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Cost efficiency of district heating for low energy buildings of the future
Energy 177 (2019) 77e86
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Energy journal homepage: www.elsevier.com/locate/energy
Cost efficiency of district heating for low energy buildings of the future* C.H. Hansen a, *, O. Gudmundsson b, N. Detlefsen a a b
Green Energy Association, Merkurvej 7, Kolding, 6000, Denmark Danfoss A/S, Heating Segment, Application and Technology, Nordborgvej 81, Nordborg, 6430, Denmark
a r t i c l e i n f o
a b s t r a c t
Article history: Received 27 December 2018 Received in revised form 3 April 2019 Accepted 7 April 2019 Available online 12 April 2019
Projects like the 4DH research platform and Heat Roadmap Europe have successfully demonstrated that district heating is the only viable solution to efficiently utilize both low-grade renewable energy, excess heat from other sources as well as waste heat for providing heat for space heating and domestic hot water purposes. Nevertheless, there are open questions regarding cost competitiveness of district heating in combination with low energy buildings of the future. In fact, one of the challenges district heating is facing, is the general perception that district heating is too investment intensive compared to individual solutions. In many cases that perception is also used to imply that district heating has no future with the introduction of strict building energy codes that require new buildings to fulfill low energy buildings standards. In this paper, the levelized cost of heating using district heating and individual heating solutions are compared by looking at a concrete area where both the heat demand per square meter as well as the distance between buildings are varied. This study thus analyses when a 4th generation district heating system is competitive, under different linear heat densities. © 2019 Elsevier Ltd. All rights reserved.
Keywords: District heating Low energy buildings Cost efficient Renewables Energy efficiency
1. Introduction District heating penetration in Europe varies between countries, with the front runners Iceland (92%), Denmark (64%), Lithuania (56%) and Sweden (51%), and countries with limited penetration like Norway (3%) and United Kingdom (2%) [12]. In the recent years district heating has been identified by the European Union Commission as one of the key technologies to reach climate goals and reduce emissions. At the same time there is a strong focus on energy efficiency of the whole energy sector, which leads to reduced heating demand of buildings. The trend towards more energy efficient buildings is generally perceived as a challenge to district heating system, since investment cost and heat losses is higher relative to the heating demand. This however should be seen in the perspective of the energy goals, which represents a future with a fossil free energy system. In the perspective of a fossil free energy system the available technologies for space heating becomes district heating and individual heating solutions utilizing green energy
*
This document is a collaborative effort. * Corresponding author. E-mail addresses: [email protected] (C.H. Hansen), [email protected] (O. Gudmundsson), [email protected] (N. Detlefsen). https://doi.org/10.1016/j.energy.2019.04.046 0360-5442/© 2019 Elsevier Ltd. All rights reserved.
sources, such as individual heat pumps, direct electrical heating and biomass boilers, assuming the electricity sector becomes green. Comparing the cost of individual heating solutions is rather simple due to limited number of influencing parameters within the system boundary. In case of district heating solutions like district heating systems the system boundary increases significantly in size and the number of parameters influencing the systems increases significantly as well. Fig. 1 shows the system boundaries for indidivual heating solutions and district heating solutions. The building and heat density of the area affect the length and pipe dimensions of the distribution network. This contributes to the complexity of district heating solutions. As the buildings go from compact to sparse distribution the investment in the distribution network will increase. If the heat demand of the buildings decreases it will only have a minor impact on the distribution network investment. Further different district heating generation units have different investment, operational and fuel costs. These are several reasons why cost comparison between individual heating and district heating solutions are challenging. In Ref. [21] the feasibility of district heating was estimated by relating the heated square meter per land area and the annual heat demand per square meter to the cost of the network distribution cost. The network cost estimation was based on the cost of
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Fig. 1. System boundaries for individual (top) and district heating (bottom) solutions.
establishing district heating systems in multiple cities in Sweden. The approach described in Ref. [21] has been used for initial highlevel assessment of district heating feasibility in areas with high heat densities. The approach is based on aggregated data from existing networks in Sweden, which historically have been supplying high heat demanding buildings. However, due to the many influencing parameters when it comes to establishing the infrastructure, for example labor costs, experience, soil composition, regulations, financial conditions and weather. This approach will only give a first impression of the cost efficiency of district heating. In Ref. [22] the profitability of expanding district heating into areas with low heat densities is analysed using a probable price model. The profitability is estimated using typical marginal heat generation costs and investment costs from actual connections investment in Sweden. It is found that establishing district heating is possible in areas with low heat densities when there is low investment costs for the distribution network and low marginal costs for the heat generation. It is also stated that the competitiveness of district heating compared to individual heating solutions is facilitated by high consumption taxes for fuel oil, natural gas and electricity in Sweden. [20] gives a review of the Swedish sparse district-heating research programme. The programme had a goal to increase the competitiveness for district heating in areas with low heat density. A result from the program is that the Swedish district-heating industry needs to reach a higher level of profitability for investments. Some methods to do this is by innovation, more efficient working routines and revised ways of communicating with customers. These methods can be more important than increasing the efficiency of the district-heating technology.
In Ref. [14] the challenges for the district heating companies are mapped with respect to supplying passive houses with district heating in Sweden. They conclude that it requires active work for the district heating companies to stay competitive against individual heating solutions. It is stated that it is important to communicate with the customers in order to ensure costumer satisfaction. It also stated that the district heating companies should strive to find new applications for use of heat (to get new costumer demand). An example of this could be heat driven technical solutions. In Ref. [18] the concept of 4th generation district heating (4GDH) is defined. The paper describes that the development of 4GDH meets two challenges. One being more energy efficient buildings, another viewing district heating as an integrated part of smart energy systems (both electricity, gas and thermal grids). In Ref. [19] the role of district heating in a future Renewable Energy System is analysed with Denmark as a case. The paper defines a scenario where the Danish energy system is converted to 100% renewable energy. The scenario also includes a space heating demand reduction of 75%. The paper finds that the best solution for converting the todays existing individual natural gas- and oil boilers to renewable energy is an expansion of district heating combined with individual heat pumps in the remaining buildings. [17] asks the question whether district heating can contribute to ensuring the sustainability of future energy systems. The paper shows that this is possible and that it is cost effective to increase the share of the heat demand that is covered by district heating. This also holds when substantial heat saving measures are installed. The differentiation of this study from the above mentioned studies is that in this study a concrete case is analysed and the cost
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Table 1 Assumptions for the individual technologies and the district heating unit. Type of heating
Investment ½V
Efficiency½%
Lifetime [years]
Maintenance ½V=year
District heating unit Oil boiler Wood pellet boiler Natural gas boiler Electrical panel/radiators Air-to-water heat pump Ground source heat pump
6175 7515 10740 6440 4965 12485 20000
100 92 80 92* 100 233* 263*
25 20 20 19* 30 15* 20
65 295 605 255 65 360 360
of establishing a new 4th generation district heating system is compared to todays individual heating solutions in both typical Danish buildings and near-zero energy buildings. With the approach in the analysis it is possible to compare how different scenarios impact the feasibility of different solutions. The scenarios considered in this analysis was the distance between the buildings and the heat demand, going from average Danish heat demand to heat demands corresponding to low-energy building standards. It is a common census that as the heat demands decreases the competitiveness of district heating decreases, primarily due to the relative increase in the specific distribution cost. The reason is that the distribution network cost has a base cost that is loosely dependent on the heat demand, resulting in limited cost savings with decreased heating demand. This has led to the perception that district heating is not cost efficient in areas with low heat density. Although this point can be valid in some areas it does not hold for low energy buildings in urban areas where the distance between buildings is limited, as shown in this study. 2. Data and methodology The following section contains a description of the data used for the paper as well as the underlying assumptions and methodology of the paper.
2.2. Technology data for district heating production units The technology data for the district heating production units are shown in Table 2. The data is based on the Danish Energy Agency Technology Catalogue unless other is stated [7]. In this study the primary district heating production unit is a centralized compression heat pump. It is designed to be able to fulfill 100% of the peak capacity demand. As a backup an electric boiler with the same peak capacity is installed. Also a storage tank dimensioned for 10 h of peak heat production is included in the investment cost estimation. In the study it is assumed that the pipes for district heating will be laid in suburban areas with asphalt and sidewalks. This increases the costs of the district heating grid compared to situations where pipes are laid in unused areas or at the same time as other infrastructure (green field and brown field). The lifetime for district heating pipes is set to 50 years in the analysis. The cost of installing the distribution network was based on experience from establishing new district heating systems in Denmark [15]. Estimation of the heat loss is based on the stated pipe heat loss coefficients of pipes from the pipe manufacturer Logstor A/S. 2.3. Fuel prices The fuel prices used in this study are the pure socioeconomic prices from Ref. [6]. Fig. 2 shows the fuel prices converted to V/GJ.
