impact on energy and global LCC. Adopting a maintenance strategy characterized by fewer planned activities and an earlier schedule of replacement interventions, which determines the implementation of the retrofitting measures, is better in terms of LCC savings.

1. Introduction

Maintenance and rehabilitation actions are of great importance for the future of the existing building stock. Existing buildings will probably continue in use for the next 25 years [1] and, in Europe, around 40% of residential buildings are already older than 50 years. Further maintenance will be required and should be perceived as an opportunity to improve the building stock and meet environmental goals [2]. Buildings are a cornerstone to reach carbon neutrality by 2050, in Europe [1], and tackle climate change [3]; climate policies thus stress the need for a significant decrease in energy consumption [4]. In fact, more than 36% of energy consumption and 40% of greenhouse gas emissions are related to buildings in Europe and North America [5,6,7,8]. Around 70% of building-related energy use is attributed to residential buildings alone [3], especially for domestic heating and cooling purposes [9].

The building’s envelope is critical in the prevention of indoor energy loss, and its appropriate design can lead to energy savings of 20–50% [10]. Its thermal retrofitting is beneficial for the decrease in energy use and CO₂ emissions [11]. Thermal retrofitting generally consists of improving the building’s envelope performance through the replacement of windows and energy systems, and application of insulation in external walls and roof [12]. Whenever these envelope elements require intervention beyond current maintenance, the opportunity presents itself for enhancing the building’s thermal performance (e.g., with insulation panels and double glazing), optimizing costs and rationalizing the retrofit process [13]. Growing concerns about environmental impact consolidated the importance of accounting for overall costs during service life through life-cycle methodologies implemented to buildings’ design, construction and maintenance [14]. A decision-making process based on life-cycle cost (LCC) awareness is an advantage for stakeholders [15].

The objective of the present study is to support the decision-making process regarding the thermal retrofitting of an existing single residential building through the analysis of global LCC. The costs considered include maintenance and energy consumption-related expenses, throughout an extended period of analysis. The methodology is developed in two main stages. The first stage encompasses two existing background methodologies: one involves optimal thermal retrofitting [16] and the other condition-based maintenance planning [17]. This previous research enables the second stage of the methodology, which focuses on the assessment of LCC concerning the energy necessary to fulfil thermal comfort needs of the building, including heating and cooling demands.

The evaluation of energy-related LCC begins with energy simulations, according to a baseline scenario and an optimal retrofitting solution [16]. This solution covers the thermal improvement of the building’s envelope elements—external walls, windows and roof. The energy consumption outcomes given by the simulations, for a 100-year time horizon, are necessary to assess the respective LCC. The global LCCs are then calculated by summing the energy and maintenance expenses, resulting from the application of the existing condition-based maintenance planning methodology [17] to the same scenarios and time horizon.

The current study allows to quantify the impact of optimal thermal retrofitting on global LCC, considering maintenance and energy. The output of results for three different maintenance strategies, for both baseline and improved scenarios, also enables conclusions about the best timing to retrofit the envelope’s elements. The replacement of existing solutions with better ones, in the context of maintenance planning, is considered an opportunity to enhance the building’s thermal performance and energy efficiency.

This paper is organized according to the following structure: framework of the research based on literature review, in Section 2; research methodology, including characterization of the case study, materials, scenarios, background and current methods, in Section 3; results and discussion of (i) the favourable moment to implement thermal retrofitting measures and (ii) LCC related to maintenance, energy and global, in Section 4; and main conclusions in Section 5.

2. Maintenance, Energy and Life-Cycle Costs: Framework Based on Literature Review

Maintenance actions are vital to the sustainability of the existing building stock and can effectively contribute to reducing energy consumption and CO₂ emissions during the operation phase, which is the most impactful regarding the sector’s carbon footprint [18]. The trend of energy use in residential buildings is positive and expected to continually increase [19], in the absence of effective measures to curb consumption. Maintenance activities implemented throughout the service life of buildings are opportune circumstances to also enhance energy efficiency [20]. Research about the relationship between sustainable maintenance and environmental challenges is still necessary [18].

The LCC associated with the operation phase can represent around 80% of the total costs and tends to rise significantly without strategic maintenance [18]. Life-cycle assessment is particularly relevant for the sustainability of constructions and respective environmental, economic and social optimization. Buildings’ life-cycles have become more interesting to researchers and stakeholders in the context of decision-making processes based on long-term performance evaluation [21]. Despite its increasing integration in building certification [15] and highly recognized relevance, LCC analysis has not often been applied [22] and still faces practical limitations and implementation challenges [23,24].

Building maintenance, energy efficiency and LCC are linked subjects. Maintenance and energy costs are considered in LCC analysis, which covers the expenses associated with the building’s design, construction, operation, and end of service life [24]. Maintenance planning and energy efficiency affect the LCC directly. This is one of the reasons why LCC analysis is used to justify the economic feasibility of environmentally friendly buildings, whose cost–benefit of energy-efficient solutions is best evaluated based on a long-term perspective [24]. Thermal retrofitting for energy efficiency can be part of maintenance activities, and the latter can be optimized to promote the longevity of the energy efficiency implemented measures, on which some authors recommend further research [25]. Notwithstanding all the identified scientific gaps, research has been developed over time concerning each of the subjects addressed in the current paper and their relationships.

