1. Introduction
In Kazakhstan, the residential building sector consumes about 14% of produced electricity and about 25% of thermal energy [
1]. In the southern Almaty region, where the population has increased over the past 15 years, from 1.15 to 1.85 million [
2], there is a shortage of energy to ensure the functioning of buildings. Due to the continued expansion of the residential building sector, both energy demand for buildings and air pollution have increased, and energy consumption in buildings must be reduced by increasing their energy efficiency. This has been provided by a government program [
3], and new energy performance requirements for buildings were approved in 2019 [
4]. However, these requirements are not justified by calculations; rather, the requirements were implemented only in comparison to buildings that meet the lowest requirements of functionality and hygiene. At the present time, during a period of stabilization of Kazakhstan’s economy, it has become relevant to establish an economically reasonable level of building thermal insulation.
Currently, government-regulated thermal energy prices in the Almaty region differ significantly from energy prices in the global market. Maintaining low energy prices for building heating is linked to the state’s desire to raise the living standards of the country’s population, but it hinders the construction of energy-efficient buildings. The thermal insulation level of partitions in residential buildings currently under construction is significantly lower than the optimal level that is applied in EU countries with a similar climate, in which there is a free energy market. The duration of the heating season, in which heating starts when the three-day average outdoor temperature falls below +10 °C, also reduces the quality of the indoor microclimate.
The objective of this work is to find out the impact of increasing the thermal insulation of partitions on the total energy consumption and total costs of residential buildings over a period of 30 years and to provide recommendations for the thermal insulation of new construction residential buildings in the Almaty region. In most investigations in this area, building thermal insulation is optimized using global energy market set prices for energy, construction work and building materials. In Kazakhstan, energy prices are artificially reduced and the prices of construction works and materials, especially innovative ones, are left to the market regulation. The study of this situation will provide new results and will help to clarify the impact of artificial regulation of energy prices on the energy consumption of buildings in the long perspective.
A number of methodologies for optimizing the energy performance of buildings have been developed, but their essence is similar—investments in energy efficiency improvement measures for buildings must be based on their payback over a set period of time, ensuring the functionality and interior comfort of the buildings. The general steps involved in the cost-optimal methodology are presented in the scientific literature. Previous research [
5] demonstrates that building age and investment costs have an important impact on the cost-optimal results; in particular, it is essential that the choice of the thermal insulation, its thickness and conductivity, and the thermal properties of windows be considered to reach a compromise between performance and investment costs.
The simplest method for determination of optimal thermal insulation of walls is presented in reference [
6]. In this study, the environmental impact on optimum insulation thickness of external walls was investigated. Optimal thermal insulation was determined for the minimal annual total cost, which is a sum of insulation cost and used energy cost. One financial analysis method is the Simple Payback Period. This method is based on the time required to repay the initial capital investment with the operating savings attributed to that investment. The main drawback of this simple analysis is that it does not take into account the change in the value of money, which is an important financial consideration [
7].
Economic and environmental benefits of thermal insulation of external walls were analyzed in reference [
8]. Optimal thickness of different thermal insulation materials was determined, using an approach for cost-optimal calculation in which total cost was the sum of insulation and energy costs. The optimum thermal insulation thickness was chosen to minimize the total cost [
9].
In a previous study, the optimization of building thermal insulation has been expanded to the optimization of building energy performance [
10]. This study presents a methodology and a new tool with the goal of assisting in the choice of economically efficient net zero energy buildings (NZEB) solutions for residential building in any climate, for different energy resources, and the local economic conditions. Lowest Initial Cost (LIC) solutions are defined for the energy end uses with relevance to space heating and cooling, water heating (domestic hot water), lighting, cooking, refrigeration, and other appliances.
Many researchers have used reference buildings for optimization of thermal insulation and energy consumption [
11]. The considered building was designed in compliance with Italian regulations regarding the envelope insulation level and characterized by common construction techniques. Since terraced housing is currently very widespread in Southern Europe, the analysis was applied to this building type by addressing simple corrective solutions, such as thick thermal insulation, use of low-emissivity glazing and window shadings, high level of air tightness and ventilation with heat recovery, solar collectors for domestic hot water (DHW), and heat pumps for space heating. The multi-story reference NZEB model with 10 renewable energy systems has been used to examine the cost-optimal combination of energy efficiency and renewable energy generation [
12]. For investigation of optimal energy retrofit strategies, as base case for cost/benefit analysis, the sampled school buildings of different educational level, age of construction and typological design were divided in homogeneous clusters, each of which was represented by a reference building [
13].
The optimal thickness of thermal insulation is determined by the following factors: type of the building, its use, size and structure, type of the insulated component (wall, floor, etc.), climatic characteristics, type of the thermal insulation applied, insulation costs: materials and labour, type and manner of energy supply, fuel and operating prices [
14]. The change in the value of money has a significant impact on the optimization process. To assess the diversity of the building materials market, economic costs of each intervention were estimated by averaging the prices presented by different companies for the same intervention [
15].
