1. Introduction
The residential and services sector accounts for 40% of Sweden’s energy use [
1] and ~10% of greenhouse gas (GHG) emissions [
2]. Of the share of energy use, space heating and domestic hot water in multifamily buildings were responsible for roughly 20% (26.6 TWh) in 2016, and district heating (DH) is the predominant energy carrier with 90% of Sweden’s multifamily buildings connected to a DH network [
3,
4]. As in many European countries, Sweden’s building stock increased rapidly between 1950 and 1975, after the Second World War and before the oil crisis [
5,
6]. During what is now called ‘the record years’, the Swedish government initiated the construction of a million dwellings between 1965 and 1975, now called the Million Homes Program [
7]. As Meijer et al. [
5] emphasize, these buildings have a common characteristic of generally poor insulation and a relatively high need for renovation, and estimations indicate that 75% of these building are in need of renovation [
8,
9].
The national targets of Sweden, originating from the targets of the European Council [
10], state that by 2020 GHG emissions shall be decreased by 40% (relative to 1990) and no net emissions shall occur by 2045. The energy intensity shall decrease by 20% by 2020 (relative to 2008 and expressed as less input energy per unit gross domestic product), and by 50% by 2030 (relative to 2005). By 2020, the share of renewable energy shall be 50% of the total energy use, and by 2040 electricity production shall be from 100% renewable resources [
11,
12]. The Swedish government [
11] also states that fossil fuel is not to be used for heating purposes by 2020. Moreover, substantial energy efficiency measures ought to be carried out within the residential and services sector. The sector has been identified as having high potential for energy savings with sufficient technical solutions, including, e.g., renovation as well as energy storage and scheduling [
13,
14,
15,
16,
17]. Werner [
4] also highlights that savings has been made in building stock, explained by reduced heat demand in buildings of the Million Homes Program, lower demands in newer buildings and milder climate. However, as Svenfelt et al. [
13] conclude, knowledge, incentives, and policy work need to address the actors with direct influence in the field.
The Swedish government has expressed that DH utilizing the technique of combined heat and power (CHP) plants provides the opportunity to make use of energy that would otherwise be wasted [
11,
12]. The use of DH has steadily increased over the past 50 years, from 13 to 60 TWh, mainly in the residential and services sector, and by 2018 ~10% of Sweden’s electricity production capacity comes from CHP technique [
3]. Studies emphasize the role of the CHP technique in the energy transition from fossil fuel to renewable resources [
18,
19,
20,
21]. However, Werner [
22] highlights a low utilization and low awareness of the benefits on a global level. Furthermore, considering the work of reducing GHG emissions, the potential electricity output from European CHP plants could be more than doubled [
23]. Studies also points to the unclear role of a DHC system in a future energy system, where questions regarding surplus electricity from intermittent sources and future access to conventional fuel as waste and biomass are unexplored [
24]. Stankeviciute [
23] points to increased competition for biomass with the transport sector as a limitation for the CHP potential. Furthermore, studies highlights potential issues where CHP plants are unprofitable in a Nordic market and a prevailing trend of heat-only boilers replacing CHP plants in DH production [
25].
According to the Swedish Energy Agency [
26], energy use within the residential and services sector will increase slightly during the coming years, mostly caused by increased use of DH due to colder weather than in previous years. A marginal increase in energy use is expected from newly constructed buildings. The prognosis until 2050 points to a decreased use of DH, with the main reasons being energy efficiency measures in the existing building stock and heat pumps starting to compete with DH in multifamily buildings [
27], the latter showing an increased market share for heat supply over the past two decades [
4].
The aim of this paper is to analyze the impact of renovation on a multifamily building stock in a regional energy system utilizing a CHP technique. The renovation measures are related to the building envelope, ventilation, and substitution from DH to a ground source heat pump (GSHP). The key performance indicators are the specific energy use and energy performance of the renovated building, and, regarding the district heating and cooling (DHC) system, primary energy savings, peak power demand, electricity production and demand, as well as local and global GHG emissions.
The two parts of this study—the renovation of multifamily buildings, and effects on DHC systems due to changes in demand—are studied in several previous studies. However, most studies treat the parts separately and there are few studies that combine both parts from a wider systems perspective, meaning analyzing the renovation’s impact on a DHC system, and even fewer studies that analyze the subsequently climate effects in terms of local and global GHG emissions. A common approach in order to analyze the issues is to utilize the general idea of a systems perspective approach inspired by Churchman [
28], who introduced the subject, and further promoted by, e.g., Bijker et al. [
29] and Olsson and Sjöstedt [
30]. A solution or change in a large system may have a great impact on its surroundings, and it is crucial to understand the system’s objective, performance, and environment in order to minimize the risk of suboptimization [
31].
