Primary energy implications of end-use energy efficiency measures in district heated buildings

Primary energy implications of end-use energy efficiency measures in district heated buildings

Energy and Buildings 43 (2011) 38–48 Contents lists available at ScienceDirect Energy and Buildings journal homepage: www.elsevier.com/locate/enbuil...

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Energy and Buildings 43 (2011) 38–48

Contents lists available at ScienceDirect

Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild

Primary energy implications of end-use energy efficiency measures in district heated buildings L. Gustavsson a,b , A. Dodoo b,∗ , N.L. Truong b , I. Danielski b a b

Linnaeus University, 35195 Växjö, Sweden Mid Sweden University, 83125 Östersund, Sweden

a r t i c l e

i n f o

Article history: Received 18 February 2010 Received in revised form 22 June 2010 Accepted 26 July 2010 Keywords: CHP plant District heat production Energy efficiency Environmental taxations Primary energy Buildings

a b s t r a c t In this study we explore the effects of end-use energy efficiency measures on different district heat production systems with combined heat and power (CHP) plants for base load production and heat-only boilers for peak and medium load productions. We model four minimum cost district heat production systems based on four environmental taxation scenarios, plus a reference district heat system used in Östersund, Sweden. We analyze the primary energy use and the cost of district heat production for each system. We then analyze the primary energy implications of end-use energy efficiency measures applied to a case-study apartment building, taking into account the reduced district heat demand, reduced cogenerated electricity and increased electricity use due to ventilation heat recovery. We find that district heat production cost in optimally-designed production systems is not sensitive to environmental taxation. The primary energy savings of end-use energy efficiency measures depend on the characteristics of the district heat production system and the type of end-use energy efficiency measures. Energy efficiency measures that reduce more of peak load than base load production give higher primary energy savings, because the primary energy efficiency is higher for CHP plants than for boilers. This study shows the importance of analyzing both the demand and supply sides as well as their interaction in order to minimize the primary energy use of district heated buildings. © 2010 Elsevier B.V. All rights reserved.

1. Introduction The energy use in buildings accounts for a large share of the total primary energy use and carbon dioxide (CO2 ) emissions in many countries [1]. Large potential exists to improve energy efficiency in buildings and thereby reduce primary energy use and CO2 emissions [2]. Improved insulation and airtightness of building envelope, energy-efficient windows, heat recovery from exhaust ventilation air and efficient appliances can improve the end-use energy efficiency of buildings. Improved energy efficiency in buildings is an important part of the climate and energy policies of Sweden and the rest of the European Union [3,4]. The European Union requires Member States to apply minimum energy efficiency standards for new buildings and for large existing buildings that undergo major renovation [5]. Sweden has set targets to reduce the final energy use per heated building area by 20% and 50% by 2020 and 2050, respectively, using 1995 as the reference [6]. The Swedish building energy regulations have been revised three times

∗ Corresponding author. Tel.: +46 63 165383; fax: +46 63 165500. E-mail address: [email protected] (A. Dodoo). 0378-7788/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2010.07.029

between 2006 and 2009 to improve end-use energy efficiency of buildings. End-use energy efficiency measures may reduce consumer costs, primary energy use and environmental impacts associated with energy use, but may also reduce the use of existing energy supply capacities and revenues for the energy utilities. Consequently, reduced energy use in buildings may be a concern for an energy utility where there is no capacity constraint, particularly for district heating utilities as such systems are capital intensive [7]. District heating accounts for 50% of the Swedish space and tap water heating [8]. Palm [9] found that district heating utilities do not find it profitable to promote energy efficiency as it reduces revenue more than cost for the utility. Gustafsson and Karlsson [10] observed that end-use energy efficiency in district heated buildings may reduce the potential for electricity cogeneration. Various studies (e.g. [7,11–17]) have analyzed the interactions between end-use energy efficiency measures and district heating systems. Many of these focus on trade-offs between the end-use measures and avoided cost in district heat production. Gustafsson [11] explored the effect of end-use energy efficiency measures on energy supply systems and found the measures to be less profitable for buildings with district heating based on CHP production. Gustavsson [7,12] analyzed the potential space and tap water heat savings in district heated buildings and explored the effect of this