2.1. Individual heating solutions 2.4. Taxes and economic parameters Although the aim of the study is to compare the cost efficiency of heating solutions that enable the transition of the energy system from fossil fuels to renewable energy sources, it was decided, for sake of completeness, to consider fossil based individual heat sources as well. The considered individual heat sources are oil, wood chip, natural gas, direct electrical panel/radiators and heat pumps based on either air or ground sources. The individual heat sources were dimensioned based on the heat demand and the domestic hot water demand of each building. They were sized to give comparable comfort and reliability as district heating systems would offer, except they were designed with a hot water storage tank to reduce both the capacity requirement and investment cost, due to the domestic hot water part. The technology data for the individual heating solutions are shown in Table 1. The efficiency is based on the total lower heating value and all prices includes Danish VAT1 of 25%. The data source is the Danish Energy Agency Technology Catalogue for individual generation units, unless it is marked with a * [8]. The lifetime of the natural gas boiler is from Ref. [4]. The efficiency of the natural gas boiler is from Ref. [29] with an assumption of 30% domestic hot water consumption. The lifetime of the air-to-water heat pump is from an earlier version of the technology catalogue. The efficiencies of the heat pumps are calculated on the basis of [13].
1
VAT is a value-added tax. The standard VAT rate is 25% in Denmark.
This section contains information regarding the tax and tariff costs as well as the interest rate, distribution and administration costs that are associated with the district heating system. The distribution and administration costs for the district heating system are based on average costs from Danish District Heating Association's Statistics 2015e2016 [3]. The distribution costs are 8,05 V/MWh, while the administration costs are 4,7 V/MWh. The taxes and tariffs shown in Table 3 are the rates concerning the individual technologies in the analysis and are including Danish VAT of 25%. It is assumed that taxes and tariffs are constant in the analysis, but that the fuel prices develop as in Fig. 2. The lower calorific value of gas oil is set at 9964 kWh/l, the taxes on oil are from Refs. [26,27,28]. The lower calorific value for natural gas is set at 11 kWh/Nm3, the taxes and tariffs on natural gas are taken from Refs. [10,25,26,28]. The taxes and tariffs on electricity are from Refs. [9,24]. The taxes and tariffs in Table 4 are the rates concerning the district heating technologies used in the analysis, and are including Danish VAT of 25%. The tax for wood chips is taken from Ref. [28]. The taxes for electricity are taken from Ref. [24] and the tariffs are from Refs. [2,5]. The PSO2 tarif is currently being phased out and is
2 The PSO tarif (Public Service Obligations) is a Danish tarif paid by the consumer as a subsidy to renewable energy.
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Table 2 Assumptions for district heating technologies, Danish VAT excluded.
½V=MWheat ½% [years] ½V=MWheat ½V=MWheat
Investment Efficiency (LHV) Lifetime Fixed O&M Variable O&M
Electrical heat pump
Storage tank
Eletric boiler
0,7 400 20b 2010 15
155a 95 20c 0d 0
0,08 99 20 1210 4
a
The price is in V/m.3. The Technology Catalogue assumes a lifetime of 25 years for a compression heat pump for district heating. A lifetime of 20 years is used in this analysis based on experience from danish district heating projects. c The lifetime is not specified in the Technology Catalogue, but is assumed to be 20 years. d Fixed and variable operation and maintenance costs are not specified for storage tanks in the Technology Catalogue. b
Table 4 Table containing taxes and tariffs for district heating technologies. Tax/Tariff
Electricity ½V=MWh
Energy tax Distribution tariff System and transmission tariff
67 953 17 936 13 926
for both the space heating and domestic hot water demands to avoid oversizing the pipes. The simultaneity factors applied for the space heating and DHW can be seen in Fig. 4. The space heating simultaneity factors are based on Danish norms and the DHW simultaneity factor are based on the Euroheat & Power recommendations [11]. The pipes were dimensioned using a maximum pressure drop of 150 Pa/m and flow velocities of max 2 m/s.
2.6. Case analysis
Fig. 2. Fuel prices for the technologies. The prices are raw prices, meaning without taxes, tariffs etc.
Table 3 Table containing taxes and tariffs for the individual technologies. Tax/Tariff Energy tax CO2 NOx Distribution
Gas oil ½V=l
Electricity ½V=kWh
Natural gas ½V=Nm3
0,333 0,076 0,001 e
a
0368 0,065 0,001 c 0,186
0,068 e e b 0,060
a It is assumed that the electricity for heating is only subject to the lowered electricity tax. b Net tariff, transport and commerce. c Including emergency supply tariff.
therefore not a part of this analysis. 2.5. District heating network To have a realistic base for the layout of the distribution network, it was designed according to a neighborhood in the town of Fredericia in Denmark, which has a mixture of multi-family, attached and single-family houses, see Fig. 3. The network was sized according to the specified design heating demand of the buildings and instantaneous domestic hot water (DHW) connection of 32,5 kW. Simultaneity factors were applied
In the analysis the domestic hot water (DHW) demand was kept constant for all cases, but the space heating demand of the buildings were varied as well as the distance between the connected buildings. The purpose of varying the space heating demand was to assess the impact the dimensioning of the distribution network has on the yearly cost of heating as the heat demand decreases. The purpose of varying the distances between the buildings was to assess how far the network could be expanded while still being cost beneficial compared to individual heating solutions. To estimate the impact of the building density on the competitiveness of the district heating the distances between buildings was increased to three times the base scenario (shown in Fig. 5). This means that the length of the district heating network pipes are three times longer than the base scenario. For each scenario of changed heat demand and building density, the distribution network was dimensioned to match the situation. The base scenario is the scenario with the most dense linear heat density in the analysis and is referred to as network scale 1. This corresponds to the suburban area shown in Fig. 3. The case where the district heating network pipes is three times longer is here referred to as network scale 3. Mathematically speaking, changing the space heating demand and the distances between buildings can be seen as two different ways of changing the linear heat density in the district heating system. A constant DHW demand is assumed in the analysis because it is behavioral dependent and as such it was not considered realistic that the building insulation level has an effect on the DHW demand. For a residence of 130 m2 the DHW consumption is about 3100 kWh/year.
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Fig. 3. Left: The analysed area. Right: Network layout design.
2.7. Buildings The analysis compares the economic tradeoffs between state of the art 4th generation district heating system to state of the art individual heating solutions as the building are moved towards low energy buildings standards. To analyze the impact of stricter building codes, on the competitiveness of district heating the space heating demand was varied from a typical heating demand in a Danish energy renovated 1970 building ð106; 1 kWh=m2 =yearÞ, down to what is expected from buildings fulfilling nearly-zero energy standard ð37; 8 kWh=m2 =yearÞ. In total six different heat demand variations is considered in this paper. They can be seen in Table 5. 2.8. Cost comparison
Fig. 4. Simultaneity factors for space heating (sh) and domestic hot water (dhw) demand as a function of the number of consumers.
To analyze whether district heating can compete with individual heating, the costs are calculated as the average yearly costs in a ^V™s lifetime. As different technologies have different technologya expected lifetimes, the investment costs are annualized. An alternative method would have been to look on a very long time horizon to mask out the impact of reinvestments. The total cost is based on the capital investment, maintenance cost, driving energy cost and unit efficiency. The average yearly price of heat is found by using Formula (1)
Fig. 5. Example of the network scaling of the area, shown to illustrate a change in linear heat density. Source: [16].
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Table 5 Heat demand variations in the analysis. Variation Space heating demand ½kWh=m2 =year
Domestic hot water demand ½kWh=m2 =year
Total demand at 130 m2½kWh=year
Design space heating capacity ½W=m2
1 2 3 4 5 6
24,1 24,1 24,1 24,1 24,1 24,1
13800 12000 10200 8500 6700 4900
30 25 20 15 10 5
82,0 68,3 54,6 41,0 27,3 13,7
[1].