Regarding studies with a wider systems perspective, Ramírez-Villegas et al. [
32] examined how different renovation strategies impact the energy rating of the building and local GHG emissions from the DH system. Moreover, Lidberg et al. [
33] concluded that renovating a building envelope decreases GHG emissions more than measures regarding ventilation, due to the increased electricity demand of the latter. It also stresses that all renovation measures decrease the DH demand, resulting in a loss of electricity production at CHP plants. The possible issues caused by decreasing heat demand and increasing electricity demand, i.e., if DH is replaced by heat pumps, are seen in other Nordic countries [
34,
35,
36,
37,
38,
39]. One concern is a possible suboptimization of the energy system in terms of emissions, where heat normally supplied by renewable DH would be substituted by heat pumps using nonrenewable electricity. However, this concern is only applicable to DH systems using a CHP technique, as mentioned by Le Truong et al. [
40], who also conclude that primary energy savings are higher for the renovation of buildings connected to DH systems using heat-only boilers, as there are no losses in electricity production.
A related study carried out by Difs et al. [
41] concluded that local electricity savings in the energy system should be prioritized over a reduction in DH use. This is due to both economics and the assumption of a deregulated European electricity market leading to global GHG emissions outweighing the saving in local GHG emissions. Djuric Ilic et al. [
42] studied opportunities for a reduction of global GHG emissions by introducing biofuel production in a DH system. The study concluded that the potential for a reduction of global GHG emissions highly depends on whether the biofuel is seen as a limited or unlimited resource and the alternative use of biofuel. Moreover, as Olsson et al. [
43] highlight, when concluding that methodological choices affect the results when estimating GHG emissions from DH systems, the local conditions should be considered when assessing DH systems.
The main contribution of this work regards the renovation packages including common measures along with a substitution from DH to GSHP, and the resulting energy performance on a building level and resulting impact of local and global emissions. Moreover, the analyzed impact of peak power needed in the DHC system can contribute to the scientific community when analyzing large scale renovation. The study is also well established in the non-academia in the region of the study, as the research include and involve energy and housing companies.
3. The Scenario Study
The study is performed as a scenario analysis and the location is Linköping, Sweden—a city with 160,000 residents located 200 km southwest from Stockholm. In addition to the national sustainability goals, the municipality of Linköping is aiming at becoming carbon neutral by 2025 [
64]. In this work, publicly utility companies, such as the two companies involved in this study, are important actors. Linköping, like many other cities, is facing the challenge of an aging building stock in need of renovation, with approximately 70% of Linköping’s total stock of multifamily buildings having been built prior to the 1980s [
6].
The scenario study is illustrated in
Figure 2. A larger energy system is represented by a DHC system, operated by Tekniska verken AB, and a subsystem consisting of a multifamily building stock, managed by Linköping’s largest housing company Stångåstaden AB. The renovation measures included in the analysis was implemented in the reference building, presented in
Section 3.1, when it was renovated in 2014 and were decided based on common praxis of the building owner. Several studies have studied similar renovation approaches and identified great potential for reducing heat demand in building by adding thermal insulation [
65,
66,
67,
68] and ventilation measures [
66,
67,
69,
70]. Therefore, the scenarios constitutes of substitution from DH to GSHP, as this is a potential future competitive situation [
27], and measures on building envelope and ventilation, which are common measures regarding this type of building [
9,
71].
The energy performance of the buildings will be analyzed on a general level whilst a more detailed analysis will be conducted on the larger DHC system in terms of primary energy savings, electricity demand and production, as well as local and global GHG emissions.
The DHC system in Linköping is the third largest high-temperature system in Sweden. The majority of the heat, cooling, and electricity production comes from CHP plants mainly using household waste, biofuels, coal and oil as fuel. The demand during a normal year amount to 1700 GWh heat, 60 GWh cooling, and 400 GWh electricity. Moreover, of the total DH demand, 40% derives from multifamily buildings [
72].
Stångåstaden AB has approximately 20,000 rental multifamily buildings, which is roughly 40% of the city’s stock of multifamily buildings. The majority of the buildings are located in the urban areas and utilize DH for heating purposes. The reference building used for estimating energy efficiency potential in the building stock is a five story multifamily building located in central Linköping and connected to the DH network [
71]. The building was constructed in 1961 and has a common construction for buildings from the time period of the record years and the million homes program. Moreover, the construction is a common type in Stångåstaden’s building stock, and the company manages several homogeneous areas with buildings of this type that will be renovated over the coming years.