Several thermal retrofitting measures applied to the building’s envelope to reduce energy consumption in existing constructions are explored in the literature. Literature review papers cover many envelope elements (e.g., walls, roof and windows) and equipment [26], or focus on façades [27,28]. Adding insulation to the building’s envelope and replacing windows are commonly pointed out as successful thermal retrofitting strategies. A review study about thermal retrofitting of the existing building stock [1] reveals the prevalence of research centred on the retrofit of the building’s envelope with cost-viable measures. It also states the predominance of studies originating from Europe and about the residential typology. A literature review paper focusing on the residential building stock in Poland [29] is an example of research intended to raise the awareness of stakeholders about the importance of energy efficiency, by identifying critical opportunities and challenges. It stresses that economic tools to analyze the cost impact of improving energy performance should be made available for stakeholders.

Costs, along with environmental and social factors, affect the decision-making on thermal improvement strategies regarding depth and scope. The relevance of cost–benefit and multi-criteria analysis as decision-making supporting tools, for owners looking forward to retrofitting their residential buildings, is highlighted in the literature [2]. The need for instruments to help define intervention priorities based on a comprehensive approach is stressed as well. Concerning the evaluation of buildings’ thermal performance, a comprehensive review paper addresses methods based on energy simulations [30], where EnergyPlus is identified as the most chosen software. LCC analysis is used to evaluate the long-term economic results of adopting energy efficiency measures, from the owner’s point of view [31]. Combined with building’s energy simulation, which enables testing the effect of several energy-related parameters, LCC analysis can lead to optimized solutions [32]. These LCC-focused research uses real residential buildings as case studies. LCC analysis is also taken into consideration and integrated in methodologies applied to other building typologies [33,34,35,36] and to macro-scale interventions [37], with the objective of assessing the economic outcomes of energy improvement measures and finding optimal solutions.

A literature review paper about the use of LCC analysis in the construction sector covers multiple studies concerning the implementation of this technique specifically to assess the building’s envelope performance and energy efficiency [17,38,39]. It highlights the (i) importance of supporting decision-makers in making a balanced choice between energy efficiency and life-cycle benefits, (ii) effective reduction in energy consumption costs over the operation phase as a consequence of an improved building’s envelope, (iii) positive impact of thermal insulation on energy use, LCC and global warming, (iv) significant weight of operation costs on the LCC, and (v) necessary joint contribution of different expertise areas, from physics to economy of constructions, and techniques to achieve optimized solutions.

The resilience and sustainability of constructions are influenced by maintenance actions [39]. Maintenance is crucial to meet environment-related policies, like the Sustainable Development Goals, and to adapt to climate change [40]. It contributes to extending buildings’ service life by enhancing the durability of elements [41]. Nevertheless, maintenance continues to demand proper attention, since its practical implementation has long suffered from the absence of robust guidelines and regulations [42]. Maintenance can be unplanned or planned, and within the latter, fit the following types: preventive, corrective and improvement. Preventive maintenance can be condition-based, among other possibilities, which means that its planning depends on condition criteria, such as the degradation level of the building’s element. Condition-based maintenance relies on inspections, carried out regularly onsite to evaluate the condition level and provide evidence to support the planning of subsequent maintenance activities [39].

Research efforts have been put into (i) optimizing the processes of inspection, diagnosis and repair [43], (ii) modelling and evaluating the physical degradation of different buildings’ elements in real service conditions [44], and (iii) exploring their condition-based maintenance in terms of planning and operation costs optimization [45,46]. The use of maintenance planning as a strategy to achieve an expected building’s environmental performance with optimized LCC, considering climate goals, is also explored in the literature [47]. The objective is to support the building managers’ decision-making process on maintenance action priorities, involving performance, risk, and schedule, thus bridging the scientific gap concerning the joint assessment of these aspects. Another study recalls the advantages of combining energy efficiency measures with necessary maintenance actions, based on planning and the assessment of alternatives that can simultaneously fulfil energy performance and economic expectations [48]. Again, the aim is to assist the owners of residential buildings in the management of their assets, under time and cost constraints. A short-sighted vision of maintenance planning, where necessary actions are often not seen as cost–benefit opportunities, is identified as the root of maintenance’s usual lack of strategic character.

Research on the implementation of condition-based maintenance to improve a building’s energy performance, using a residential case study, is found in the literature [49]. Different scenarios involving thermal retrofitting—such as adding insulation and replacing windows—were analyzed through simulations to assess their impact on costs, considering specific implementation timings for each case. The study demonstrates how condition-based maintenance can contribute to optimizing maintenance planning while improving energy efficiency. Nevertheless, the conclusions emphasize that, despite the support of technological tools, maintenance outcomes remain strongly dependent on human judgement and assumptions. This highlights the inherent complexity of decision-making in this field. Therefore, research that integrates multiple dimensions influencing stakeholders’ decisions—such as determining the optimal timing for interventions and evaluating long-term energy and cost benefits under real conditions—remains a promising avenue for further study.