Avg:yearly price of heat ¼ NVj ðkÞ,a1 T;k " # T X ¼ NBj;t ð1 þ kÞt ,a1 T;k
(1)
t¼0
where aT;k , is the capital gains factor or the annuity factor which is defined in Formula (2)
aT;k ¼
1 ð1 þ kÞt k
(2)
NBj;t is the net payment at time t for alternative j. T is the lifetime of the investment and k is the discount rate. NVj is the present value of alternative j as a function of the discount rate. The discount rate considered in this analysis was 4% for both district heating and individual heating technologies. 3. Results 3.1. Impact of design space heating capacity on the capital cost When considering the impact of reduced space heating demand it must be noted that the space heating generally counts less than half of the total capacity demand. The design space heating capacity3 therefore does not have much influence on the main distribution network cost, since the majority of the demand will be caused by the DHW preparation, which is dimensioned to be 32,5 kW for instantaneous DHW preparation and typically 3e6 kW for storage tank solutions. In the analysis it is assumed that all households use instantaneous DHW preparation. For the connection with a space heating demand of 82,0 kWh/m2/year the space heating peak capacity demand is 3,9 kW, while it is 0,65 kW for a connection with a space heating demand of 13,7 kWh/m2/year. As the differences in the required capacity does not change that much there is only a limited cost saving to find for individual heating units and no cost savings in the district heating substations and the service pipeline. 3.2. District heating main distribution pipeline There is generally a limited cost savings achieved in the distribution network as the capacity demand reduces. This is because a) a large part of the investment cost is independent or loosely connected to the capacity, for example planning cost, permit costs and excavation cost, and b) pipes come in discrete sizes, meaning even if the capacity drops to some extent it does not necessarily mean that smaller pipes can be used. The impact of the reduced heat demand on the main distribution pipe network cost when going from a
3 The design space heating capacity is the buildings dimensioning heat loss at 12+C.
Fig. 6. Impact of the space heating demand ðW=m2 Þ on the main distribution network cost.ðMVÞ
design space heating demand of 30 W/m2 to 5 W/m2 is shown in Fig. 6.
3.3. District heating generation units The main benefits of district heating compared to individual heating solutions is realized at the heat source. First of all the heat source design capacity will be much lower than the sum of the capacities from individual heating units due to simultaneity of usage, secondly economy of scale provides better possibilities of realizing low price for the driving energy and thirdly there will be much higher freedom of choosing the appropriate heat source. When dimensioning the heat source in this study, simultaneity was only applied on the DHW demand. By applying simultaneity factors on the heating demand, slight design distribution capacity savings could be achieved, it will although have minimal impact on the cost of the distribution grid, as Fig. 6 indicates. The applied aggregated DHW profile used in the study is shown in Fig. 7. The space heating demand was determined based on the outdoor temperature according to the standardized Copenhagen weather profile [23], no simultaneity or demand shifting due to building thermal mass was considered. Similar to Fig. 6 the impact of the design space heating capacity on the cost of the heat source can be seen in Fig. 8. The costs include both the electrical compression heat pump, electric boiler and storage tank.
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Fig. 7. Daily DHW profile (percentage of daily use) applied in the study to estimate the impact of the DHW on the heat source capacity requirement.
Fig. 9. Comparison of the price of heat between newly established district heating (network scale 1) using an electric heat pump and different types of individual heating. The heat demand is 13800 kWh/year. The network scale of 1 for district heating refers to the most dense linear heat density (in this study) explained in Section 2.6.
Fig. 8. Impact of the space heating demand ðW=m2 Þ on the heat production facility investment cost.ðMVÞ
3.4. Economical comparison between district heating and individual heating solutions Fig. 9 shows the yearly costs for providing space heating and domestic hot water to a household with a total heat demand of 13800 kWh/year. The district heating is produced on an electrical compression heat pump. The figure shows that under the assumptions in this paper, the newly established district heating system is the cheapest form of heating for a household. The second cheapest alternative is an individual natural gas boiler, which is around 430V more expensive than district heating, per year. After the individual natural gas boiler comes the individual air/water heat pump and individual wood pellet boiler, which is respectively
Fig. 10. Comparison of the price of heat between newly established district heating (network scale 1) using an electric heat pump and different types of individual heating. The heat demand is 4900 kWh/year (near-zero energy building).
790V and 805V more expensive than district heating, per year. Fig. 10 shows the yearly costs for providing space heating and domestic hot water to a household with a total heat demand of
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4900 kWh/year. The rest of the assumptions are the same as in Fig. 9. The results show that a newly established district heating system is also the cheapest form of heating for low energy building. District heating is around 207V cheaper than electrical heating, which is the cheapest alternative to district heating. The individual natural gas boiler is around 40V more expensive per year compared to electrical heating. This is because the space heating in this scenario is so low that the investment cost is a very significant factor. Individual electrical heating has much lower investment costs than natural gas. So much that it offsets the relatively high variable costs of electrical heating.
3.5. Impact of increased distances between connected buildings It is well known that district heating is a good solution for urban areas. Generally, it can be said that the more densely built and heat intense the buildings are, the more cost competitive district heating becomes. In this respect it is of interest to get an idea on a) how the building density will impact the competitiveness and b) what the influence of reduced building heat demand will have on the competitiveness. Generally, this is addressed through the linear heat density, which is the yearly heat delivery per pipe meter per year. By doing a quick estimation of the linear heat density of an area it is possible to get a first impression of the feasibility of district
heating compared to alternative solutions, see Ref. [21] for an example of a method to estimate the linear heat density of an area. Fig. 11 gives an idea on how linear heat density will impact the cost competitiveness of district heating versus its cheapest alternatives in a Danish context. Fig. 11 shows that as the space heating demand decreases, the distance between the yearly heating cost of district heating and the individual heating solutions decrease on an absolute level. The cheapest alternative is a natural gas boiler for 30 W/m2 to 10 W/m2 and electrical panel/radiators for 5 W/m2. District heating is a competitive solution for all the cases where the network scale is between 1 and 2. As the heating demand moves toward the demand of a low energy building and the distance between buildings increase, then the yearly heating cost of district heating gets closer to the yearly heating cost of the individual heating solutions. This is natural since increasing the distance between buildings will increase the heat loss in the district heating system and greatly increase the investment cost, and in the case of low energy buildings there are less energy units to split the costs on. For a network scale of 2,5, district heating is not able to compete on price alone for the case where a household only has a heat demand of 4900 kWh/year. If the network scale is increased to 3, this will be the case for the four cases with a heat demand of 10 200 kWh/year or less. There are a number of factors that will impact the competitiveness, for example system operating temperatures, pipe selection, soil composition, applied heat source, fuel costs and taxes. Due to the many factors that impact the cost of district heating systems, a proper feasibility study is always needed to determine the actual situation for a given area. 3.6. Impact of percentage of connected costumers
Fig. 11. Yearly heating cost for the six different heat demand variations combined with different district heating network scales, compared to the cheapest individual alternative for each heat demand variation. The heating cost of district heating is represented by the dots (dashed lines), while the cheapest individual alternatives is represented by the solid lines. In the figure the dots should only be compared to the solid lines of the same color. As an example, all the green dots represent yearly heating costs for a building with a heating demand of 5 W/m2, but the linear heat density is varied from dense (network scale of 1) to sparse (network scale of 3). The green dots should only be compared to the solid green line, showing the cheapest individual alternative (in this case electrical panel/radiators). If a dot is below the solid line of the same color, district heating is cheaper than the cheapest individual heating solution. If a dot is above the solid line of the same color, an individual heating solution is cheaper than establishing a district heating system. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
The results in this paper has so far been based on the assumption that the district heating system is dimensioned to supply the whole heat demand in the considered area and that all the household in the area will be connected to the district heating system. In the following it will still be assumed that the district heating system is dimensioned such that it can supply the whole heat demand in the considered area, but it is investigated what will happen to the competitiveness of the district heating system if not all costumers choose to connect to the district heating system. This means that fewer costumers will have to carry the investment costs and heat loss of the full system. For a heat demand variation the investment costs will in this context be identical for all percentages of connected costumers, as will the heat losses in the main pipes. Only the heat losses in the service pipes will be reduced with the percentage of connected costumers. As this is an illustrative sensitivity analysis it is assumed that the flow in the system is sufficient for all percentages of connected costumers (meaning that there is not placed e.g. a shunt in the system to increase the flow rate). The two dots in Fig. 12 are also found in Fig. 11 for the case with a network scale of 2. A network scale of 2 is applied in Fig. 12 because it can be seen in Fig. 11 that for this network scale and a heat demand of 30 W/m2 (13 800 kWh/year), district heating is very competitive compared to the cheapest individual alternative. For this network scale and a heat demand of 5 W/m2 (4900 kWh/year), district heating is only just competitive compared to the cheapest individual alternative. This means that district heating for this network scale ranges from very competitive to just competitive, when varying the heat demand, making it an interesting case on which to analyze the impact of connected customers. The figure shows that as the percentage of connected customers decrease, the less competitive the district heating system becomes.