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on district heating system designs and costs. He found the cost and energy saving potential to strongly depend on the specific building and district heating system. Gilijamse and Boonstra [13] compared the cost-effectiveness of the use of CHP supply systems and final heat savings measures for new buildings. They found the combination of CHP supply systems and final heat savings measures to be less cost-effective compared to when either measure is applied separately. In most studies the interactions between the end-use measures and district heating systems have been studied using simulation models. Rolfsman [14] proposed a linear programming model to explore the effect of end-use measures on district heating systems. Nässén and Holmberg [15] examined the costeffectiveness of end-use measures in district heated buildings using an optimization model. Joelsson and Gustavsson [16] and Gustavsson and Joelsson [17] analyzed the primary energy savings in district heated buildings, including fuel inputs at each stage of the energy chain based on annual average final energy demand and annual average district heat production. However, the yearly profiles of final energy savings and district heat production influence the primary energy savings of energy efficiency measures in district heated buildings. The overall effect of end-use energy efficiency measures on a district heating system can be complex, depending on the scale and period of the intervention and the energy use profile of buildings [7]. End-use energy efficiency measures may alter buildings’ energy use profiles, and consequently the profile of the heat load duration curve of a district heating system. This may influence the primary energy use and cost of district heat production. Studies that have considered these dynamics of end-use energy efficiency measures and district heat production in detail, focusing on primary energy savings, are lacking. In this study we analyze the potential to reduce final heat demand in a district heated building by end-use energy efficiency measures, and explore the effects of the reduced heat demand on

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different district heat production systems. We focus on primary energy savings and consider how the final heat savings influences district heat production. The end-use energy efficiency measures we consider are installation of improved water taps, windows and doors, increased insulation in attic and exterior walls, and installation of a heat recovery unit in the ventilation system. We consider five different systems. The reference district heat production system is the existing district heat production in Östersund, Sweden. The four other district heat production systems are based on four environmental taxation scenarios. 2. Methods Our approach has three parts: (i) modeling the final heat savings in the building when implementing the end-use energy efficiency measures; (ii) exploring the effects of different environmental taxation regimes on district heat production systems; and (iii) analyzing the interactions between the demand and supply sides. Fig. 1 summarizes our approach. 2.1. Demand side 2.1.1. Case-study building Our case-study building is a multi-storey wood-frame apartment building constructed around 1995 in Sweden. It has 4 floors and 16 apartments, and a total heated floor area of 1190 m2 . The roof consists of two layers of asphalt-impregnated felt, wood panels, 40 cm mineral wool between wooden roof trusses, polythene foils and gypsum boards, giving an overall U-value of 0.13 W/m2 K. The windows are double-glazed and have a U-value of 1.9 W/m2 K. The external doors have a U-value of 1.19 W/m2 K and consist of framing with doubleglazed window panels. The external walls have a U-value of 0.20 W/m2 K and consist of three layers: 5 cm plaster-compatible

Fig. 1. Schematic diagram of the analysis. The broken lines represent optimization boundaries.