3. Methodology

3.1. Characterization of the Case Study

The present research is based on a practical case study, corresponding to a single-family house located in a neighbourhood in Sesimbra, Portugal (Figure 1). The region’s climate is classified as warm temperate with dry, hot summers (Csa), according to the Köppen–Geiger classification [50]. The mean annual temperature ranges between 16 °C and 17 °C, and the accumulated annual precipitation varies between 601 mm and 800 mm [51]. Average temperatures range from 8 °C to 15 °C in winter and from 20 °C to 30 °C in summer. The cold season is relatively mild due to the moderating influence of the nearby Atlantic Ocean, while summer temperatures can exceed 35 °C during heatwaves [52]. This building was specifically selected due to its extensive ten-year monitoring period, during which sensors captured granular data on energy consumption, indoor temperature, and humidity, providing a robust empirical baseline for validating the life-cycle assessments. Furthermore, the integration of these monitored attributes allows for a comparative analysis between generalized retrofitting solutions and tailored, condition-based decisions specifically adapted to this unique architectural and climatic context [16].

The orientations of the main façade, where the entrance of the house is located, and the access to the plot are northeast and northwest, respectively. A secondary construction, which functions as a garage, is also built in the southeast corner of the plot. This three-storey, semi-detached house connects with the neighbouring construction on the southwest side. The social spaces (kitchen and living room) are accommodated on the ground floor and the private areas (bedrooms and office) on the upper levels. The case study is characterized by current construction systems, which consist mainly of (i) a column–beam structure and slabs in concrete, (ii) walls built with hollow bricks and mortar, (iii) external claddings in painted render, (iv) ceramic roof tiles, and (v) aluminum-framed windows. The house’s only source of energy is electricity.

3.2. Overview of the Methodology

The methodological framework adopted in this study integrates two complementary approaches to assess the global life-cycle costs (LCC_g) of a residential building: (i) energy simulations, and (ii) condition-based maintenance planning. The energy simulations allow the estimation of the energy life-cycle costs (LCC_e) associated with the building’s operation, considering both the baseline scenario (before thermal retrofitting) and the optimal retrofitting solution (after thermal retrofitting). The condition-based maintenance methodology enables the evaluation of the maintenance life-cycle costs (LCC_m), according to different maintenance strategies (MS1, MS2, and MS3) defined for the building envelope elements.

The combination of these two approaches supports a comprehensive analysis of the building’s performance and long-term economic outcomes. The integration of LCC_e and LCC_m provides the global life-cycle costs (LCC_g), which represent the total economic impact over a 100-year time horizon. Figure 2 illustrates the overall methodological process, showing the relationship between the energy and maintenance analyses, and the resulting assessment of LCC_g.

3.3. Optimal Retrofitting Solution for Energy Efficiency: Before and After Scenarios

The background methodology concerning energy efficiency [16] enables the definition of an optimal retrofitting solution (ORS) to improve the performance of the case study, based on the following criteria: energy efficiency, retrofitting cost, durability and sustainability. The ORS consists of the combined thermal retrofit of the main building’s envelope elements by (i) adding external thermal insulation composite system (ETICS) with 40 mm rock wool panels to the external walls, for a total wall area of 185.33 m², (ii) adding 80 mm extruded polystyrene (XPS) panels above the roof slab, for a total area of 100.15 m², and (iii) replacing the existing window frames and glazing by others with better performance, for a total window area of 20.82 m².

The new aluminum windows are provided with thermal break frames and double-glazing, including 8 mm thick tempered glass, 16 mm air gap, and two 6 mm thick annealed glass sheets with a polyvinyl butyral (PVB) interlayer, from the exterior to the interior. The windows’ typology is tilt and turn, with two leaves. The colour of the finishing materials is white, both for the ETICS’s mortar and the window frame’s powder coating.

The ORS is analyzed in opposition to the baseline scenario (BS), which reflects the case study’s lowest performance in terms of energy efficiency, given the absence of any thermal measures (e.g., thermal insulation). The BS and ORS correspond to the building’s condition, regarding the constitution of its main envelope’s elements, before and after the thermal retrofit, respectively. These elements, defined with detail for the energy simulations in the background methodology, are presented in

Table 1. Layers of the building’s envelope elements, according to the BS and ORS.

	Windows	External Walls	Roof
BS (before the thermal retrofit)	Aluminium frame without thermal break and single-glazing
ORS (after the thermal retrofit)	Aluminium frame with thermal break and double-glazing *

* An 8mm thick tempered glass, 16mm air gap, and two 6mm thick annealed glass sheets with a polyvinyl butyral (PVB) interlayer, from the exterior to the interior. 1—painted plaster, 2—ceramic hollow bricks, 3—painted render, 4—adhesive base coat, 5—thermal insulation panels, 6—reinforcement layer and finishing coat, 7—ceramic tiles, 8—wood batten, 9—bituminous impermeable membrane, 10—levelling layer, 11—concrete slab, 12—PVC batten, 13—sub-roof panels, 14—waterproof breathable membrane.

