Heat Recovery Ventilation and Thermal Insulation: Economic Decision-Making in Central European Households

Abstract

Energy conservation has become a critical issue, especially in the context of global environmental challenges and rising energy costs. This article emphasizes the growing importance of sustainability by integrating technical evaluations of heat recovery ventilation (HRV) systems and energy demand reduction with an economic analysis of new detached buildings in Poland. We studied the economic efficiency of the application of HRV in the context of different insulation thicknesses and quantities of air exchanged. Through over 2500 building energy performance simulations, the study explores the economic and environmental interplay between investments in HRV and insulation technologies. The findings demonstrated that households can achieve significant energy savings, around 2600 kWh annually, by installing an HRV system. These savings are contingent upon various factors, including air exchange rates, insulation thickness, and the thermal properties of windows. The economic analysis revealed that economic benefits due to optimal insulation are in the range of EUR 1000–8600 and from EUR 500 up to 5900 regarding investment in HRV, depending on the energy price and intensity of ventilation.

1. Introduction

The intersection of environmental politics and residential energy consumption is driving a greater emphasis on energy efficiency, renewable energy adoption, electrification, and sustainable building practices. These efforts are critical not only for mitigating climate change but also for advancing long-term environmental sustainability. Buildings, which account for approximately 40% of global energy consumption and over 30% of total greenhouse gas emissions [1,2], play a central role in the global push for sustainability. Notably, energy used for ventilation alone can range from 10% to 50% of a building’s total electricity consumption [3]. This underscores the significant potential for reducing environmental impacts by optimizing ventilation and energy efficiency in residential buildings.

Energy consumption in residential buildings can vary widely depending on factors such as geographic location, climate conditions, building size and age, construction materials, occupancy habits, and the level of energy efficiency measures in place. In light of these complexities, it is increasingly important to focus on sustainable solutions—such as improved insulation, efficient ventilation systems, and the integration of renewable energy sources—that not only reduce the environmental impact but also ensure comfortable and energy-efficient living conditions for occupants.

Although HRV has been discussed extensively in the current literature, no studies have been identified that specifically address the context of Central European countries while simultaneously incorporating the optimization of external envelope heat transfer coefficients and HRV systems. This study focuses on building performance with respect to two highly influential parameters—thermal insulation and ventilation—from both technical and economic perspectives. These two characteristics have been selected due to their relative accessibility for modification during the construction phase, in contrast to factors such as building orientation, geological conditions, or shading, which are less easily controlled but also significantly affect energy performance. The following section presents findings from some of the most recent studies concerning HRV and/or the optimization of external envelope thermal properties. Gauch et al. [4] noticed a lack of systematic investigation of more characteristics of the building and they introduced it in their study. They found out that HRV significantly and positively influenced building efficiency, but their study concerned only multi-story buildings. Our research can also be compared to the work of Saari et al. [5], who analyzed detached houses—in different regulatory frameworks and with different given heat transfer coefficients—but their study did not focus on insulation and HRV optimization, and their study also concerned the Finnish climate.

Kim et al. [6] focused on three locations in Norway to investigate the energy efficiency of decentralized ventilation systems in cold weather conditions compared to centralized ventilation systems. They determined a suitable ventilation system for adapting to cold climates. Meanwhile, Dodoo et al. [7] used a multi-family building in Sweden to show how various technical and economic-related parameters can be used to achieve deep energy savings cost-efficiently.

Kaya et al. [8] quantified the factors that influence rural homeowners’ decisions to invest in exterior insulation to improve energy efficiency, lower heating costs, and reduce air pollution, ash disposal, and the time spent monitoring coal-burning stoves. Liu et al. [9] performed a global sensitivity analysis and optimized the design of an HRV for zero-emission buildings. They quantified the contributions of various design input parameters to the variation in annual recovery efficiency and annual net energy savings. Fouih et al. [10] provided a global comparison of three standard ventilation systems used in residential and commercial buildings in different climate zones (France). They also conducted a sensitivity analysis of ventilation system parameters on energy savings. Mróz and Dutka [11] provided a new approach to evaluating heat recovery devices in a mechanical ventilation system. Their evaluation was based on an exergy balance equation and economic analysis, which required the application of a multicriteria decision aid method. Their proposed set of evaluation criteria comprised driving exergy, simple payback time, and investment costs.