In order to analyze the effects on the DHC system, the building energy simulation results will be scaled-up to a larger building stock. The stock is a selection of similar types of buildings in Stångåstaden’s building stock. The selection of buildings was constructed between 1961 and 1975 and consists of detached multifamily buildings with exhaust air ventilation. Moreover, the selected building stock has a mean energy performance of 155 kWh/m2 and comprises 273,500 m2, which is close to 10% of Linköping’s residential area in terms of multifamily buildings.
The studied building presents an annual energy performance of 140 kWh/m
2 in the building energy simulation, as will be seen in the reference scenario later on. It is 10% lower than the mean energy performance of the selected building stock. This is explained mainly by the good thermal properties of the building, relative to other buildings from the time period [
73]. However, it also infers that it is improbable that the results of the upscaled building stock would be an overestimation.
3.1. The Reference Building and Renovation Scenarios
The original construction can be seen in
Table 2 along with the envelope measures conducted in 2014 when the building underwent deep renovation. The renovation included insulation of the façade (100 mm) and attic (180 mm), new windows with a glazing heat transfer coefficient (
U-value) of 1.1 W/m
2·K and solar heat gain factor (
g-value) of 0.43. A balanced mechanical ventilation system with heat recovery was also part of the renovation and is included in the scenarios presented in
Table 3.
The building model used in this study has been previously validated with regard to its accuracy in prediction at both zone and building levels [
71]. The model predicted the indoor air temperature with a maximum standard deviation of 0.4 °C from measurement during winter in a reference apartment in the building. The predicted annual space heating demand had a difference from measured heat demand of 3.7% before renovation and 5.6% after the renovation.
Standard values from a Swedish setting were used as input data for the simulations [
76]. The residents in the building were assumed to use 30 kWh of electricity per square meter of apartment area for domestic purposes and 70% of this is assumed to be useful heat gains when there is a heat deficit. The residents were assumed be away from the building during office hours and to use the majority of the electricity when they were at home, see La Fleur et al. [
71]. The thermal bridges were set to “normal” in IDA ICE version 4.8. The annual space heating was simulated during normal year corrected climate data from Linköping [
77]. The simulation had a variable time step (maximum 1.5 h) with an output time step of 1 h. The desired indoor temperature was assumed to be 21 °C, in accordance with the recommendations of the Swedish National Board of Health and Welfare [
78].
The selected scenarios derive from when the reference building was renovated in 2014 and include measures on the building envelope and ventilation. A substitution of the heating solution, from DH to GSHP, is also added in this study. The scenarios are presented in
Table 3. The building and its energy use prior to the deep renovation in 2014 serve as a reference scenario (R). Scenario 1 consists of DH as the heating system along with building envelope measures. An extensive renovation with additional ventilation measures comprises scenario 2. The renovation package of scenario 2 also includes the measures carried out in 2014, and previously studied by La Fleur et al. [
71,
79]. Furthermore, scenario 3 consists of a substitution from DH to GSHP, scenario 4 adds measures on the envelope and, lastly, added ventilation measures make up scenario 5.
The ground source heat pump, introduced in scenarios 3–5, was simulated using the early state building optimization plant in IDA ICE. The maximum power of the heat pump was 60% of maximum power demand, and the maximum coefficient of performance of the heat pump is 4.
3.2. The DHC System
Figure 3 presents a description of the DHC system, with the demands of electricity, district cooling and DH. The DHC production is based on two incineration CHP plants: the Gärstad waste-based CHP plant located in the northern part of Linköping and the mixed fuel CHP plant located in the central part. The system is complemented with a third biofuel-based CHP plant in the nearby town of Mjölby, and heat-only biofuel boilers. As a backup, there are also heat-only boilers (HOBs) using oil and fat to cover peak loads.
The Gärstad CHP plant consists of three waste incineration boilers, called CHP 1–3, 4 and 5 in
Figure 3, with a flue gas condensing and steam turbine through a gas turbine heat recovery steam generator, a so-called hybrid system. CHP 1–3 have a maximum capacity of 75 MW heat, an additional 15 MW heat from flue gas condensing, and 10 MW electricity. A decision was made to expand the Gärstad waste incineration plant by adding fourth and fifth waste-fueled boilers with steam turbines (CHP 4 and 5). The fourth boiler with flue gas condensing and steam turbine max capacity is 68 MW heat, an additional 15 MW heat from flue gas condensing and 19 MW electricity. The fifth boiler with steam turbine can produce 84 MW, an additional 12 MW heat from flue gas condensing and 21 MW electricity. The steam from waste incineration in all Gärstad CHP plant’s boilers is used for heat and electricity production or only heat production. The majority of waste is organic and comes from households in the surrounding region. The technical input data may be seen in
Table 4.