. The BS and the ORS are the two main scenarios analyzed in the current study.

3.4. Condition-Based Maintenance: Planning and Life-Cycle Costs

The background methodology [17] assesses the effect of maintenance actions on the service life of building envelope elements. The impact of maintenance on durability is assessed by quantifying how much the maintenance actions improve the overall physical degradation condition of the elements, through the severity of degradation index S_w (Equation (1)) [53]. The methodology is based on condition-based maintenance strategies, whose actions are scheduled according to the condition of the elements, over a determined period. It consists of a probabilistic approach using a stochastic maintenance model, based on Petri Nets.

$$S_w={\displaystyle \frac{\sum \left(A_n\times k_n\times k_{a,n}\right)}{A\times k}}$$

(1)

S_w is the severity of degradation, in percentage;

A_n is the area affected by anomaly n, in m²;

k_n is the multiplication factor for the anomaly n, as a function of their degradation condition within the range K = {0, 1, 2, 3, 4};

k_a,n is the weighting coefficient according to the relative weight of anomaly n, according to their severity, repair cost, influence on the overall degradation of the component, propensity to cause other anomalies, and risk to the owners’ and users’ safety;

A is the total area of the component, in m²;

k is the multiplying factor corresponding to the highest degradation condition of the component with area A.

The maintenance strategies’ impact on the durability of the building’s envelope elements is analyzed according to the following parameters: number of interventions, service life, efficiency index, and life-cycle costs (LCC_m). All of these parameters can be estimated through the condition-based maintenance methodology [39]. Nevertheless, the most relevant in the context of the present study is the LCC_m (Equation (2)). The LCC_m corresponds to the sum of all the expenses necessary for the element to continue in operation, by the end of the determined time frame, under a specific maintenance strategy. It represents the costs concerning construction, inspections, and maintenance activities for that period.

$${LCC}_m=C_{initial}+\sum _{t=1}^t{C}_{inspection}+\sum _{t=1}^t{C}_{maintenance}$$

(2)

LCC_m is the implementation and maintenance life-cycle costs, in Euros;

C_initial is the construction cost, in Euros;

C_inspection is the annual inspection cost, in Euros;

C_maintenance is the annual maintenance cost, in Euros;

t is the time frame (100 years, in the current study), in years.

Existing databases of Sw values, based on onsite visual inspections of case studies in real service conditions, enabled the implementation of the methodology to several claddings or construction elements, such as renders in façades (RF), ceramic claddings in pitched roofs (CCPR), ETICS, and aluminum window frames (AWF) [39]. These previous studies provide evidence for the current analysis, namely the reference age at which the cladding or element reaches the degradation condition threshold for the implementation of the actions within each maintenance strategy (

Table 2. Reference age at which the building’s envelope elements reach the degradation condition required for the implementation of the actions within each maintenance strategy.

Maintenance Strategies	Building’s Envelope Elements
	External Walls				Roof		Windows
	RF		ETICS		CCPR		AWF
	MA	Age	MA	Age	MA	Age	MA	Age
MS1	TR	16	TR	18	TR	76	TR	40
MS2	1st MI	8	1st MI	12	1st MI	8	1st MI	32
	2nd MI	14	2nd MI	20	2nd MI	15	2nd MI	40
	TR	29	TR	31	TR	90	TR	55
MS3	1st CO	7	1st CO	5	1st CO	4	1st CO	9
	1st MI	10	2nd CO	8	2nd CO	6	2nd CO	12
	2nd CO	13	1st MI	17	1st MI	13	1st MI	36
	2nd MI	19	3rd CO	24	3rd CO	16	2nd MI	45
	3rd CO	26	4th CO	28	4th CO	20	3rd CO	46
	TR	36	2nd MI	29	2nd MI	24	4th CO	48
			5th CO	43	5th CO	39	TR	62
			TR	46	6th CO	47
					TR	102

RF—render in façade; ETICS—external thermal insulation composite system; CCPR—ceramic cladding in pitched roof; AWF—aluminum window frame; MA—maintenance action; TR—total replacement; MI—minor intervention; CO—cleaning operation.

). The maintenance strategies considered in the methodology are the following: MS1, a total replacement (TR); MS2, a combination of two minor interventions (MI) and a total replacement; and MS3, a combination of three cleaning operations (CO) interspersed with two minor interventions, and a total replacement.

The current study covers the implementation of the maintenance strategies MS1, MS2 and MS3 on external walls, roof and windows, according to two models, for a set maximum period of 100 years. Model 1 consists essentially of the BS (Table 1), in which the total replacements do not imply thermal improvements. Model 2 comprises both BS and ORS (Table 1). In this case, the initial construction corresponds to the BS, and the thermal retrofitting concerning the ORS is implemented in the context of the first TR. This solution is substituted by a similar one in the following total replacements. The ORS is introduced in the maintenance planning at different ages of the building’s envelope element, depending on the element and maintenance strategy (Table 2).

The reference costs used to calculate the LCC_m, in the current study, are presented in

Table 3. Reference costs used to calculate the LCC_m.