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mineral wool panels, 12 cm thick timber studs with mineral wool between the studs, and a wiring and plumbing installation layer consisting of 7 cm thick timber studs and mineral wool. Two-thirds of the facade is plastered with stucco, while the facades of the stairwells and the window surrounds consist of wood paneling. The ground floor consists of 1.5 cm oak boarding on 16 cm concrete slab laid on 7 cm expanded polystyrene and 15 cm macadam, resulting in a U-value of 0.23 W/m2 K. 2.1.2. Potential energy savings We model the energy balance of the building before and after applying each of the end-use energy efficiency measures, to estimate the final energy savings. We use simplified assumptions for the measures applied to the building. For the exterior walls, we assume that 25 cm of additional mineral wool insulation is added to the exterior facade of the building, covered by new stucco and plasterboard cladding supported by wooden studs spaced 60 cm apart. This leads to exterior wall U-value of 0.11 W/m2 K. We assume that the original roof overhang is sufficient to cover the thicker walls. We assume that the original double-glazed windows are replaced by triple-glazed units with low emissivity coating and filled with krypton gas, which corresponds to a U-value of 0.85 W/m2 K. We similarly assume that the original double-glazed windows in the doors are replaced by triple-glazed units giving an overall U-value of 0.85 W/m2 K. We assume that an additional 10 cm mineral wool insulation can be installed in the existing attic space, resulting in a U-value of 0.11 W/m2 K. We assume the existing mechanical ventilation system for exhaust air is complemented with a heat recovery unit of 85% efficiency, and the ventilation ducts for incoming air can be fitted in the buildings [18]. We assume that the building’s designed airtightness of 0.8 l/m2 is maintained. Based on data from the Swedish Energy Agency [19], we assume that end-use energy for tap water heating is reduced by 40% by changing from conventional to efficient water taps. The annual final energy use of the building with and without energy efficiency measures are simulated with the VIP+ program [20]. The VIP+ is a dynamic energy balance program that models the hourly final energy use for space and tap water heating, ventilating, and household and facility electricity of buildings. The program has been validated by the International Energy Agency building energy simulation test and diagnostic method (IEA BESTEST). The program calculates the energy balance considering a building’s thermal characteristics, orientation, heating and ventilation systems, indoor temperature and operation schedule besides outdoor temperature. We use the climate data for Östersund, Sweden and assume an indoor temperature of 22 ◦ C in the living areas and 18 ◦ C in the common areas. 2.2. Supply side 2.2.1. Reference district heat production system The reference district heat production system, serving Östersund and surrounding areas, consists of a CHP plant with a flue gas condenser and two heat-only boilers (HOB). The heat and electricity capacities of the CHP plant are 80 MWheat and 40 MWelec , respectively. The heat production of the CHP plant can be increased by 30 MWheat when the flue gas condenser is used. The capacity of each of the heat boilers is 25 MWheat . An accumulator tank of 26,000 m3 capacity is connected to the production system to increase the efficiency of heat and electricity production. The CHP plant and the boilers are fuelled by peat (∼10%) and biomass residues (∼90%) such as bark, sawdust, logging residues and recovered wood. During the 12-month period from 1st May 2008 to 30th April 2009, the output of the production system was 210 GWh electricity and 612 GWh heat. Fig. 2 shows the measured heat load of the production system during this period, arranged in descending order.

Fig. 2. The measured heat load duration curve of the reference heat production for 2008/2009 arranged in descending order.

2.2.2. Environmental taxation scenarios To explore the primary energy savings under different environmental constraints, we use four environmental taxations scenarios that influence the district heat production. The design of the district heat production under the different taxation scenarios is based on the heat load duration curve of the reference production (Fig. 2), and the production units which give the lowest heat production cost for each scenario. The scenarios are: (i) the No tax scenario with the year 2008 Swedish price of fuels with zero taxes; (ii) the Swedish tax scenario with the year 2008 Swedish prices and taxes on fuels, comprising of a carbon tax of D 386/t CO2 for emissions related to non-electricity production, an energy tax that varies for different fossil fuels used for non-electricity production, and an average green electricity certificate (GEC) benefit of D 12.5/MWhe of produced green electricity [21]; (iii) the Social cost-550 ppm scenario with the year 2008 fossil fuel prices excluding taxes, plus a carbon damage cost of D 20.55/t CO2 ($30/t CO2 ) corresponding to the 550 ppm emission scenario by Stern [22]; (iv) the Social cost-BAU scenario with the year 2008 fossil fuel prices excluding taxes, plus a carbon damage cost of D 58.23/t CO2 ($85/t CO2 ) corresponding to the business as usual (BAU) emission scenario by Stern [22]. The costs of the fuels under the various scenarios are shown in Table 1, based on data from the Swedish Energy Agency [21]. 2.2.3. Modeling minimum cost district heat production systems We select the district heat production units for each taxation scenario based on the utilization time and minimum district heat cost. We consider the fuels and technologies shown in Table 2. The technologies consist of CHP plants and HOB. The CHP plants are based on biomass steam turbine (BST); biomass integrated gasification combined-cycle (BIGCC); coal-based steam turbine (CST); and natural gas combined-cycle (NGCC) technologies. The calculation of the heat production cost is based on the following equation from Gustavsson [12]: Cheat =