Heat recovery systems (HRV) have been increasingly recognized for their potential to significantly enhance energy efficiency in buildings. Various studies demonstrated how HRV systems can save up to 60% of heat energy, as seen in recent research [12]. By integrating energy-efficient technologies, such as air-to-air heat pumps, solar photovoltaic systems, and solar thermal domestic hot water systems, HRV can further improve energy savings. For instance, simulations showed that HRV use leads to a 7% reduction in heat pump energy consumption annually [13]. Studies by Hamdy et al. [14] found that HRV systems with efficiencies between 60% and 80% provided optimal low-emission and cost-effective solutions. Similar results were observed in building retrofits in subarctic Sweden by Shadram et al. [15], and in residential buildings in the Netherlands [12].

Thermal insulation in residential buildings, in addition to an HRV system, can yield significant energy savings by reducing heating and cooling loads. Demir et al. [16] provided a general analytical solution for the optimum distribution of thermal insulation material for volumes confined with environments at different temperatures for a given investment cost or constant insulation material volume. Gagliano and Aneli [17] analyzed another method of energy-saving solution—ventilated facades—but their research refers to the Italian climate and, as they noticed in their study, the performance of ventilated facades is greater in warmer climates. Adamczyk and Dylewski [18] demonstrated the importance of thermal insulating investment in buildings across three areas: economic, environmental, and social. Their analysis considered various factors, including the condition of the building before thermal insulation, the type of construction material used in the building, the heat source, the type of thermal insulation, and the climate zone in which the building is located. In another paper, Dylewski and Adamczyk [19] presented economic and ecological indicators for thermal insulating building investments. They [20] proposed a methodology for assessing both the economic and ecological benefits that result from changing the user profile and thermal insulation performance. The balances of ecological benefits were analyzed in accordance with the idea of sustainable development by adopting model residential buildings.

HRV systems play an important role not only in energy optimization, but also in improving thermal comfort [21], dehumidification [22,23], and in combination with air-to-air heat pumps in cost-efficient heating/cooling systems [24]. Using wastewater energy to preheat air used in HRV was analyzed by Ploskić and Wang [25], and they concluded that such a system can reduce ventilation heating demand by 27% and 40%, depending on the air preheater’s size, and mitigate the severe outdoor climate of northern Sweden, in which this study was undertaken. Similar conclusions were presented by Cablé et al. [26], where a wood-burning stove as a preheating source was added to the system with HRV in French and Norwegian locations.

This study integrates thermodynamic and financial analysis to evaluate two key investment decisions made by private individuals constructing new residential buildings: the selection of thermal insulation and the implementation of heat recovery ventilation (HRV) systems. By combining technical calculations with economic evaluation, the analysis provides investors with a more comprehensive basis for decision-making, linking energy performance with financial implications.

These considerations are particularly relevant in light of tightening energy efficiency standards and the growing need to reduce carbon emissions. Despite increasing attention to sustainable building practices, there remains a noticeable gap in the literature regarding the combined assessment of HRV and insulation strategies under Central European climatic conditions. Poland was selected as a representative case due to its temperate climate and the high share of the population—over 58%—residing in detached or semi-detached houses.

Recent studies have addressed selected aspects of energy demand in Polish residential buildings. Hurnik et al. [27] analyzed the energy performance of a typical occupied single-family home through comprehensive on-site diagnostics, evaluating energy consumption across four stages of thermal renovation. Amanowicz et al. [28] reviewed advancements in ventilation systems aimed at reducing energy use, focusing on research from the past three years. Basińska et al. [29] developed a multi-objective optimization model for the thermal modernization of multi-family buildings, considering insulation materials, window types, and their impact on costs, primary energy use, and CO₂ emissions.

While these contributions offer valuable insights, none address the full scope of issues considered in the present study. To date, no research has been identified that examines a newly built private residential building in Poland, incorporating a wide range of U-values for various envelope components, airtightness levels, and ventilation intensities, alongside an economic evaluation that reflects fluctuating energy prices.

The case study focuses on a newly constructed detached building, as existing homes in Poland commonly rely on gravity-based ventilation systems integrated with chimneys and window grilles. Retrofitting such systems is typically costly and complex, often requiring the removal or modification of chimneys, ventilation shafts, and windows. Due to this variability and lack of consistent data on retrofit costs, existing buildings were excluded from the scope of this analysis.

The novelty of this work lies in its extensive simulation framework evaluating the thermal performance of building envelopes with varying U-values and the impact of HRV systems on energy efficiency. This is complemented by a financial analysis that accounts for the cost and availability of commonly used energy sources, offering a realistic perspective on the feasibility and benefits of different design choices.