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Fig. 12. Yearly heating cost for a heat demand of 13 800 kWh/year and 4900 kWh/year with a network scale of 2. The percentage of connected costumers to the district heating system is varied and compared to the cheapest individual alternative for the heat demand variation. As in Fig. 11 the heating cost of district heating is represented by the dot/x's (dashed lines), while the cheapest individual alternatives is represented by the solid lines. In the figure the dot/x's should only be compared to the solid lines of the same color. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
This is natural since district heating is a collective system which benefits from more customers. For the case with a heat demand of 4900 kWh/year, the district heating system is only marginally cheaper than the individual heating alternative. This means that when the percentage of connected customers fall below 90e95% the district heating system is not competitive. For the case with a heat demand of 13 800 kWh/year, the district heating system is very competitive compared to the individual heating alternative. In this case the percentage of connected customers can fall below 80% and still be competitive compared to the indvidiual heating alternative. For a network scale of 1 the competitiveness of district heating is higher and less sensitive to the percentage of connected customers. In general it can be observed that the higher the linear heat density is in an area, fewer customers are required for district heating to be competitive when comparing to an individual heating alternative. Although a district heating system can be competitive with fewer connected customers, more customers will descrease the costs for the whole system. An alternative approach would be to dimension the system to a fewer number of customers at first. This would however result in a more expensive system since adding more customers to the system will result in added investment costs. The costs of a system built in two steps will be significantly higher than a system built in one step.
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for district heating compared to an individual natural gas boiler. Compared to an individual biomass boiler and an individual air-towater heat pump, district heating is approximately 750V cheaper. In percentages, the annual cost of district heating is approximately 18% lower than an individual natural gas boiler and approximately 30% cheaper than an individual biomass boiler and an individual air-to-water heat pump. In a scenario where the buildings meet the energy limit of the Danish building regulations for 2015 (BR15), a new district heating system is the most cost-effective source of heating when compared to individual heating solutions. For a 130 m2 building this is equivalent to a heat demand of 4900 kWh/year. In this scenario the yearly price of heating is approximately 200 V cheaper than individual electric heating (16%) and 250V cheaper than an individual natural gas boiler (19%). Compared to an individual air-to-water heat pump, the yearly price of heating for a new district heating system is approximately 875V cheaper (45%). These results are for a dense area. In areas with both low heat demand and low building density, district heating is not the most competitive heating solution. As this analysis was performed under Danish conditions it was of particular interest to investigate the impact of taxes on the results. The results show that even if energy taxes are lowered or completely removed the analysis show that a new district heating system is the most cost-effective source of heating. The economics of scale of the heat source and accessibility to fuels with lower costs will outweigh the added investment in the distribution grid and the unavoidable distribution heat losses. The analysis shows that the percentage of connected customers in an area is an important factor for the district heating system. For a district heating system with a low linear heat density (low energy buildings and a large distribution network), close to full participation from the possible customers is required for the district heating system to be competitive. For systems with high linear heat densities (larger heat demand from buildings, denser distribution network or both) fewer customers are required for the district heating system to be competitive. This result is consistent with dense district heating systems being more competitive than a less dense district heating systems, all else equal. The overall outcome of this study is that a new district heating system is competitive compared to individual heating solutions. Both for the existing building stock as well as for the future low energy building stock. There is even room for considerable uncertainties regarding the costs of establishing the district heating network. In addition to being more cost efficient than individual heating solutions, it opens up for a variety of options to reduce greenhouse gas emissions by making a collective conversion to a fuel source emitting less green house gasses. Outside Denmark, it is likely that the heat in a district heating system will not be produced with the same technologies as in Denmark. The final result depends on fuel prices, tariffs and taxes and as these vary from country to country the results may change. However, the advantages of district heating (high fuel efficiency, lower heat production capacity requirement and cheaper fuels) will most often make district heating cost efficient. This is especially the case in densely populated areas where the relative heat loss will be low.
4. Conclusion CRediT authorship contribution statement In a scenario where the buildings correspond to a typical energy renovated Danish building from 1970, a new district heating system is the most cost-effective source of heating. For a 130 m2 building this is equivalent to a heat demand of 13800 kWh/year. In this scenario the yearly price of heating is approximately 400V cheaper
C.H. Hansen: Conceptualization, Methodology, Formal analysis, Writing - original draft, Visualization. O. Gudmundsson: Conceptualization, Methodology, Formal analysis, Writing - original draft. N. Detlefsen: Conceptualization, Supervision.
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References [1] Christensen Peter Ove. Investeringsteori. 2 edition. Syddansk Universitetsforlag; 2005. [2] Energi Dansk. Elforsyningens nettariffer & priser. Dansk Energi; 2016. https:// www.danskenergi.dk/~/media/Filer_til_nyheder_2016/Elforsyningens_ nettariffer_og_priser_2016-endelig.ashx. [3] Fjernvarme Dansk. Statistik 2015/2016. 2016. http://www.danskfjernvarme. dk/-/media/danskfjernvarme/videnom/aarstatistik/%C3%A5rsstatistik-2016—n %C3%B8gletal.xlsx. [4] DGC. Gaskedlers levetid er omkring 19 år i gennemsnit. September 2017. http://www.dgc.dk/sites/default/files/filer/publikationer/A1621_gaskedler_ levetid.pdf. [5] Energinet.dk. Tariffer. September 2016. https://www.energinet.dk/El/Tariffer. [6] Energistyrelsen. Samfundsøkonomiske beregningsforudsætninger for energipriser og emissioner. 2017 apr. https://ens.dk/sites/ens.dk/files/Analyser/ samfundsoekonomiske_beregningsforudsaetninger_2017_ver_2.pdf. [7] Energistyrelsen. Dataark for el og fjernvarmeproduktion. 2017. https://ens.dk/ sites/ens.dk/files/Analyser/technology_data_for_el_and_dh_-_upd_dec2018. xlsm. [8] Energistyrelsen. Teknologikatalog for individuelle varmeanlæg og energitransport. 2017. https://ens.dk/sites/ens.dk/files/Analyser/sep_2017_ update_-_technology_data_for_individuel_heating_-_.xlsx. [9] Energitilsynet. Elprisstatistik 1. kvartal 2017. sep 2016. http://energitilsynet. dk/fileadmin/Filer/0_-_Nyt_site/EL/Prisstatistik/2017/Elprisstatistik_1.__ kvartal_2017.pdf. [10] Energitilsynet. Naturgasstatistik 1. kvartal 2017. sep 2017. http:// energitilsynet.dk/fileadmin/Filer/0_-_Nyt_site/GAS/Prisstatistik/2017/ Naturgasstatistik_1._kvt._2017.pdf. [11] Euroheat & Power. Guidelines for district heating substations. 2008. https:// www.euroheat.org/wp-content/uploads/2008/04/Euroheat-PowerGuidelines-District-Heating-Substations-2008.pdf. [12] Euroheat & Power. Country by country statistics 2017. 2017. https://www. euroheat.org/publications/country-country-2017/. [13] ForskEL. Styr din varmepumpe vers. 2. feb 2015. https://www. styrdinvarmepumpe.dk/sites/default/files/Slutrapportering%20fra%20SDVP2% 20forskEL%2012075.pdf. €ling, Reidhav Charlotte, Dalenba €ck Jan Olof, Werner Sven. Is there [14] Morgan Fro a role for district heating in future cities with low energy bulidings?. In: The 11th international symposium on district heating and cooling; 2008. http:// citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.605.7245. [15] Energi Grøn. The competitiveness of district heating compared to individual