Building’s Envelope Elements		Model	Initial Application (€/m2)	Inspection (€/m2)	CO (€/m2)	MI (€/m2)	TR (€/m2)
External walls	RF	1	59.36	1.24	48.73	68.96	79.18
	RF + ETICS	2	59.36		55.09	75.35	100.87
Roof	CCPR	1	70.00	1.24	13.21	39.57	90.07
		2	70.00				146.70
Windows	AWF	1	218.83	1.24	4.65	76.07	223.01
		2	218.83				334.50

RF—render in façade; ETICS—external thermal insulation composite system; CCPR—ceramic cladding in pitched roof; AWF—aluminum window frame; CO—cleaning operation; MI—minor intervention; TR—total replacement.

, based on the database of construction and renovation costs for Portugal Gerador de Preços (https://geradordeprecos.info/, accessed on 10 October 2024).

The reference costs are multiplied by the respective area for each building element and annual occurrence of the action, according to each maintenance strategy (Table 2). The annual costs associated with the maintenance activities are then summed, considering the 100-year period of analysis (Equation (2)), encompassing the results of external walls, roof and windows.

3.5. Energy Simulations: Energy Consumption and Life-Cycle Costs

The new part of the methodology, developed for the present study, is based on global energy simulations of the case study to assess the life-cycle costs allocated to energy (LCCe) for the determined time horizon. The method for the energy simulations is the one used in the background methodology [16], applied to the same architectural model and Building Energy Model (BEM) [54]. The plug-in ‘Euclid’ is used to translate visual information from the BEM directly into the simulation software EnergyPlus as descriptive data. Subsequently, additional data are input into EnergyPlus [55], such as the parameters in

Table 4. Data input into EnergyPlus to perform the simulations.

Degrees from true North	160°	HVAC template	Ideal Loads Air System
Number of occupants	2	HVAC setpoint	20–25 °C
Artificial lights	9–10 W/m2	Window material	Clear—3 mm
Electric equipment	200 W/person	Ground media temperature	18 °C
Air changes per hour	50%	Climate archive location	Montijo—PRT (.epw file)
Percentage of ideal building use for thermal comfort per day  41%

. The recorded climate data used from 2009 to 2023.

The LCC_e corresponds to the sum of all the owner’s expenses, during the building’s service life, necessary to heat and cool the interior spaces, based on thermal comfort requirements, and to guarantee the functioning of equipment and artificial lighting. Annual energy consumption values are necessary to calculate the LCC_e. The sum of the monthly output given by the energy simulations for a one-year period results in the whole year consumption, which, multiplied by the reference market value from the Portuguese electricity supplier EDP (0.15 €/kWh approximately), leads to the base annual energy consumption value (AEC) (Equation (3)).

$$AEC=(\sum _{m=1}^m{E}_{heating}+\sum _{m=1}^m{E}_{cooling }+\sum _{m=1}^m{E}_{equipmant }+\sum _{m=1}^m{E}_{lighting} ) . C_{energy }$$

(3)

AEC is the base annual energy cost, in Euros;

E_heating is the energy consumption for heating, in kWh;

E_cooling is the energy consumption for cooling, in kWh;

E_equipment is the energy consumption for equipment functioning, in kWh;

E_lighting is the energy consumption for artificial lighting, in kWh;

m is the number of months comprised in one year, in months;

C_energy is the cost of energy, in €/kWh.

As referred to above, the LCC_e study is done for a 100-year time horizon and covers both models (1 and 2) and maintenance strategies (MS1, MS2 and MS3) analyzed in the case of LCC_m. In the case of Model 2, the LCC_e for the whole period of analysis is composed of different AEC, as the building’s energy consumption depends on the thermal performance of the envelope’s elements. This is influenced by the thermal improvements in the context of maintenance, which coincide with the TR actions concerning external walls, windows and roof (

Table 5. AEC based on the different annual energy consumption reference values.

	AE1 (€)	AE2 (€)	AE3 (€)	AE4 (€)
AEC	2736.78	2123.29	2021.33	1451.13

). Therefore, the following four energy simulations are performed to obtain all the necessary annual energy consumption reference values: (i) no improvement scenario (AE₁), (ii) including the first projected TR, which involves external walls (AE₂), (iii) including the first and second projected TR, which encompass external walls and windows (AE₃), and (iv) including the first, second and third projected TR, which encompass external walls, windows and roof (AE₄). In the LCC_e assessment of Model 1, the AE₁ is the only reference value needed because thermal improvements are not considered. The AEC can correspond to four different values, as the E_heating, E_cooling, E_equipment and E_lighting (Equation (3)) sum corresponds to the annual energy consumption, which varies based on AE₁, AE₂, AE₃ and AE₄.