2. System Description

Simulations in this study were conducted using a model of a newly constructed single-family house located in central Poland, specifically in the Łódź area. The house, designed for two to six occupants, consists of two stories with no basement (the layout of a single floor (ground floor) is presented in Figure 1), offering a total usable area of 175.26 m² and a usable volume of 464.5 m³. It is equipped with an underfloor heating system. The external walls are made of 0.24 m-thick autoclaved aerated concrete, and the foundation consists of a 0.25 m-thick concrete slab. Most of the windows, as well as the longer side of the building, face south. Simulations were conducted for this building considering different insulation thicknesses, both with and without the implementation of an HRV system. In the scenarios without the HRV system, natural ventilation was assumed. Detailed information about the building is provided in

Table 1. External building partitions—surface area, thermal properties, and unit cost of insulation materials.

Barrier	Area	Insulation Material	Thermal Conductivity	Density	Specific Heat	Cost
	m2		W/mK	kg/m3	kJ/kgK	EUR/m3
Floor	92.5	Extruded polystyrene XPS	0.035	60	0.75	104.6
Ceiling	102.3	Mineral wool	0.037	100	1.03	45.5
External walls	266.2	Polystyrene EPS	0.038	20	1.46	52.3
Windows	22.5	N/A	N/A	N/A	N/A	N/A

and

Table 2. An overview of the building envelopes for a selected insulation thickness.

Symbol	Layer Thickness	Material Description
	m
ROOF
Roof-Sheeting	0.0100	Trapezoidal sheet metal or tile sheet metal
Polyethylene	0.0010	Polyethylene foil
Pine	0.0650	Cross-grain pine wood
Internal resistance of heat transfer, Ri (m2·K/W):			0.100
External resistance of heat transfer, Re (m2·K/W):			0.040
Total resistance of heat transfer and conduction, R (m2·K/W):			0.551
Overall heat transfer coefficient, U (W/(m2·K)):			1.813
CEILING
Wool	0.2000	Rock mineral wool
Polyethylene	0.0020	Polyethylene foil
Plasterboard	0.0200	Plasterboard
Finish-CW	0.0100	Cement-lime plaster or smooth finish
Internal resistance of heat transfer, Ri (m2·K/W):			0.100
External resistance of heat transfer, Re (m2·K/W):			0.100
Total resistance of heat transfer and conduction, R (m2·K/W):			5.715
Overall heat transfer coefficient, U (W/(m2·K)):			0.175
WALL
Finish-CW	0.0100	Cement-lime plaster or smooth finish
YTONG	0.2400	Ytong 600-PP4/0.6 S+GT
EPS 70-038	0.1500	Polystyrene
Finish-CW	0.0100	Cement-lime plaster or smooth finish
Internal resistance of heat transfer, Ri (m2·K/W):			0.130
External resistance of heat transfer, Re (m2·K/W):			0.040
Total resistance of heat transfer and conduction, R (m2·K/W):			5.742
Overall heat transfer coefficient, U (W/(m2·K)):			0.174
FLOOR
Wall at the floor level: SZ1
Difference in floor height and groundwater level, Zgw: 4.00
Terracotta	0.0200	Terracotta
Reinforced concrete	0.0500	Reinforced concrete
Polyethylene	0.0020	Polyethylene foil
STYR_FUND	0.1000	Foundation polystyrene
Reinforced concrete	0.2500	Reinforced concrete
Polyethylene	0.0020	Polyethylene foil
XPS 200	0.2000	Insulation XPS
Polyethylene	0.0020	Polyethylene foil
BET-Lean	0.1000	Lean concrete slab
Gravel	0.5800	Gravel
Equivalent ground resistance along with transfer resistances, Rg (m2·K/W):			1.437
Total resistance of heat transfer and conduction, R (m2·K/W):			10.616
Overall heat transfer coefficient, U (W/(m2·K)):			0.094

. Table 1 includes the surface areas of individual external building elements, such as walls, roof, floor, and windows. Additionally, it presents the types of insulation materials applied to each partition, along with their thermal properties (e.g., thermal conductivity, density, and specific heat). The unit cost of the insulation materials is also provided, which was used in the economic analysis. Table 2 presents an overview of the building envelopes for a selected insulation thickness, which serves as a variable parameter in the simulations. It includes the calculated thermal resistance of each envelope component, along with the overall heat transfer coefficient.

The numerical values of the following variables are the main results of the simulations:

• Ventilation: total volume of air exchange (m³/h) controlled by the ventilation system,
• Infiltration: total volume of air exchange (m³/h) uncontrolled by the ventilation system,
• Overall heat transfer coefficient (U) of the external walls ($U_{ew}$), floor ($U_{fl}$), and ceiling ($U_{ce}$).