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heating. 2018. https://www.danskfjernvarme.dk/-/media/danskfjernvarme/ gronenergi/analyser/03052018-the-competitiveness-of-district-heatingcompared-to-individual-heatingv2.pdf. Energi Grøn. Fjernvarme har konkurrencefordele over for individuel forsyning. 2018. https://www.danskfjernvarme.dk/groen-energi/nyheder/arkiv/ 2018/180409-se-fjernvarmens-konkurrenceforhold-overfor-individuelforsyning. €ller Bernd, Vad Mathiesen Brian, Anders Dyrelund. The role of Lund Henrik, Mo district heating in future renewable energy systems. Energy 2010. https://doi. org/10.1016/j.energy.2009.11.023. Lund Henrik, Werner Sven, Wiltshire Robin, Svendsen Svend, Thorsen Jan Eric, Hvelplund Frede, Vad Mathiesen Brian. 4th generation district heating (4gdh) integrating smart thermal grids into future sustainable energy systems. Energy 2014. https://doi.org/10.1016/j.energy.2014.02.089. Münster Marie, Morthorst Poul Erik, Larsen Helge V, Bregnbæk Lars, Werling Jesper, Lindboe Hans Henrik, Ravn Hans. The role of district heating in the future Danish energy system. Energy 2012. https://doi.org/10.1016/j. energy.2012.06.011. Nilsson Stefan Forsaeus, Reidhav Charlotte, Lygnerud Kristina, Werner Sven. Sparse district-heating in Sweden. Appl Energy 2008. https://doi.org/10.1016/ j.apenergy.2007.07.011. Persson Urban, Werner Sven. Heat distribution and the future competitiveness of district heating. Appl Energy 2011. https://doi.org/10.1016/j.apenergy. 2010.09.020. Reidhav Charlotte, Werner Sven. Profitability of sparse district heating. Appl Energy 2008. https://doi.org/10.1016/j.apenergy.2008.01.006. SBI. Climate data. December 2018. https://sbi.dk/bsim/Pages/Climate-data. aspx. SKAT. Skat. 2017 September. http://www.skm.dk/skattetal/satser/satser-ogbeloebsgraenser/elafgiftsloven. SKAT. Skat. 2017 September. http://www.skm.dk/skattetal/satser/satser-ogbeloebsgraenser/gasafgiftsloven. SKAT. Skat. 2017 September. http://www.skm.dk/skattetal/satser/satser-ogbeloebsgraenser/co2-afgiftsloven. SKAT. Skat,. 2017 September. http://www.skm.dk/skattetal/satser/satser-ogbeloebsgraenser/mineralolieafgiftsloven. SKAT. Skat. 2017 September. http://www.skm.dk/skattetal/satser/satser-ogbeloebsgraenser/kvaelstofoxiderafgiftsloven-nox. Vaillant. Ecotec plus vcw/vci med actostor vih cl 25 s. September 2017. https://www.vaillant.dk/kunder/produkter/ecotec-plus-vcw-vci-medactostor-vih-cl-25-s-836.html.
Contents lists available at ScienceDirect
Energy journal homepage: www.elsevier.com/locate/energy
Cost efficiency of district heating for low energy buildings of the future* C.H. Hansen a, *, O. Gudmundsson b, N. Detlefsen a a b
Green Energy Association, Merkurvej 7, Kolding, 6000, Denmark Danfoss A/S, Heating Segment, Application and Technology, Nordborgvej 81, Nordborg, 6430, Denmark
a r t i c l e i n f o
a b s t r a c t
Article history: Received 27 December 2018 Received in revised form 3 April 2019 Accepted 7 April 2019 Available online 12 April 2019
Projects like the 4DH research platform and Heat Roadmap Europe have successfully demonstrated that district heating is the only viable solution to efficiently utilize both low-grade renewable energy, excess heat from other sources as well as waste heat for providing heat for space heating and domestic hot water purposes. Nevertheless, there are open questions regarding cost competitiveness of district heating in combination with low energy buildings of the future. In fact, one of the challenges district heating is facing, is the general perception that district heating is too investment intensive compared to individual solutions. In many cases that perception is also used to imply that district heating has no future with the introduction of strict building energy codes that require new buildings to fulfill low energy buildings standards. In this paper, the levelized cost of heating using district heating and individual heating solutions are compared by looking at a concrete area where both the heat demand per square meter as well as the distance between buildings are varied. This study thus analyses when a 4th generation district heating system is competitive, under different linear heat densities. © 2019 Elsevier Ltd. All rights reserved.
Keywords: District heating Low energy buildings Cost efficient Renewables Energy efficiency
1. Introduction District heating penetration in Europe varies between countries, with the front runners Iceland (92%), Denmark (64%), Lithuania (56%) and Sweden (51%), and countries with limited penetration like Norway (3%) and United Kingdom (2%) [12]. In the recent years district heating has been identified by the European Union Commission as one of the key technologies to reach climate goals and reduce emissions. At the same time there is a strong focus on energy efficiency of the whole energy sector, which leads to reduced heating demand of buildings. The trend towards more energy efficient buildings is generally perceived as a challenge to district heating system, since investment cost and heat losses is higher relative to the heating demand. This however should be seen in the perspective of the energy goals, which represents a future with a fossil free energy system. In the perspective of a fossil free energy system the available technologies for space heating becomes district heating and individual heating solutions utilizing green energy
*
This document is a collaborative effort. * Corresponding author. E-mail addresses: [email protected] (C.H. Hansen), [email protected] (O. Gudmundsson), [email protected] (N. Detlefsen). https://doi.org/10.1016/j.energy.2019.04.046 0360-5442/© 2019 Elsevier Ltd. All rights reserved.
sources, such as individual heat pumps, direct electrical heating and biomass boilers, assuming the electricity sector becomes green. Comparing the cost of individual heating solutions is rather simple due to limited number of influencing parameters within the system boundary. In case of district heating solutions like district heating systems the system boundary increases significantly in size and the number of parameters influencing the systems increases significantly as well. Fig. 1 shows the system boundaries for indidivual heating solutions and district heating solutions. The building and heat density of the area affect the length and pipe dimensions of the distribution network. This contributes to the complexity of district heating solutions. As the buildings go from compact to sparse distribution the investment in the distribution network will increase. If the heat demand of the buildings decreases it will only have a minor impact on the distribution network investment. Further different district heating generation units have different investment, operational and fuel costs. These are several reasons why cost comparison between individual heating and district heating solutions are challenging. In Ref. [21] the feasibility of district heating was estimated by relating the heated square meter per land area and the annual heat demand per square meter to the cost of the network distribution cost. The network cost estimation was based on the cost of
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Fig. 1. System boundaries for individual (top) and district heating (bottom) solutions.
establishing district heating systems in multiple cities in Sweden. The approach described in Ref. [21] has been used for initial highlevel assessment of district heating feasibility in areas with high heat densities. The approach is based on aggregated data from existing networks in Sweden, which historically have been supplying high heat demanding buildings. However, due to the many influencing parameters when it comes to establishing the infrastructure, for example labor costs, experience, soil composition, regulations, financial conditions and weather. This approach will only give a first impression of the cost efficiency of district heating. In Ref. [22] the profitability of expanding district heating into areas with low heat densities is analysed using a probable price model. The profitability is estimated using typical marginal heat generation costs and investment costs from actual connections investment in Sweden. It is found that establishing district heating is possible in areas with low heat densities when there is low investment costs for the distribution network and low marginal costs for the heat generation. It is also stated that the competitiveness of district heating compared to individual heating solutions is facilitated by high consumption taxes for fuel oil, natural gas and electricity in Sweden. [20] gives a review of the Swedish sparse district-heating research programme. The programme had a goal to increase the competitiveness for district heating in areas with low heat density. A result from the program is that the Swedish district-heating industry needs to reach a higher level of profitability for investments. Some methods to do this is by innovation, more efficient working routines and revised ways of communicating with customers. These methods can be more important than increasing the efficiency of the district-heating technology.