The periods during which each thermal improvement is in operation in MS1, MS2 or MS3, considering the time horizon of 100 years, are presented in Table 6. These periods are essential to calculate the LCC_e of Model 2 (Equation (4)). As for Model 1, they are not necessary, since the TR actions do not imply thermal improvements. The LCC_e of Model 1 remains constant regardless of the maintenance strategy. The AEC is subjected to an inflation rate throughout the period of analysis, according to data sourced from the Energy Services Regulatory Authority (ERSE). The rate applied to each year’s AEC results from the mean of the previous ten years’ inflation rate values, which corresponded to 2.5% in 2025.

$${LCC}_e=\sum _{t=1}^t{(AEC}_1. i_t)+\sum _{t=1}^t{(AEC}_2. i_t)+\sum _{t=1}^t{(AEC}_3. i_t)+\sum _{t=1}^t{(AEC}_4. i_t)$$

(4)

LCC_e is the energy life-cycle costs, in Euros;

AEC₁ is the annual energy cost without thermal improvements, in kWh;

AEC₂ is the annual energy cost with thermal improvements of external walls, in kWh;

AEC₃ is the annual energy cost with thermal improvements of external walls and windows, in kWh;

AEC₄ is the annual energy cost with thermal improvements of external walls, windows and roof, in kWh;

i_t is the inflation rate of the year t, in percentage;

t is the time frame (100 years, in the current study), in years.

Table 6. Period in operation of each thermal improvement implemented through a TR action, according to the maintenance strategies MS1, MS2 and MS3, for the 100-year time horizon.

Maintenance Strategy	Period in Operation of the Thermal Improvement (Years)
	-	External Walls	External Walls Windows	External Walls Windows Roof
	AE1	AE2	AE3	AE4
MS1	16	24	36	24
MS2	29	26	35	10
MS3	36	26	38	*

* The roof is not replaced in the case of MS3, because the end of service life occurs after the 100-year time horizon, according to this maintenance strategy.

Table 6. Period in operation of each thermal improvement implemented through a TR action, according to the maintenance strategies MS1, MS2 and MS3, for the 100-year time horizon.

Maintenance Strategy	Period in Operation of the Thermal Improvement (Years)
	-	External Walls	External Walls Windows	External Walls Windows Roof
	AE1	AE2	AE3	AE4
MS1	16	24	36	24
MS2	29	26	35	10
MS3	36	26	38	*

* The roof is not replaced in the case of MS3, because the end of service life occurs after the 100-year time horizon, according to this maintenance strategy.

3.6. Global Life-Cycle Costs

The final stage of the methodology concerns the estimation of global life-cycle costs (LCC_g) (Equation (5)), which encompasses both LCC_m and LCC_e, for the same time horizon of 100 years [52]. The LCC_g are calculated for Models 1 and 2, considering the maintenance strategies MS1, MS2 and MS3.

$${LCC}_g={LCC}_m+{LCC}_e$$

(5)

LCC_g is the global life-cycle costs, in Euros;

LCC_m is the implementation and maintenance life-cycle costs, in Euros;

LCC_e is the energy life-cycle costs, in Euros.

Also, the impact of introducing the optimal retrofitting solution in the maintenance planning in terms of life-cycle costing is quantified by assessing the differences between (i) both models’ results, considering each maintenance strategy, and (ii) the results of the three maintenance strategies, considering each model.

4. Results and Discussion

The LCC_m results show that, regardless of Models 1 or 2, the costs are the lowest for MS1 and the highest for MS3 (

Table 7. LCC_m for Models 1 and 2, according to the maintenance strategies MS1, MS2 and MS3, and costs comparison, for the 100-year period of analysis.

Models	Maintenance Strategies
	MS1	MS2	MS3
1 (BS)	37,367.90 €	53,047.84 €	67,760.85 €
2 (BS + ORS)	38,080.53 €	52,636.66 €	67,863.05 €
Costs comparison	712.63 €	−411.19 €	102.20 €

). This suggests that the LCC_m increases with the complexity of the maintenance strategy, which is progressively higher from MS1 to MS3, considering the number of planned actions (Table 2). Maintenance according to strategy MS3 is 45% more expensive than MS1 in the case of no thermal retrofitting, by the end of the time horizon. This percentage falls to 44% when improvement measures are implemented. Upgrading the building in terms of energy efficiency, through the ORS, leads to higher maintenance costs (Table 7). Nevertheless, the difference in LCC_m between Models 2 and 1, by the end of the 100 years, is not significant regardless of the maintenance strategy (Figure 3), ranging between 1.02 € and 7.13 € per year.

The LCC_m difference between both models is more accentuated in the case of MS1, probably due to shorter TR cycles, which imply more maintenance actions over the whole-time span, comparatively with MS2 and MS3. The cost of a TR is considerably higher than the expenses concerning CO or MI, especially for windows and roof, which, combined with its higher frequency, can be impactful on the LCC_m comparison value between models for MS1. The values corresponding to MS2 and MS3 can be affected by the CO and MI timing differences between renders and ETICS in façades (Table 2). While for windows and roof the timings of these maintenance operations are the same for Models 1 and 2, this does not apply to external walls, because the thermal improvement implies a change in the type of cladding. External walls represent 59–63% of the total LCC_m value, while both windows and roof represent the remaining percentage (Figure 3).