The optimal energy efficiency level also depends on annual operation and maintenance cost which is the sum of the energy costs (for each energy carrier), the operation costs (securities, services etc.), the maintenance cost (inspection, cleaning, overhaul, consumables) and the costs associated with periodic replacement of equipment [
16].
Energy efficiency optimization results vary between different climate zones across European countries. In colder climates, thermal insulation and building air tightness appear much more important as thermal improvements are strongly dependent on heating loads. In warmer, sunny locations, Solar irradiance could be evaluated as Solar heat gains and reduce the heating loads [
17]. Given the significant climatic variations that exist in different parts of Turkey, 16 cities from four climate zones of Turkey were selected for analysis of optimal thermal insulation thickness. The results showed variation of optimum thermal insulation thicknesses between 2 and 17 cm [
18]. However, increasing the thickness of the thermal insulation layer does not always give positive results of building energy efficiency. The energetic and economic influence of external thermal insulation is evaluated for a case study for various cities in Italy, and the results demonstrated the need to avoid excessive thermal insulation of buildings to obtain the highest energy savings [
19]. The provided results highlight the different challenges and opportunities presented by the large variation in thermal conditions and solar availability across European climates.
The building energy efficiency design and evaluation process is dependent on life cycle assessment methodologies [
20]. The authors expand the traditional understanding that constructions are mostly concerned with cost, time, and quality. To these criteria, sustainable construction adds the consideration of the building’s life cycle because the minimization and reduction of the impacts on the environment depends on the performance of the building during all its phases. Following these considerations, authors of this article presents an overview of life cycle methodologies: life cycle assessment (LCA), life cycle energy analysis (LCEA), life cycle ZEB (LC-ZEB), and life cycle costs (LCCA). Life cycle cost analysis is an economic method of project evaluation in which all costs arising from owning, operating, maintaining and disposing of a project are considered to be potentially important to that decision [
21]. The main goal of the LCCA in construction sector is to define the cost-effective energy efficiency measures and renewable energy technologies for energy efficient buildings [
22]. The LCCA conducted for multi-family Net ZEB helped answer the questions: how far should we go with energy efficiency measures and when should we start to apply renewable energy technologies?
A multi-objective analysis is often used to obtain optimal energy efficiency of buildings, through the analyses of combinations of various structural solutions, energy systems, and building materials [
23]. The optimization methodology for NZEB design to enhance its energetic and economic performance includes four steps: building simulation, optimization process, multi-objective analyses and testing solution’s robustness [
24].
The main goal of all methods is to determine the cost-optimal solution from different alternatives. These alternatives are comparable only with the same economic assumptions, study period, and service date. According to [
22], cost-optimal solutions can be estimated in present-value and annual-value terms. The calculation method requires that all future costs be discounted to their present-value equivalent.
The first data on the optimal management of Kazakhstan’s energy resources were provided in a study about the need to decrease greenhouse gas investment [
25]. This study provides an analysis of the recent situation and identifies the reasons for energy inefficiencies: outdated heat generating companies, low energy prices, and low incentives for efficient energy use.
The latest data on the energy performance of buildings in Kazakhstan are provided in the Law of Republic of Kazakhstan on Energy Saving and Energy Efficiency [
26]. It is stated that efficient use of energy resources must be compatible with technical possibilities and economic justification. The law provides support for the development of methodological and normative measures that increase the energy performance of buildings.
3. Results and Discussion
The analysis of total costs of pitched insulated roofs showed that the optimal insulation thickness for the use of district and gas heating is 15 cm. This is, on average, 0.29 W/(m
2·K) (
Figure 2). A more detailed analysis of the total costs showed that in the case of district heating use, the total costs increase slightly when the thickness of the thermal insulation layer reaches up to 20 cm, and in the case of gas, this difference is larger. In the case of a longer heating season, the minimum values of total costs approach a thinner insulation layer. Summarizing the calculation results, under the given conditions and future energy use, the optimal value of the heat transfer coefficient of the insulated pitched roof proposed is 0.25 W/m
2·K.
The minimum total costs of flat roofs are obtained by a thickness of 15 cm thermal insulation, but the optimal heat transfer coefficient of this structure is less than that of pitched insulated roofs, because there is no influence of the timber that crosses the thermal insulation layer (
Figure 3). The choice of lower thermal conductivity materials would make it economically optimal to achieve the heat transfer coefficient of the flat roofs not more than 0.22 W/m
2·K.
A similar situation was found in the analysis of the insulation of ceilings to a ventilated shelter (
Figure 4). In the case of a wooden ceilings, the lowest total costs correspond to 15 cm insulation thickness, but in the case of a reinforced concrete ceiling, these were even greater than 20 cm in thickness when the heat transfer coefficient is less than 0.20 W/m
2·K. Therefore, it is recommended that this value of the transfer coefficient be considered as the optimal value of the heat transfer coefficient of the ceilings to ventilated shelters. More efficient thermal insulation materials should be used in wooden frame ceilings or part of the insulation layer should be installed on top of this ceiling to minimize the initial investment (excluding the price of the wooden framework).