Cfuel CRF × Ccap + Cfom Cvom + − Velec × ˛ + heat heat t

where Cheat is the heat production cost (D /MWheat ), Cvom is the variable operation and maintenance (O&M) costs of the plant (D /MWhfuel ), heat is the efficiency of heat production of the plant, Cfuel is the fuel cost of the plant (D /MWhfuel ), Velec is the value of produced electricity (D /MWhelec ), ˛ is the electricity-to-heat ratio of the plant, CRF is the capital recovery factor of the plant, Ccap is the capital cost of the plant (D /MWheat ), Cfom is the annual fixed O&M costs of the plant (D /MWheat ), and t is the utilization time of the plant.

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Table 1 Fuel costs under the various scenarios (D 2007 /MWh). Fuel type

Scenarios

Fuel oil Diesel oil Coal Forest fuel Natural gas Wood powderb a b

No tax

Swedish tax

Social cost-550 ppm

Social cost-BAU

29.7 52.0 8.0 16.3 33.7 26.1

62.9 90.5 46.3 (17.4)a 16.3 37.6 (37.9)a 26.1

36.1 58.3 15.5 16.5 37.9 26.4

47.7 70.0 29.3 16.8 45.6 26.9

CHP plant. Estimated based on forest fuel cost.

For district heating systems with CHP production, the value of the electricity produced influences the cost of heat production. The production cost of heat may be determined by subtracting the value of the cogenerated electricity from the total production cost of the CHP plant [23,24]. We calculate the value of cogenerated electricity using the subtraction method, where we consider the cogenerated electricity as by-product and assume its value to be equivalent to the cost of electricity produced with a reference condensing power plant [24]. Coal-fired condensing plants are the dominant marginal electricity production technology in the Nordic region today [25]. However, this may change in the future due to factors including investments, greenhouse gas reduction policies, strategic and security reasons [26]. In this study we calculate the cost of the cogenerated electricity as the lowest production cost from the condensing power plants (Table 2) for each taxation scenario. We assume the same technologies as for cogeneration but also add carbon capture and storage (CCS) for the CST technology. We calculate the cost of the electricity using the data in Table 2 and the equation:

Celec =

Cfuel CRF × Ccap + Cfom Cvom + + elec elec t

where Celec is the production cost of electricity (D /MWhelec ), Cvom is the variable O&M costs of the plant (D /MWhfuel ), elec is the efficiency of electricity production, Cfuel is the fuel cost of the plant (D /MWhfuel ), CRF is the capital recovery factor of the plant, Ccap capital cost of the power plant (D /Mwelec ), Cfom is the annual fixed O&M costs of the plant (D /MWelec ) and t is the utilization time of the plant (hours/year).

We assume a 6% discount rate, 25-year economic plant life and 7200 maximum plant operating hours per year. We use exchange rates of SEK/D = 9.62 and SEK/$ = 6.59, based on the average rates for 2008. We take a simplified approach and assume that the costs associated with start-up of the production units are minor, and thus are not considered in our calculations. We calculate the primary energy use and the heat and electricity generated by the minimum cost district heat production systems based on the operation schedules, production units and fuels. We consider fuel cycle energy inputs in our calculations. We assume distribution losses of 7% to the building for both electricity and district heat. 2.3. Demand and supply side interactions We establish the yearly final heat demand profile of the building with and without energy efficiency measures, to determine the profile of energy savings based on the hourly simulation of the heat demand. Next we match the energy savings profile to the district heat production units to calculate the reduced heat production for each production unit. For periods when the marginal plant is the CHP plant, reduced heat production will result in reduced electricity cogeneration. For heat recovery of ventilation air, additional electricity is used. The reduced cogenerated electricity and increased ventilation electricity are covered by the reference condensing power plant production as defined in the various environmental taxations scenarios. Finally, we calculate the primary energy savings due to the enduse energy efficiency measures as the primary energy savings in the district heat production minus the primary energy used in the condensing power plants to cover the reduced cogenerated elec-