In Ref. [14] the challenges for the district heating companies are mapped with respect to supplying passive houses with district heating in Sweden. They conclude that it requires active work for the district heating companies to stay competitive against individual heating solutions. It is stated that it is important to communicate with the customers in order to ensure costumer satisfaction. It also stated that the district heating companies should strive to find new applications for use of heat (to get new costumer demand). An example of this could be heat driven technical solutions. In Ref. [18] the concept of 4th generation district heating (4GDH) is defined. The paper describes that the development of 4GDH meets two challenges. One being more energy efficient buildings, another viewing district heating as an integrated part of smart energy systems (both electricity, gas and thermal grids). In Ref. [19] the role of district heating in a future Renewable Energy System is analysed with Denmark as a case. The paper defines a scenario where the Danish energy system is converted to 100% renewable energy. The scenario also includes a space heating demand reduction of 75%. The paper finds that the best solution for converting the todays existing individual natural gas- and oil boilers to renewable energy is an expansion of district heating combined with individual heat pumps in the remaining buildings. [17] asks the question whether district heating can contribute to ensuring the sustainability of future energy systems. The paper shows that this is possible and that it is cost effective to increase the share of the heat demand that is covered by district heating. This also holds when substantial heat saving measures are installed. The differentiation of this study from the above mentioned studies is that in this study a concrete case is analysed and the cost
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Table 1 Assumptions for the individual technologies and the district heating unit. Type of heating
Investment ½V
Efficiency½%
Lifetime [years]
Maintenance ½V=year
District heating unit Oil boiler Wood pellet boiler Natural gas boiler Electrical panel/radiators Air-to-water heat pump Ground source heat pump
6175 7515 10740 6440 4965 12485 20000
100 92 80 92* 100 233* 263*
25 20 20 19* 30 15* 20
65 295 605 255 65 360 360
of establishing a new 4th generation district heating system is compared to todays individual heating solutions in both typical Danish buildings and near-zero energy buildings. With the approach in the analysis it is possible to compare how different scenarios impact the feasibility of different solutions. The scenarios considered in this analysis was the distance between the buildings and the heat demand, going from average Danish heat demand to heat demands corresponding to low-energy building standards. It is a common census that as the heat demands decreases the competitiveness of district heating decreases, primarily due to the relative increase in the specific distribution cost. The reason is that the distribution network cost has a base cost that is loosely dependent on the heat demand, resulting in limited cost savings with decreased heating demand. This has led to the perception that district heating is not cost efficient in areas with low heat density. Although this point can be valid in some areas it does not hold for low energy buildings in urban areas where the distance between buildings is limited, as shown in this study. 2. Data and methodology The following section contains a description of the data used for the paper as well as the underlying assumptions and methodology of the paper.
2.2. Technology data for district heating production units The technology data for the district heating production units are shown in Table 2. The data is based on the Danish Energy Agency Technology Catalogue unless other is stated [7]. In this study the primary district heating production unit is a centralized compression heat pump. It is designed to be able to fulfill 100% of the peak capacity demand. As a backup an electric boiler with the same peak capacity is installed. Also a storage tank dimensioned for 10 h of peak heat production is included in the investment cost estimation. In the study it is assumed that the pipes for district heating will be laid in suburban areas with asphalt and sidewalks. This increases the costs of the district heating grid compared to situations where pipes are laid in unused areas or at the same time as other infrastructure (green field and brown field). The lifetime for district heating pipes is set to 50 years in the analysis. The cost of installing the distribution network was based on experience from establishing new district heating systems in Denmark [15]. Estimation of the heat loss is based on the stated pipe heat loss coefficients of pipes from the pipe manufacturer Logstor A/S. 2.3. Fuel prices The fuel prices used in this study are the pure socioeconomic prices from Ref. [6]. Fig. 2 shows the fuel prices converted to V/GJ.
2.1. Individual heating solutions 2.4. Taxes and economic parameters Although the aim of the study is to compare the cost efficiency of heating solutions that enable the transition of the energy system from fossil fuels to renewable energy sources, it was decided, for sake of completeness, to consider fossil based individual heat sources as well. The considered individual heat sources are oil, wood chip, natural gas, direct electrical panel/radiators and heat pumps based on either air or ground sources. The individual heat sources were dimensioned based on the heat demand and the domestic hot water demand of each building. They were sized to give comparable comfort and reliability as district heating systems would offer, except they were designed with a hot water storage tank to reduce both the capacity requirement and investment cost, due to the domestic hot water part. The technology data for the individual heating solutions are shown in Table 1. The efficiency is based on the total lower heating value and all prices includes Danish VAT1 of 25%. The data source is the Danish Energy Agency Technology Catalogue for individual generation units, unless it is marked with a * [8]. The lifetime of the natural gas boiler is from Ref. [4]. The efficiency of the natural gas boiler is from Ref. [29] with an assumption of 30% domestic hot water consumption. The lifetime of the air-to-water heat pump is from an earlier version of the technology catalogue. The efficiencies of the heat pumps are calculated on the basis of [13].
1
VAT is a value-added tax. The standard VAT rate is 25% in Denmark.
This section contains information regarding the tax and tariff costs as well as the interest rate, distribution and administration costs that are associated with the district heating system. The distribution and administration costs for the district heating system are based on average costs from Danish District Heating Association's Statistics 2015e2016 [3]. The distribution costs are 8,05 V/MWh, while the administration costs are 4,7 V/MWh. The taxes and tariffs shown in Table 3 are the rates concerning the individual technologies in the analysis and are including Danish VAT of 25%. It is assumed that taxes and tariffs are constant in the analysis, but that the fuel prices develop as in Fig. 2. The lower calorific value of gas oil is set at 9964 kWh/l, the taxes on oil are from Refs. [26,27,28]. The lower calorific value for natural gas is set at 11 kWh/Nm3, the taxes and tariffs on natural gas are taken from Refs. [10,25,26,28]. The taxes and tariffs on electricity are from Refs. [9,24]. The taxes and tariffs in Table 4 are the rates concerning the district heating technologies used in the analysis, and are including Danish VAT of 25%. The tax for wood chips is taken from Ref. [28]. The taxes for electricity are taken from Ref. [24] and the tariffs are from Refs. [2,5]. The PSO2 tarif is currently being phased out and is
2 The PSO tarif (Public Service Obligations) is a Danish tarif paid by the consumer as a subsidy to renewable energy.
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Table 2 Assumptions for district heating technologies, Danish VAT excluded.
½V=MWheat ½% [years] ½V=MWheat ½V=MWheat
Investment Efficiency (LHV) Lifetime Fixed O&M Variable O&M
Electrical heat pump
Storage tank
Eletric boiler
0,7 400 20b 2010 15
155a 95 20c 0d 0
0,08 99 20 1210 4
a
The price is in V/m.3. The Technology Catalogue assumes a lifetime of 25 years for a compression heat pump for district heating. A lifetime of 20 years is used in this analysis based on experience from danish district heating projects. c The lifetime is not specified in the Technology Catalogue, but is assumed to be 20 years. d Fixed and variable operation and maintenance costs are not specified for storage tanks in the Technology Catalogue. b
Table 4 Table containing taxes and tariffs for district heating technologies. Tax/Tariff
Electricity ½V=MWh
Energy tax Distribution tariff System and transmission tariff
67 953 17 936 13 926
for both the space heating and domestic hot water demands to avoid oversizing the pipes. The simultaneity factors applied for the space heating and DHW can be seen in Fig. 4. The space heating simultaneity factors are based on Danish norms and the DHW simultaneity factor are based on the Euroheat & Power recommendations [11]. The pipes were dimensioned using a maximum pressure drop of 150 Pa/m and flow velocities of max 2 m/s.
2.6. Case analysis
Fig. 2. Fuel prices for the technologies. The prices are raw prices, meaning without taxes, tariffs etc.