In real-life conditions, a ventilation system can generally be controlled by the end user, i.e., the homeowner, with ease and precision in the case of mechanical systems and, in the case of natural ventilation systems, only partially and with some problems. We have introduced two values for the ventilation intensity (V) variables in the simulations: 140 m³/h and 210 m³/h. Both meet the Polish legal requirements of a minimum volume of air exchange equal to 20 m³ per person.

Infiltration is impacted by air changes per hour (ACPH), given a pressure difference of 50 Pa between the interior of the building and the external environment. Two ACPH values were simulated: for a very tightly sealed building (ACPH = 1) and for standard building envelope airtightness (ACPH = 4).

A total of 2512 simulations were conducted, with the simulations divided as follows: 1256 simulations were performed for natural ventilation, and 1256 simulations were carried out with a heat recovery ventilation (HRV) system (with a heat recovery efficiency of 60%). For each of the 1256 simulations, different insulation thicknesses were considered for the external walls (ranging from 0.1 m to 0.35 m), as well as variable insulation thicknesses for the floor and ceiling. Changes in these insulation thicknesses influenced the overall thermal resistance and, consequently, the overall heat transfer coefficient (U-value) of the building envelope, with the values of the heat transfer coefficients determined by the typical thicknesses of insulation materials available on the market. Thus, the simulations were performed for various combinations of heat transfer coefficients for the individual building components, with the corresponding U-values (starting values). Heat exchange for external walls was simulated with 11 different values of the overall heat transfer coefficient (W/m²K): 0.103, 0.112, 0.116, 0.119, 0.123, 0.127, 0.132, 0.137, 0.142, 0.153, and 0.174, which resulted from the assumed varying thickness of the external wall insulation applied in the simulation. For the floor, five values of overall heat transfer coefficient were used (W/m²K): 0.074, 0.094, 0.109, 0.120, and 0.128, and for the ceiling, three values were used (W/m²K): 0.09, 0.12, and 0.18. For doors, only one standard value (1.3 W/m²K) was assumed. For windows, two values of the overall heat transfer coefficient were used: 0.90 W/m²K and 0.74 W/m²K.

Using the set of parameters described above, 2512 simulations of the total heat energy demand for the analyzed building were performed. For each simulation, the annual heating demand of the building was calculated. The data (U-parameters) were used to create the 2512 simulations, so we received a set of possible results of heating demand, costs, and NPV, and we could use these ‘output’ data to draw conclusions presented in the article.

3. Methodology and Heating Demand Calculations

The amount of energy required to heat a building depends on various factors, including the building’s size, insulation, climate, heating system efficiency, and desired indoor temperature. Energy requirements can also be estimated based on historical data, energy consumption patterns, or through energy simulation software commonly used in building design and energy analysis. It is important to conduct a thorough analysis considering all relevant factors to accurately determine the energy required for heating a specific building. The program Audytor OZC ver. 7.0 (Sankom Ltd., Warsaw, Poland) was used to determine the annual heat demand of the single-family building. The software was used to support the calculation of the design heat load of rooms, to determine the seasonal demand for heat energy according to the current standards [30,31,32].

The design heat load (${\Phi }_{HL,i}$) consists of the total design heat loss and excess thermal power, and it is determined by the following equation [30]:

$${\Phi }_{HL,i}={\Phi }_{T,i}+{\Phi }_{V,i}+{\Phi }_{RH,i},$$

(1)

where:

${\Phi }_{T,i}$—design heat loss of the heated space (i) by penetration, W,

${\Phi }_{V,i}$—design ventilation heat loss of the heated space (i), W,

${\Phi }_{RH,i}$—excess thermal power required to compensate for the effects of weakened heating of the heated space (i), W.

Design heat loss of the heated space (i) by penetration can be determined from the formula [30]:

$${\Phi }_{T,i}=\left(H_{T,ie}+H_{T,iue}+H_{T,ig}+H_{T,ij}\right)·\left({\theta }_{int,i}-{\theta }_e\right),$$

(2)

where:

$H_{T,ie}$—coefficient of heat loss by transfer from the heated space (i) to the environment (e) through the building envelope, W/K,

$H_{T,iue}$—coefficient of heat loss by transfer from the heated space (i) to the environment (e) through the unheated space, W/K,

$H_{T,ig}$—coefficient of heat loss by transfer from the heated space (i) to the ground (g) under steady state, W/K,

$H_{T,ij}$—coefficient of heat loss by transfer from the heated space (i) to the adjacent heated space to a significantly different temperature, W/K,

${\theta }_{int,i}$—design internal temperature of the heated space (i), °C,

${\theta }_e$—design external temperature, °C.