The LCCm difference between Models 1 and 2 is mainly due to (i) the costs of replacing the existing solutions for the ORS with one with better thermal performance, concerning all the intervened elements, and (ii) the costs and timings of the other maintenance actions in external walls. The cost of CO and MI on windows and roof is identical in both models, because the implementation of these maintenance operations concerns the ceramic claddings and external surface of the aluminum frames, according to the background methodology [17]. These components are the same even in the case of the thermal retrofitting comprised in Model 2, as well as the respective maintenance actions’ schedule and costs. As for external renders and ETICS in façades, the expenses and timings associated with the several types of maintenance activities are different.

The results in Table 7 indicate that a less sophisticated maintenance strategy, such as MS1, based only on the total replacement of building’s elements by the end of service life, is the least expensive option in terms of LCCm (Figure 4). However, it is important to bear in mind that maintenance is crucial for extending the service lives of buildings and for the sustainability of constructions, considering environmental concerns [56]. The end of service life depends on defined performance requirements. Obsolescence is reached when the condition of the building or its elements does not meet these requirements. The concept of obsolescence is comprehensive and can involve social, aesthetic, regulatory and environmental aspects [57]. The end of service life can be due to objective factors (e.g., safety and functionality) and subjective ones (e.g., aesthetic and social), which tend to vary depending on the stakeholder and on period values [58]. This means that a non-compromising level of physical degradation, regarding the building’s operation, might not be acceptable to the owner, considering its several demands. In this context, opting for a maintenance strategy that includes minor operations, such as MS2, can be a balanced choice in compliance with higher standards, which would cost just more 156.80 € per year than MS1 (Table 7). Also, choosing maintenance over letting the envelope’s elements fully degrade can prevent escalating damage and overall degradation. This is associated with external claddings and windows for being the first protection layer, thus considerably exposed, susceptible to degradation agents, and prone to defects that can affect the whole building’s performance [43,59].

The LCC_e outcomes reveal that annual energy-related costs are lower for Model 2, regardless of the maintenance strategy (

Table 8. LCC_e for Models 1 and 2, according to the maintenance strategies MS1, MS2 and MS3, and costs comparison, for the 100-year period of analysis.

Models	Maintenance Strategies
	MS1	MS2	MS3
1 (BS)	283,756.65 €	283,756.65 €	283,756.65 €
2 (BS + ORS)	209,194.94 €	227,150.20 €	238,731.80 €
Costs comparison	74,561.70 €	56,606.45 €	45,024.85 €

; Figure 5). The savings in energy consumption by implementing thermal improvements through the ORS, within the context of maintenance planning, range between 45,024.85 € and 74,561.70 €, depending on the maintenance strategy. Model 1 represents the highest possible energy expenses, because it does not include thermal insulation measures. In this case, the LCC_e is the same for all the maintenance strategies (Table 8), since no thermal retrofitting is involved in TR and the energy consumption is not altered by the planned activities. The comparison of maintenance costs—LCC_m (Table 7)—indicates that a relatively small additional investment in thermal retrofitting can result in substantial annual energy savings over the analysis period. Specifically, an extra 7.13 € spent annually on maintenance corresponds to an average annual energy saving of 745.62 €, assuming the cost comparison values for MS1 are evenly distributed throughout the 100-year period.

The results for Model 2 show that the decrease in energy demand is more significant in the case of MS1 (Table 8; Figure 5), mainly because the first TR actions are scheduled earlier than in MS2 and MS3 (Table 2). TR are expected to happen 13–15 and 20–26 years later in the case of MS2 and MS3, respectively, depending on the building’s element, compared to MS1. The first TR consists of an opportunity for thermal retrofitting, in Model 2, and the respective timing affects the LCC_e. The sooner the benefits in terms of energy efficiency become effective, the lower the energy budget by the end of 100 years. The schedule of the first TR actions planned in MS1 leads to 8% and 12% lower LCC_e than the LCC_e of MS2 and MS3, respectively.

MS1 is also the maintenance strategy where all the considered building elements are simultaneously retrofitted sooner. The AEC (Table 5), which depends on the annual energy consumption reference values (AE₁, AE₂, AE₃ and AE₄), varies according to the elements that are already retrofitted. The first type of element to be subjected to a TR corresponds to the external walls, based on the planning of maintenance activities in MS1, MS2 and MS3 (Table 2). The second and third ones are the windows and roof, respectively. In Model 2, the energy efficiency level reaches its peak (AE₄) once the planned maintenance activities have encompassed the TR of the three types of elements, improving their thermal performance. This is expected to occur first for MS1, followed by MS2 and MS3, in this order. The annual energy cost (AEC) decreases as the number of retrofitted building elements increases, from AE₁ to AE₄, leading to higher reductions in energy costs (Figure 6 and Table 5). The AEC becomes 22% lower if the external walls are thermally improved with ETICS compared to the original cladding solution before maintenance. The savings in AEC increase to 47% if the thermal improvement comprises the windows and roof, in addition to the external walls.

The LCC_g results reflect the preponderance of the LCC_e on global costs (

Table 9. LCC_g for Models 1 and 2, according to the maintenance strategies MS1, MS2 and MS3, and costs comparison, for the 100-year period of analysis.