Table 3 Table containing taxes and tariffs for the individual technologies. Tax/Tariff Energy tax CO2 NOx Distribution
Gas oil ½V=l
Electricity ½V=kWh
Natural gas ½V=Nm3
0,333 0,076 0,001 e
a
0368 0,065 0,001 c 0,186
0,068 e e b 0,060
a It is assumed that the electricity for heating is only subject to the lowered electricity tax. b Net tariff, transport and commerce. c Including emergency supply tariff.
therefore not a part of this analysis. 2.5. District heating network To have a realistic base for the layout of the distribution network, it was designed according to a neighborhood in the town of Fredericia in Denmark, which has a mixture of multi-family, attached and single-family houses, see Fig. 3. The network was sized according to the specified design heating demand of the buildings and instantaneous domestic hot water (DHW) connection of 32,5 kW. Simultaneity factors were applied
In the analysis the domestic hot water (DHW) demand was kept constant for all cases, but the space heating demand of the buildings were varied as well as the distance between the connected buildings. The purpose of varying the space heating demand was to assess the impact the dimensioning of the distribution network has on the yearly cost of heating as the heat demand decreases. The purpose of varying the distances between the buildings was to assess how far the network could be expanded while still being cost beneficial compared to individual heating solutions. To estimate the impact of the building density on the competitiveness of the district heating the distances between buildings was increased to three times the base scenario (shown in Fig. 5). This means that the length of the district heating network pipes are three times longer than the base scenario. For each scenario of changed heat demand and building density, the distribution network was dimensioned to match the situation. The base scenario is the scenario with the most dense linear heat density in the analysis and is referred to as network scale 1. This corresponds to the suburban area shown in Fig. 3. The case where the district heating network pipes is three times longer is here referred to as network scale 3. Mathematically speaking, changing the space heating demand and the distances between buildings can be seen as two different ways of changing the linear heat density in the district heating system. A constant DHW demand is assumed in the analysis because it is behavioral dependent and as such it was not considered realistic that the building insulation level has an effect on the DHW demand. For a residence of 130 m2 the DHW consumption is about 3100 kWh/year.
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Fig. 3. Left: The analysed area. Right: Network layout design.
2.7. Buildings The analysis compares the economic tradeoffs between state of the art 4th generation district heating system to state of the art individual heating solutions as the building are moved towards low energy buildings standards. To analyze the impact of stricter building codes, on the competitiveness of district heating the space heating demand was varied from a typical heating demand in a Danish energy renovated 1970 building ð106; 1 kWh=m2 =yearÞ, down to what is expected from buildings fulfilling nearly-zero energy standard ð37; 8 kWh=m2 =yearÞ. In total six different heat demand variations is considered in this paper. They can be seen in Table 5. 2.8. Cost comparison
Fig. 4. Simultaneity factors for space heating (sh) and domestic hot water (dhw) demand as a function of the number of consumers.
To analyze whether district heating can compete with individual heating, the costs are calculated as the average yearly costs in a ^V™s lifetime. As different technologies have different technologya expected lifetimes, the investment costs are annualized. An alternative method would have been to look on a very long time horizon to mask out the impact of reinvestments. The total cost is based on the capital investment, maintenance cost, driving energy cost and unit efficiency. The average yearly price of heat is found by using Formula (1)
Fig. 5. Example of the network scaling of the area, shown to illustrate a change in linear heat density. Source: [16].
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Table 5 Heat demand variations in the analysis. Variation Space heating demand ½kWh=m2 =year
Domestic hot water demand ½kWh=m2 =year
Total demand at 130 m2½kWh=year
Design space heating capacity ½W=m2
1 2 3 4 5 6
24,1 24,1 24,1 24,1 24,1 24,1
13800 12000 10200 8500 6700 4900
30 25 20 15 10 5
82,0 68,3 54,6 41,0 27,3 13,7
[1].
Avg:yearly price of heat ¼ NVj ðkÞ,a1 T;k " # T X ¼ NBj;t ð1 þ kÞt ,a1 T;k
(1)
t¼0
where aT;k , is the capital gains factor or the annuity factor which is defined in Formula (2)
aT;k ¼
1 ð1 þ kÞt k
(2)
NBj;t is the net payment at time t for alternative j. T is the lifetime of the investment and k is the discount rate. NVj is the present value of alternative j as a function of the discount rate. The discount rate considered in this analysis was 4% for both district heating and individual heating technologies. 3. Results 3.1. Impact of design space heating capacity on the capital cost When considering the impact of reduced space heating demand it must be noted that the space heating generally counts less than half of the total capacity demand. The design space heating capacity3 therefore does not have much influence on the main distribution network cost, since the majority of the demand will be caused by the DHW preparation, which is dimensioned to be 32,5 kW for instantaneous DHW preparation and typically 3e6 kW for storage tank solutions. In the analysis it is assumed that all households use instantaneous DHW preparation. For the connection with a space heating demand of 82,0 kWh/m2/year the space heating peak capacity demand is 3,9 kW, while it is 0,65 kW for a connection with a space heating demand of 13,7 kWh/m2/year. As the differences in the required capacity does not change that much there is only a limited cost saving to find for individual heating units and no cost savings in the district heating substations and the service pipeline. 3.2. District heating main distribution pipeline There is generally a limited cost savings achieved in the distribution network as the capacity demand reduces. This is because a) a large part of the investment cost is independent or loosely connected to the capacity, for example planning cost, permit costs and excavation cost, and b) pipes come in discrete sizes, meaning even if the capacity drops to some extent it does not necessarily mean that smaller pipes can be used. The impact of the reduced heat demand on the main distribution pipe network cost when going from a
3 The design space heating capacity is the buildings dimensioning heat loss at 12+C.
Fig. 6. Impact of the space heating demand ðW=m2 Þ on the main distribution network cost.ðMVÞ
design space heating demand of 30 W/m2 to 5 W/m2 is shown in Fig. 6.
3.3. District heating generation units The main benefits of district heating compared to individual heating solutions is realized at the heat source. First of all the heat source design capacity will be much lower than the sum of the capacities from individual heating units due to simultaneity of usage, secondly economy of scale provides better possibilities of realizing low price for the driving energy and thirdly there will be much higher freedom of choosing the appropriate heat source. When dimensioning the heat source in this study, simultaneity was only applied on the DHW demand. By applying simultaneity factors on the heating demand, slight design distribution capacity savings could be achieved, it will although have minimal impact on the cost of the distribution grid, as Fig. 6 indicates. The applied aggregated DHW profile used in the study is shown in Fig. 7. The space heating demand was determined based on the outdoor temperature according to the standardized Copenhagen weather profile [23], no simultaneity or demand shifting due to building thermal mass was considered. Similar to Fig. 6 the impact of the design space heating capacity on the cost of the heat source can be seen in Fig. 8. The costs include both the electrical compression heat pump, electric boiler and storage tank.
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Fig. 7. Daily DHW profile (percentage of daily use) applied in the study to estimate the impact of the DHW on the heat source capacity requirement.
Fig. 9. Comparison of the price of heat between newly established district heating (network scale 1) using an electric heat pump and different types of individual heating. The heat demand is 13800 kWh/year. The network scale of 1 for district heating refers to the most dense linear heat density (in this study) explained in Section 2.6.
Fig. 8. Impact of the space heating demand ðW=m2 Þ on the heat production facility investment cost.ðMVÞ
3.4. Economical comparison between district heating and individual heating solutions Fig. 9 shows the yearly costs for providing space heating and domestic hot water to a household with a total heat demand of 13800 kWh/year. The district heating is produced on an electrical compression heat pump. The figure shows that under the assumptions in this paper, the newly established district heating system is the cheapest form of heating for a household. The second cheapest alternative is an individual natural gas boiler, which is around 430V more expensive than district heating, per year. After the individual natural gas boiler comes the individual air/water heat pump and individual wood pellet boiler, which is respectively
Fig. 10. Comparison of the price of heat between newly established district heating (network scale 1) using an electric heat pump and different types of individual heating. The heat demand is 4900 kWh/year (near-zero energy building).
790V and 805V more expensive than district heating, per year. Fig. 10 shows the yearly costs for providing space heating and domestic hot water to a household with a total heat demand of
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4900 kWh/year. The rest of the assumptions are the same as in Fig. 9. The results show that a newly established district heating system is also the cheapest form of heating for low energy building. District heating is around 207V cheaper than electrical heating, which is the cheapest alternative to district heating. The individual natural gas boiler is around 40V more expensive per year compared to electrical heating. This is because the space heating in this scenario is so low that the investment cost is a very significant factor. Individual electrical heating has much lower investment costs than natural gas. So much that it offsets the relatively high variable costs of electrical heating.