To calculate the heat loss of the heated space using Equation (2), it is necessary to determine the temperature difference between the design internal temperature of the heated space (i) and the design external temperature. The external design temperature is dependent on the building’s location within Poland, specifically on the climatic zone in which the building is situated. Poland has been divided into five design zones (I–V), with external air temperatures ranging from −16 °C (coastal areas) to −24 °C (mountainous regions and the Suwałki area). The humidity was set at 100%. Climatic zones allow for the determination of the basic calculation parameters for the external air. For each zone, there is a specific design external temperature:

• Zone I: −16 °C
• Zone II: −18 °C
• Zone III: −20 °C
• Zone IV: −22 °C
• Zone V: −24 °C

Design ventilation heat loss of the heated space (i) is calculated from the following relationship [30]:

$${\Phi }_{V,i}=H_{V,i}·\left({\theta }_{int,i}-{\theta }_e\right),$$

(3)

where:

$H_{V,i}$—coefficient of design ventilation heat loss, W/K, determined from the formula:

$$H_{V,i}=\dot{V_i}·\rho ·c_p,$$

(4)

where:

$\dot{V_i}$—ventilation air flow rate of the heated space (i), m³/s,

$\rho$—density of air at temperature ${\theta }_{int,i}$, kg/m³,

c_p—specific heat of air at temperature ${\theta }_{int,i}$, J/(kgK).

Omitting, for simplicity, the variation of the values of density and specific heat of air as a function of temperature, and relating the airflow to one hour, Equation (4) takes the following form [30]:

$$H_{V,i}=0.34\dot{·V_i}.$$

(5)

Determination of the volume flow rate of ventilation air depends on whether or not there is a ventilation system in the room. In the absence of a ventilation system, it is assumed that the air supplying the room is characterized by the parameters of outdoor air. The larger of the two values should be taken as the value of the ventilation air flow rate:

• value of infiltration airflow ${\dot{V}}_{inf,i}$,
• minimum air flow rate required for hygienic reasons ${\dot{V}}_{min,i}$,

  $$\dot{V_i}=\max \left({\dot{V}}_{inf,i}, {\dot{V}}_{min,i}\right).$$

  (6)

The flow of air infiltrating into the heated space (i) can be calculated as follows [30]:

$${\dot{V}}_{inf,i}=2·V_i·n_{50}·e_i·{\epsilon }_i,$$

(7)

where:

V_i—the cubic capacity of the heated space (i) (calculated based on internal dimensions), m³,

n₅₀—internal air exchange rate, resulting from a pressure difference of 50 Pa between the interior and exterior of the building, taking into account the influence of air vents, h⁻¹,

e_i—coverage ratio,

ε_i—correction factor to account for the increase in wind velocity as a function of the height of the heated space above ground level.

The minimum air flow rate, required for hygienic reasons, flowing into the heated space (i) can be determined as follows [30]:

$${\dot{V}}_{min,i}=n_{min}·V_i,$$

(8)

where:

n_min—minimum air exchange rate per hour, h⁻¹.

In the case of the presence of a ventilation system, the ventilation airflow of the heated zone (i) is calculated as follows [30]:

$$\dot{V_i}={\dot{V}}_{inf,i}+{\dot{V}}_{su,i}·f_{V,i}+{\dot{V}}_{mech,inf,i},$$

(9)

where:

${\dot{V}}_{su,i}$—airflow supplied to the heated space, m³/s,

$f_{V,i}$—temperature reduction factor,

${\dot{V}}_{mech,inf,i}$—excess airflow removed from the heated space, m³/s.

4. Economic Analysis

The economic analysis presented here is highly practical. The data were analyzed in a format suitable for individual investors (households) using a discrete form but in multidimensional aspects. The presented economic analysis serves to evaluate the economic performance of the recuperation system installed in the building, to find economically optimal heat transfer coefficients for particular barrier insulation, and to identify and discuss the risks of each optimal solution in sensitivity analysis.

For each of the 2512 simulations performed, we calculated the total cost of the insulation investment based on the prices of insulation materials.

Due to the complexity of the problem, our results were divided into four categories depending on ACPH and ventilation intensity, as shown in

Table 3. Categories (cat) of simulation results.

	ACPH = 1	ACPH = 4
Ventilation = 210 m3/h	I	II
Ventilation = 140 m3/h	III	IV

.

Two energy price values were assigned to each category: a low (effective) price, $P_{L }$ = 0.08 EUR/kWh (such a price is attainable in Poland for a condensing gas boiler (CGB) and heat pump (HP), April 2024), and a high (effective) price, $P_{H }$ = 0.20 EUR/kWh (for direct electric heating, April 2024). By effective price, we mean the price per kWh adjusted by the proper efficiency factor (92% for CGBs and 346% for HPs). These prices and factors were obtained from Industry Agreement for Energy Efficiency [33], an environmental conservation organization in Poland, and they include all taxes and related fees (e.g., distribution fees). These prices were used to calculate the monetary value of final energy saved as a result of investing in additional insulation (compared to the insulation with the highest heat transfer coefficients in a given category but not higher than the maximum values required by law) for each category. We used final energy, as it is the most relevant for end users.