The central CHP plant consists of three boilers and three steam turbines, two back-pressure turbines and one combined condensing and backpressure turbine. The first boiler is fueled with a mixture of coal, with fractions of rubber and wood. The second boiler uses heating oil. The third boiler, with flue gas condensing, is fueled with wood and fractions of plastics. The central plant can produce electricity and heat or use a direct condenser for the sole production of heat. Cooling of condensing turbine occurs with water from the nearby river Stångån. This means that heat of approximately 50 GWh/year may be wasted in a recooler in Stångån.
District cooling is produced in a district heating-driven absorption plant of 12 MW and an electricity-driven compression-cooling plant of 6 MW, and is distributed by a network in the same way as district heating in order to satisfy the cooling demand in Linköping’s urban area.
In order to calculate local and global GHG emissions, factors presented in
Table 5 are used. The locally emitted GHG is a result of the fuel use in the DHC system. Also included in this study is the globally emitted GHG caused by changes in electricity production and increase in demand.
5. Discussion
The savings in terms of supplied energy are larger within the scenarios with DH (R, 1, and 2) than within the scenarios with GSHP (3, 4, and 5), as presented in
Table 6. Measures on the building envelope display limited potential, mainly due to relatively good
U-values on the reference building. Added ventilation measures, on the other hand, contribute to a larger improvement, especially in scenario 2. A substitution from DH to GSHP (scenario 3) produces better results in terms of energy performance than the more extensive renovation scenario of scenarios 1 and 2. Moreover, scenario 3 produces good results, as the energy performance ends up close to 85 kWh/m
2, which is the highest permitted value for new construction of multifamily buildings [
82]. Scenarios 4 and 5 reduce the energy performance even further. This means that it should be considered whether the incentives for continuing with measures in scenarios 4 and 5 are high enough for the building owner. Moreover, as presented in
Table 7, scenario 3 demands the most electricity and causes the largest GHG emissions as seen in
Figure 8. Hence, this is the least desirable solution from a wider systems perspective. However, an incentive for further renovation measures, as in e.g., scenarios 4 and 5, may also be an improved indoor climate [
79,
84].
The largest reduction of peak power needed in the DH system occurs in December, as seen in
Figure 6. December is also the peak month of use according to
Figure 4, followed by January and February. However, December is not the month with the highest peak demand according to
Figure 5b, where February followed by January and December are the high use months in terms of DH demand. This is explained by December being the month with stable low temperature days along with low solar radiation, causing the latent heat stored in the building to be low, and therefore requires more supplied energy. Moreover, during January and February the solar radiation and latent heat increase, but it is also during those months that the single coldest days of the year occur, causing the peak demand in the DH system.
The results indicate reduced energy use and reduced demand for heat in the DHC system. This subsequently reduces electricity production at the CHP plants. In Sweden, DH is mainly based on nonfossil fuel, and the out-phasing should be done by 2020. This, in turn, leads to a reduction in global emissions if DH is used to a high degree. Thus, the two desires of decreasing energy use for heating purposes and decreasing GHG emissions may contradict each other. However, in this study, GHG emissions indicate a reduction on a local level, in accordance with the reduction of biofuel and coal use. It should be noted that a reduction in primary energy use of biofuel, if seen as a scarce resource, is calculated to have positive effect on GHG emissions. The biofuel may be used elsewhere and substitute fossil fuel as primary energy, as Lidberg et al. [
33] and Djuric Ilic et al. [
42] highlight. In the future, when the out-phasing of fossil fuel in the DHC systems has resulted in a fully renewable system, the reduced use of DH and subsequently reduced use of biofuel in such systems may contribute to a larger reduction of global GHG emissions.
Regarding local and global emissions, the Swedish government [
12] has stated that the transmission capacity in the electricity grid, both domestic and between neighboring countries, shall increase. Hence, in the future we will have an integrated European electricity market. As promoted by the Swedish Environmental Research Institute [
83], marginal production should be used when assessing changes in electricity use. This leads to the marginal electricity being coal condensing power, as presented in
Figure 8. However, other solutions employ a closer geographical perspective and mixed production, such as a Nordic mix production or a national perspective, in this case a Swedish mix production [
81].