The results of the total costs calculation of the walls show that most of the analyzed cases fall within the area of the lowest total costs corresponding to 15 cm thick insulation (
Figure 5). The lowest costs reflect a 10 cm insulation area with cheaper gas heating and longer heating season. Due to the variety of wall construction and insulation, the heat transfer coefficients of the walls corresponding to the minimum total cost are from 0.21 to 0.29 W/m
2·K. After summing the results, 0.25 W/m
2·K is the recommended optimal wall heat transfer coefficient.
Floor calculations clearly show the lowest total cost for the 10 cm thick floor insulation, but in the case of more expensive heating networks and a shorter heating season, the total cost increases slightly with a 15 cm thick thermal insulation layer (
Figure 6). This corresponds to a range from 0.22 to 0.30 W/m
2·K of the floor to ground heat transfer coefficient. Considering that increasing the floor insulation thickness is one of the cheapest ways to install thermal insulation, the value of the heat transfer coefficient depends on the size of the building, and that increased floor on the ground insulation further reduces the energy consumption of the building when installing floor heating, an optimal floor for the ground heat transfer coefficient could be 0.23 W/m
2·K.
It is more difficult to optimize windows than other building elements as windows perform other functions in addition to saving thermal energy (
Figure 7).
However, in terms of heat loss estimation, less energy-saving windows are currently optimal due to the low energy price, although windows of 60 mm thickness with double-glazed insulated glass units and one low emissivity glass pane with a heat transfer coefficient of 1.6 W/m
2·K are eligible for indoor microclimate conditions. The total cost is only slightly increased by using a window frame with better thermal properties when the value of the heat transfer coefficient of the window decreases up to 1.4 W/m
2·K. The use of triple glazing is not optimal under the investigated conditions, not only due to rising total costs, but also due to the decreasing amount of solar energy entering the building through the windows. A window with a triple-glazed unit, on average, has lower solar heat gains than it saves thermal energy compared to a double-glazed insulated glass unit (
Table 7). Therefore, it is suggested to set the optimal heat transfer coefficient of the windows at 1.4 W/m
2·K, which can be achieved using a frame of better thermal performance and a double-glazed glass unit.
The analysis of the dependence of total costs and the scenarios of changes in energy prices and the value of money was also performed. For all partitions, the trends of change in total cost differ slightly, it was found that the total costs are 7–10% higher at a lower actual discount rate (r = 2). This means that with more intensive changes in energy prices and value for money, the optimal level of insulation would be even higher. This analysis has shown that in order to significantly change the situation of increasing the energy efficiency of residential buildings in the region, the artificial regulation of low thermal energy prices needs to be stopped as soon as possible. Therefore, it is recommended for the management of the construction sector of the region to set the heating energy prices as close as possible to the market conditions, and allocate the additional funds to subsidize the implementation of energy efficiency measures in new residential buildings. The results of the analysis show that a gradual increase in thermal energy prices will not produce tangible results of energy efficiency in the long perspective.
An additional analysis of subsidies for energy efficiency improvement measures has shown that the elimination of artificial price reductions alone is not enough to achieve long-term energy efficiency goals [
35]. In many countries, subsidies for innovative energy performance measures, in particular those using renewable energy, are used to increase the energy efficiency of a building [
36]. Other researchers suggest that most appropriate measures are demonstration projects and soft loans for energy efficiency measures [
37]. However, other studies have found that subsidizing energy efficiency measures needs to be well thought out and systematically addressed, as otherwise most subsidies could go to corporate profits [
38] or reductions in energy and construction taxes and would have a negative impact on public budgets [
39].
The recommended minimum optimal values for the heat transfer coefficient of the building envelope elements for the Almaty region of Kazakhstan are given in
Table 7, line 1.
In 2017, cost-optimal analysis according to the methodology used in this study, applying the same scenarios of energy price change and monetary value change, was performed in Lithuania using a district network price of 0.06 EUR/kWh and gas heating price of 0.04 EUR/kWh. These were about four times higher than the prices of Almaty in 2019. The calculated optimal values of heat transfer coefficients are presented in
Table 6 (line 2). Comparative analysis showed that the optimal level of thermal insulation of building partitions in Lithuania is about 30% higher than that in Almaty. This difference is not large because a longer calculation period was chosen, and the prices of thermal insulation materials and construction work in Almaty are also lower.
Using recommended values of the heat transfer coefficients of the partitions, the energy efficiency characteristics of the reference building were calculated; results are presented in
Table 8.
The heat losses through the external envelope of the reference building are 118.7 kWh/m
2·y, ventilation heat losses are 23.0 kWh/m
2·y, and heat gains are 52.7 kWh/m
2·y. The approximate heating energy consumption of this reference building is 90 kWh/m
2·y. As an example for comparison purposes, the average heating energy consumption for 1–2 family buildings in Germany in 2017 was 122 kWh/m
2·y [
40]. The significant part of this difference is due to higher solar heat gains in Almaty.