To evaluate the economic performance of the insulation investment, we used the net present value (NPV) measure, calculated as in Equation (10):

$${NPV\_ins}_{j,cat}={PVA\_ins}_{j,cat}\left(\Delta EnVal\right)-\Delta {C\_ins}_{j,cat},$$

(10)

where:

${PVA\_ins}_j\left(\Delta EnVal\right)$—the current monetary value (growing annuity) of the difference between the value of the building’s highest final energy demand (also lowest investment cost) and the value of the final energy demand for a given category, cat, and simulation, j. This difference represents monetary gains due to energy savings during the insulation investment’s life. We used an interest rate of 5%, an energy price growth of 3.9% (the average geometric growth rate in the EU for 2008–2023), and a period of 30 years.

$\Delta {C\_ins}_{j,cat}$—the difference between the monetary investment cost in insulation (of external walls, floors, and ceilings) for a building in a given simulation and category and the corresponding insulation cost for the lowest investment (also a building with the highest energy demand).

The NPV for the HRV system was calculated according to Equation (11):

$${NPV\_hrv}_{j,cat}={PVA\_crv}_{j,cat}\left(\Delta EnVal\right)-\Delta {Chrv}_{cat},$$

(11)

where:

${PVA\_hrv}_j\left(\Delta EnVal\right)$—the current monetary value (growing annuity) of the difference between the value of energy demand for a building with an HRV system and the value of the final energy demand for a building without HRV, in a given category, cat, and simulation, j, for the building with optimal insulation thickness. This difference represents monetary gains due to final energy savings during the investment life of the HRV. We used an interest rate of 5%, an energy price growth of 3.9%, and a period of 15 years.

$\Delta {C\_hrv}_{cat}$—the difference between the monetary investment cost in an HRV system (i.e., EUR 3409) and the alternative cost of investing in a natural ventilation system (i.e., EUR 1136), increased by the present value of the growing annuity of the monetary value of energy used by the HRV for the building with optimal insulation thickness in each category. The same maintenance costs were assumed for the HRV and natural ventilation.

5. Results and Discussion

Calculating the heating demand of a building involves several steps to assess various factors that influence the amount of heat needed to maintain comfortable indoor temperatures. The effect of insulation thickness and, consequently, the overall heat transfer coefficient of the exterior walls, on the percentage of heat loss to the environment through each building envelope is shown below. In Figure 2a, it refers to an insulation thickness of 0.15 m, and in Figure 2b to an insulation thickness of 0.25 m. As can be seen, the greater thickness of insulation had a 9% reduction in thermal losses through the exterior walls. These losses, in turn, increased mainly through windows, and to a lesser extent through the ceiling.

Figure 3 presents the annual thermal energy balance for the IV category of simulation results (according to Table 3), where V = 140 m³/h and ACPH = 4. The balance included heat gains and heat losses through various building partitions, such as internal (walls, ceilings, windows, and doors) and external (walls, roofs, windows, and doors) partitions, heat energy losses through ground-adjacent partitions, heat energy losses caused by ventilation air, heat gains from solar radiation, and internal heat gains. The result was the total annual heating energy demand, which for this case was 33.98 GJ (9439 kWh). For comparison, with natural ventilation for the same building, the annual heating energy demand was 12,081 kWh. The largest contributions to the energy balance were heat gains from solar radiation, amounting to 46.42 GJ (73.7% of total heat gains), heat losses through external partitions at 37.67 GJ (52.7% of total heat losses), and heat losses from ventilation air at 23.33 GJ (32.6% of total heat losses).

Table 4. Annual and monthly energy balance.