Models	Maintenance Strategies
	MS1	MS2	MS3
1 (BS)	321,124.55 €	336,804.49 €	351,517.50 €
2 (BS + ORS)	247,275.47 €	279,786.86 €	306,594.85 €
Costs comparison	73,849.08 €	57,017.63 €	44,922.65 €

). LCC_e represents 81–88% and 78–85% of LCC_g of Models 1 and 2, respectively, depending on the maintenance strategy (Figure 7). Model 2 is associated with significantly lower global costs, as in the case of LCC_e (Table 8), below the LCC_g of Model 1 in 23%, 17% and 13% for MS1, MS2 and MS3, respectively. MS1 is the maintenance strategy leading to the lowest LCC_g, like in the previous results (Table 7 and Table 8), whose value is 19% less than that of MS3.

The decision for the implementation of maintenance according to Model 2 and strategy MS1 stands out as the best, in terms of LCC_g, considering the 100-year time horizon. This is mainly due to the alignment of planned maintenance activities with the opportunity for thermal improvements as well as their earlier implementation, compared to other strategies. However, opting for strategy MS2 in Model 2 would still lead to LCC_g savings while improving the building’s durability and physical degradation conditions, based on proper maintenance care. The latter scenario would have an annual additional cost of just 325.11 €, considering that the result of the cost comparison between MS1 and MS2 is evenly distributed over the whole time span.

The outcomes of the LCC analysis reveal that the benefits in terms of energy savings compensate for the investment in the thermal retrofitting of the envelope’s elements, according to the ORS, in the long term. The implementation of maintenance with the goal of enhancing the building’s energy efficiency and reducing the respective costs, through the improvement of thermal performance, is advantageous regardless of the maintenance strategy. The LCC_g savings from choosing the least expensive maintenance strategy, MS1, based on the replacement of elements once they have reached the end of service life, are not significant compared to MS2, corresponding to 12% for Model 2.

5. Conclusions

In the present research, the energy LCC_e, maintenance LCC_m, and global LCC_g of a real-world case study are analyzed, based on simulations for different models and maintenance strategies. Model 1 corresponds to a baseline scenario, lacking thermal improvement measures; Model 2 corresponds to a scenario where the ORS is implemented. The ORS includes the thermal retrofitting of external walls, windows and roof, which take place within the context of the following three possible maintenance strategies: MS1, based on the replacement of elements when they reach the end of service life; MS2, additionally includes prior minor interventions; and MS3, that considers cleaning operations as well before the maintenance activities already considered in MS1 and MS2. The maintenance activities extend the service life of the building’s elements; thus, the respective schedule varies according to the maintenance strategy. The study enables the quantification of the ORS impact on the LCC_g and estimates the best timing to intervene or which maintenance strategy to adopt.

The outcomes of the study indicate that the number of planned maintenance activities and the respective schedule, according to the different maintenance strategies, influence the LCC results. MS1 leads to the lowest LCC_m. However, MS2 could be a balanced choice in terms of cost–benefit, considering that the additional cost of minor operations enables the building to meet stakeholders’ higher standards. As for LCC_e, MS1 also leads to the highest savings. This is mainly due to the earlier scheduling of the thermal retrofitting of the building’s elements compared to MS2 and MS3. In the case of MS1, the service life of the elements is not extended through CO and MI, so their replacement needs to occur sooner. This is advantageous for improving energy efficiency and reducing consumption, which has a direct positive impact on LCC_e. The LCC_e are preponderant to the LCC_g, representing a strong majority of the costs. The implementation of thermal improvement measures, through the ORS, represented by Model 2, is clearly beneficial in terms of LCC_e and LCC_g. It contributes to increasing the LCC_m, comparatively with Model 1, although not significantly. The slight rise in the maintenance costs compensates for the subsequent considerable savings in energy consumption.

The economic viability of the optimal retrofitting solution (ORS) was further evaluated through a payback period analysis, considering the incremental investment required for the building’s envelope elements—totalling €12,012.52 based on the specific intervention areas (185.33 m² of walls, 100.15 m² of roof, and 20.82 m² of windows). The results indicate that the payback period is intrinsically linked to the adopted maintenance strategy: 16.3 years for MS1, 21.1 years for MS2, and 26.7 years for MS3. Although LCC analysis remains the primary tool for long-term decision-making over a 100-year horizon, these payback figures provide a practical metric for stakeholders.

The results of the study confirm that maintenance can be an opportunity to enhance building energy efficiency. The simultaneous improvement of the building’s physical degradation condition and energy performance, through maintenance activities, is advantageous to the stakeholder, who benefits from long-term cost optimization and concurrent benefits.

Although LCC analysis is crucial for supporting decision-making, it remains a complex process that involves multiple interrelated criteria. Investments in maintenance can generate additional benefits that were not directly quantified in the present study, such as increases in the building’s asset value. Effective maintenance management not only prevents neglect and physical degradation but also contributes positively to users’ comfort and well-being. Future research that incorporates quantifiable indicators of these broader benefits would further support the decision-making process. Moreover, including payback time assessments in the analysis of LCC savings could provide valuable insights for evaluating long-term economic viability.