3.5. Impact of increased distances between connected buildings It is well known that district heating is a good solution for urban areas. Generally, it can be said that the more densely built and heat intense the buildings are, the more cost competitive district heating becomes. In this respect it is of interest to get an idea on a) how the building density will impact the competitiveness and b) what the influence of reduced building heat demand will have on the competitiveness. Generally, this is addressed through the linear heat density, which is the yearly heat delivery per pipe meter per year. By doing a quick estimation of the linear heat density of an area it is possible to get a first impression of the feasibility of district
heating compared to alternative solutions, see Ref. [21] for an example of a method to estimate the linear heat density of an area. Fig. 11 gives an idea on how linear heat density will impact the cost competitiveness of district heating versus its cheapest alternatives in a Danish context. Fig. 11 shows that as the space heating demand decreases, the distance between the yearly heating cost of district heating and the individual heating solutions decrease on an absolute level. The cheapest alternative is a natural gas boiler for 30 W/m2 to 10 W/m2 and electrical panel/radiators for 5 W/m2. District heating is a competitive solution for all the cases where the network scale is between 1 and 2. As the heating demand moves toward the demand of a low energy building and the distance between buildings increase, then the yearly heating cost of district heating gets closer to the yearly heating cost of the individual heating solutions. This is natural since increasing the distance between buildings will increase the heat loss in the district heating system and greatly increase the investment cost, and in the case of low energy buildings there are less energy units to split the costs on. For a network scale of 2,5, district heating is not able to compete on price alone for the case where a household only has a heat demand of 4900 kWh/year. If the network scale is increased to 3, this will be the case for the four cases with a heat demand of 10 200 kWh/year or less. There are a number of factors that will impact the competitiveness, for example system operating temperatures, pipe selection, soil composition, applied heat source, fuel costs and taxes. Due to the many factors that impact the cost of district heating systems, a proper feasibility study is always needed to determine the actual situation for a given area. 3.6. Impact of percentage of connected costumers
Fig. 11. Yearly heating cost for the six different heat demand variations combined with different district heating network scales, compared to the cheapest individual alternative for each heat demand variation. The heating cost of district heating is represented by the dots (dashed lines), while the cheapest individual alternatives is represented by the solid lines. In the figure the dots should only be compared to the solid lines of the same color. As an example, all the green dots represent yearly heating costs for a building with a heating demand of 5 W/m2, but the linear heat density is varied from dense (network scale of 1) to sparse (network scale of 3). The green dots should only be compared to the solid green line, showing the cheapest individual alternative (in this case electrical panel/radiators). If a dot is below the solid line of the same color, district heating is cheaper than the cheapest individual heating solution. If a dot is above the solid line of the same color, an individual heating solution is cheaper than establishing a district heating system. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
The results in this paper has so far been based on the assumption that the district heating system is dimensioned to supply the whole heat demand in the considered area and that all the household in the area will be connected to the district heating system. In the following it will still be assumed that the district heating system is dimensioned such that it can supply the whole heat demand in the considered area, but it is investigated what will happen to the competitiveness of the district heating system if not all costumers choose to connect to the district heating system. This means that fewer costumers will have to carry the investment costs and heat loss of the full system. For a heat demand variation the investment costs will in this context be identical for all percentages of connected costumers, as will the heat losses in the main pipes. Only the heat losses in the service pipes will be reduced with the percentage of connected costumers. As this is an illustrative sensitivity analysis it is assumed that the flow in the system is sufficient for all percentages of connected costumers (meaning that there is not placed e.g. a shunt in the system to increase the flow rate). The two dots in Fig. 12 are also found in Fig. 11 for the case with a network scale of 2. A network scale of 2 is applied in Fig. 12 because it can be seen in Fig. 11 that for this network scale and a heat demand of 30 W/m2 (13 800 kWh/year), district heating is very competitive compared to the cheapest individual alternative. For this network scale and a heat demand of 5 W/m2 (4900 kWh/year), district heating is only just competitive compared to the cheapest individual alternative. This means that district heating for this network scale ranges from very competitive to just competitive, when varying the heat demand, making it an interesting case on which to analyze the impact of connected customers. The figure shows that as the percentage of connected customers decrease, the less competitive the district heating system becomes.
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Fig. 12. Yearly heating cost for a heat demand of 13 800 kWh/year and 4900 kWh/year with a network scale of 2. The percentage of connected costumers to the district heating system is varied and compared to the cheapest individual alternative for the heat demand variation. As in Fig. 11 the heating cost of district heating is represented by the dot/x's (dashed lines), while the cheapest individual alternatives is represented by the solid lines. In the figure the dot/x's should only be compared to the solid lines of the same color. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
This is natural since district heating is a collective system which benefits from more customers. For the case with a heat demand of 4900 kWh/year, the district heating system is only marginally cheaper than the individual heating alternative. This means that when the percentage of connected customers fall below 90e95% the district heating system is not competitive. For the case with a heat demand of 13 800 kWh/year, the district heating system is very competitive compared to the individual heating alternative. In this case the percentage of connected customers can fall below 80% and still be competitive compared to the indvidiual heating alternative. For a network scale of 1 the competitiveness of district heating is higher and less sensitive to the percentage of connected customers. In general it can be observed that the higher the linear heat density is in an area, fewer customers are required for district heating to be competitive when comparing to an individual heating alternative. Although a district heating system can be competitive with fewer connected customers, more customers will descrease the costs for the whole system. An alternative approach would be to dimension the system to a fewer number of customers at first. This would however result in a more expensive system since adding more customers to the system will result in added investment costs. The costs of a system built in two steps will be significantly higher than a system built in one step.
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for district heating compared to an individual natural gas boiler. Compared to an individual biomass boiler and an individual air-towater heat pump, district heating is approximately 750V cheaper. In percentages, the annual cost of district heating is approximately 18% lower than an individual natural gas boiler and approximately 30% cheaper than an individual biomass boiler and an individual air-to-water heat pump. In a scenario where the buildings meet the energy limit of the Danish building regulations for 2015 (BR15), a new district heating system is the most cost-effective source of heating when compared to individual heating solutions. For a 130 m2 building this is equivalent to a heat demand of 4900 kWh/year. In this scenario the yearly price of heating is approximately 200 V cheaper than individual electric heating (16%) and 250V cheaper than an individual natural gas boiler (19%). Compared to an individual air-to-water heat pump, the yearly price of heating for a new district heating system is approximately 875V cheaper (45%). These results are for a dense area. In areas with both low heat demand and low building density, district heating is not the most competitive heating solution. As this analysis was performed under Danish conditions it was of particular interest to investigate the impact of taxes on the results. The results show that even if energy taxes are lowered or completely removed the analysis show that a new district heating system is the most cost-effective source of heating. The economics of scale of the heat source and accessibility to fuels with lower costs will outweigh the added investment in the distribution grid and the unavoidable distribution heat losses. The analysis shows that the percentage of connected customers in an area is an important factor for the district heating system. For a district heating system with a low linear heat density (low energy buildings and a large distribution network), close to full participation from the possible customers is required for the district heating system to be competitive. For systems with high linear heat densities (larger heat demand from buildings, denser distribution network or both) fewer customers are required for the district heating system to be competitive. This result is consistent with dense district heating systems being more competitive than a less dense district heating systems, all else equal. The overall outcome of this study is that a new district heating system is competitive compared to individual heating solutions. Both for the existing building stock as well as for the future low energy building stock. There is even room for considerable uncertainties regarding the costs of establishing the district heating network. In addition to being more cost efficient than individual heating solutions, it opens up for a variety of options to reduce greenhouse gas emissions by making a collective conversion to a fuel source emitting less green house gasses. Outside Denmark, it is likely that the heat in a district heating system will not be produced with the same technologies as in Denmark. The final result depends on fuel prices, tariffs and taxes and as these vary from country to country the results may change. However, the advantages of district heating (high fuel efficiency, lower heat production capacity requirement and cheaper fuels) will most often make district heating cost efficient. This is especially the case in densely populated areas where the relative heat loss will be low.
4. Conclusion CRediT authorship contribution statement In a scenario where the buildings correspond to a typical energy renovated Danish building from 1970, a new district heating system is the most cost-effective source of heating. For a 130 m2 building this is equivalent to a heat demand of 13800 kWh/year. In this scenario the yearly price of heating is approximately 400V cheaper
C.H. Hansen: Conceptualization, Methodology, Formal analysis, Writing - original draft, Visualization. O. Gudmundsson: Conceptualization, Methodology, Formal analysis, Writing - original draft. N. Detlefsen: Conceptualization, Supervision.
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