Month	Average External Temperature	Heat Energy Losses Through External Partitions	Heat Energy Losses Through Internal Partitions	Heat Energy Losses Through Ground-Adjacent Partitions	Heat Energy Losses Caused by Ventilation Air	Heat Gains from Solar Radiation	Internal Heat Gains	Total Heating Energy Demand
	Tem, m	QD	Qiw	Qg	Qve	Qsol	Qint	QH, nd
	°C	GJ	GJ	GJ	GJ	GJ	GJ	GJ
January	−1.0	5.66	0.94	0.47	3.28	1.88	1.41	7.09
February	−1.0	5.11	0.85	0.44	3.28	1.88	1.27	6.56
March	3.3	4.52	0.75	0.47	2.66	4.01	1.41	3.37
April	7.6	3.26	0.55	0.41	2.03	4.79	1.36	1.33
May	13.5	1.80	0.31	0.36	1.17	6.26	1.41	0.15
June	16.6	0.95	0.17	0.29	0.72	6.48	1.36	0.03
July	17.5	0.74	0.13	0.25	0.59	6.28	1.41	0.01
August	17.9	0.63	0.11	0.23	0.54	5.70	1.41	0.01
September	12.9	1.90	0.32	0.24	1.26	3.90	1.36	0.38
October	6.6	3.64	0.61	0.30	2.18	2.92	1.41	2.70
November	3.8	4.24	0.71	0.35	2.58	1.33	1.36	5.21
December	0.7	5.21	0.87	0.42	3.03	1.00	1.41	7.14
Season	8.3	37.67	6.33	4.22	23.33	46.42	16.58	33.98

provides a detailed energy balance, not only on an annual basis but also broken down by individual months. The largest heat gains from solar radiation occurred during the summer months, which was associated with the highest solar radiation in these climatic conditions, while the smallest gains were observed in the winter months. During the winter period, the lowest outdoor air temperatures in Poland led to the highest heat losses through external partitions during these months.

Figure 4 illustrates the effect of using the HRV system on the heat demand values for the analyzed building, for the case of V = 210 m³/h and ACPH = 1 (cat I, part A, Table 3). Overall, across all the specifications for different values of ACPH, air volume, and different heat transfer coefficients, the average energy savings caused by installing the HRV system were equal to 2640 kWh per year.

For each of the 314 case simulations, the energy savings needed to heat the building by using the HRV system were between 29% and 35%, with an average of 32.6%. Annual heat demand was in the range of 6300–7700 kWh for the HRV system. On the other hand, without the HRV system (natural ventilation), this demand was 9600–11,200 kWh. The values depend on the thickness of the insulation used (transmission coefficients). The higher the value of the heat transfer coefficient, the higher the value of the heat demand.

Table 5. Optimal results of overall heat transfer coefficients (U) and NPV for energy prices of 0.2 EUR/kWh (part A) and 0.08 EUR/kWh (part B).

Cat	${\mathit{U}}_{\mathit{e}\mathit{w}}$	${\mathit{U}}_{\mathit{f}\mathit{l}}$	${\mathit{U}}_{\mathit{c}\mathit{e}}$	${\mathit{N}\mathit{P}\mathit{V}}_{\mathit{i}\mathit{n}\mathit{s}}$	${\mathit{R}\mathit{O}\mathit{I}}_{\mathit{i}\mathit{n}\mathit{s}}$	${\mathit{N}\mathit{P}\mathit{V}}_{\mathit{h}\mathit{r}\mathit{v}}$	${\mathit{R}\mathit{O}\mathit{I}}_{\mathit{h}\mathit{r}\mathit{v}}$	${\mathit{B}\mathit{E}\mathit{P}\mathit{r}}_{\mathit{h}\mathit{r}\mathit{v}}$
(A)
I	0.103	0.109	0.09	8500	114%	5881	186%	N/A
II	0.103	0.109	0.09	8570	115%	5221	165%	N/A
III	0.103	0.109	0.09	7979	107%	2464	78%	N/A
IV	0.103	0.109	0.09	8084	108%	1828	58%	N/A
(B)
I	0.116	0.128	0.12	1158	19%	830	32%	N/A
II	0.116	0.120	0.12	1176	19%	565	22%	N/A
III	0.116	0.128	0.12	1035	17%	−452	−17%	0.10
IV	0.116	0.128	0.12	1059	18%	−701	−27%	0.12

presents the optimal values of the overall heat transfer coefficients for a given category from Table 3. The results presented in Table 5 highlight several important conclusions. Firstly, comparing values in panels A and B, it can be concluded that energy price was the main determinant of HRV and insulation economic profitability. For higher energy prices, the NPV of investing in additional insulation or an HRV system was higher, and vice versa for lower prices. However, to exploit lower energy prices during the building’s lifetime, additional investment is needed, either in CGBs or HPs, rather than direct electric heating (e.g., underfloor electric mats). The economic profitability of these investments was not considered in this paper; however, it will be the subject of our analysis in forthcoming research.

Secondly, for the same price level, higher ventilation intensity (210 m³/h vs. 140 m³/h) and airtightness of the building mean that the HRV investment is more profitable. It means that for buildings with a smaller volume or fewer inhabitants, the HRV system does not provide economic benefits in the case of moderate and low energy prices (see Figure 5). For a building that needs more intensive air exchange, the economic benefits are positive and even higher with better airtightness. For example, for a building with high energy prices (panel A) and with 210 m³/h of air exchange, airtightness increases the economic benefit by 660 EUR. If an investment cost that increases the airtightness from 4 ACPH to 1 ACPH is less than 660 EUR, it becomes a profitable investment. For buildings with lower energy prices (panel B) and low ventilation intensity, the return on investment (ROI, equal to NPV divided by HRV system cost) is negative. Only with significantly higher energy prices of 0.1 EUR/kWh (better airtightness) or 0.12 EUR/kWh (worse airtightness) would the return on investment increase to 5%.

The results also indicate that for high energy prices, the optimal overall heat transfer coefficients suggested the following insulation thicknesses: 0.3 m for external walls, 0.15 m for floors, and −0.4 m for ceilings. In the case of lower energy prices, these values were lower and equal to 0.26 m for walls, 0.1 m for floors, and 0.3 m for ceilings. These optimal values can be compared with lower insulation thicknesses, for example, for 0.15 m for external walls, 0.15 m for floors, and 0.2 m for ceilings, the NPV would drop from EUR 8500 to 635 due to the increase of energy demand equal to 2170 kWh per year.

The risks associated with the investments considered in this paper are related to energy price variability and the timing of the investment. While price levels are regulated by the state, they also depend on the costs reported by producers. Because decisions about insulation thickness are dependent on energy prices for the selected heating method, which are not known in the long term, it is safer for investors to assume adverse changes in the energy price market and slightly overinvest in insulation. This is the easiest way to hedge against the risk of energy price variability.

From another perspective, even if energy prices are expected to be low (for example, due to an increasing share of renewable energy sources with low variable energy production costs), it can make sense to overinvest in insulation. Selecting the same insulation thickness for a low energy price environment (row 6, Table 5) as you would for a high energy price environment with a leaky building and high ventilation needs (row 2, Table 5) would result in an NPV decrease of only EUR 177. This value is negligible compared to the total cost of insulating a new building.

Investment risk timing relates to the price variability of insulation materials. For example, a 10% decrease in the price of insulation materials would result in an 8.7% increase in the NPV value (for the conditions described in row 2 in Table 4). Unfortunately, this risk is very difficult to hedge. It would require the investor to be able to buy materials when their prices are low and bear the cost of storing them until required, which may be impractical.

6. Conclusions

This study analyzed the economic and energy performance of new detached residential buildings in Poland, focusing on the combined impact of wall, roof, and floor insulation levels and the use of a heat recovery ventilation (HRV) system. Over 2500 simulations were performed to investigate how varying envelope parameters, ventilation intensities, and heating energy prices influenced energy demand and investment profitability.

Key findings included the following:

• Energy performance: The use of an HRV system reduced the building’s annual heat demand by up to 2600 kWh, depending on the air exchange rate and insulation level. Optimal heat transfer coefficients were found to range between 0.103 and 0.116 W/m²K (walls), 0.109 and 0.128 W/m²K (floors), and 0.090 and 0.120 W/m²K (ceilings), adjusted to different heating energy prices.
• Economic outcomes: The net present value (NPV) of investing in HRV ranged from EUR 500 to 5900, and from EUR 1000 to 8600 for insulation, depending on ventilation rates and energy prices. The return on investment (ROI) for HRV exceeded 58% in high energy price scenarios and remained positive in most cases. ROI for insulation exceeded 17% even with low energy costs and surpassed 100% when electricity was used for heating.
• Decision-making insight: The results showed that in most scenarios, investment in insulation and HRV was financially beneficial. However, in buildings with very low ventilation intensity, high insulation levels, and access to cheap energy (e.g., heat pumps), HRV investment may not be cost-effective.

This study directly addressed the two main research questions posed in the introduction. Firstly, it demonstrated that the installation of a heat recovery ventilation (HRV) system can provide measurable economic and energy-saving benefits, particularly in buildings with moderate to high ventilation intensity and in scenarios where the cost of heating energy is average or high. Secondly, the simulations showed that the optimal level of insulation varied depending on the energy source and its cost. Nevertheless, even in cases where insulation levels exceeded the technically optimal values, the financial risk of overinvestment remained low due to the consistently high return on investment (ROI), especially in high energy price environments.

Looking ahead, future research will focus on analyzing the synergies between HRV systems and other sustainable technologies, such as heat pumps or photovoltaic panels, particularly in the context of energy-efficient building design in Central Europe. Additionally, further studies should investigate how fluctuations in energy prices and construction material costs influence long-term economic performance.