Table 2 Investment cost, fixed and variable costs and conversion efficiency of different technologies. The data is based on lower heating values (LHV). Technology

Capacity (MWheat )

Investment cost (D /kWheat )

Fixed O&M cost (D /kWheat )

Variable O&M cost (D /MWhfuel )

Efficiency (%) Heat

HOB Biomassa Wood powderb Oila Coalc CHP plants BSTc BIGCCa NGCCa CSTc Condensing power plant CSTc CST with CCSc NGCCc BSTd BIGCCa a b c d

– – – –

646 430 300 690

80 80 80 80 (MWelect ) 400 400 400 400 100

12.92 8.6 4.5 17.3

1.95 1.95 0.65 2.59

1150 1700 950 1350

17.3 42.5 23.8 33.8

2.6 3.1 1.0 3.1

(D /kWelec ) 1200 1900 620 1200 1680

(D /kWelec ) 24.9 74.8 18.7 20 42

(D /MWhfuel ) 3.12 5.2 1.04 2.39 3.12

CEC [35] with adjustment for the difference in investment cost between Hansson et al. [36] and CEC [35]. Swedish Wood Fuel Association and Swedish Energy Agency [37], with 170% adjustment. Hansson et al. [36]. Estimated from CEC [35].

Electricity

110 95 90 90

– – – –

80 47 43 59

30 43 46 30

– – – – –

(%) 47 37 58 45 47

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Table 3 Annual final operation energy use of cumulatively applied energy efficiency measures. End-use energy (kWh/m2 year)

Applied end-use energy efficiency measures

Initial + Improved taps + Improved windows & doors + Additional roof insulation + Additional external walls insulation + Ventilation heat recovery

Space heating

Tap water heating

Ventilation electricity

Household/facility electricity

Total

94.2 94.2 69.6 66.6 60.9 25.2

25.0 15.0 15.0 15.0 15.0 15.0

2.3 2.3 2.3 2.3 2.3 12.5

44.8 44.8 44.8 44.8 44.8 44.8

166.3 156.3 131.7 128.7 123.0 97.5

Fig. 3. Annual final heat use profiles of the building when applying the energy efficiency measures cumulatively.

tricity and increased ventilation electricity. This can be expressed as: Eprimary =

n 

Eheat.i

i=1

 1 heat.i



˛i elec





Eelec elec

where Eprimary is the net primary energy savings, n is the number of production units in the district heating system, Eheat.i is the reduced district heat production energy of the production unit i in the plant, Eelec is the increased electricity use, heat.i is the efficiency of heat production of the unit i in the plant, ˛i is the electricity-to-heat ratio of the production unit i in the plant, and elec is the efficiency of electricity production of the reference condensing power plant. 3. Results 3.1. Demand side The annual final energy use for operating the building before and after applying the end-use energy efficiency measures is shown in Table 3. In Fig. 3, the annual final heat use profiles for the building when applying the energy efficiency measures are shown. The effects of previous measures are included so the cumulative effects of applying the energy efficiency measures are shown. In total, the energy efficiency measures decrease the annual final heat use by 79 kWh/m2 or 66%, but the ventilation electricity use increases by 10 kWh/m2 due to the ventilation heat recovery. However, the electricity use of the ventilation system is based on the default values given by the VIP+. The electricity use for ventilation heat recovery is

Fig. 4. District heat production cost of different production units under the No tax scenario, and operation periods of the units with the minimum heat production cost.

10 kWh/m2 in VIP+ while Tommerup and Svendsen [27] reported this to be typically about 7 kWh/m2 and suggested this might be reduced to 3 kWh/m2 with more efficient systems. Hence, VIP+ may have slightly overestimated the electricity use for ventilation heat recovery. Further, the electricity use for ventilation without heat recovery is slightly underestimated as VIP+ uses 2.3 kWh/m2 while typically reported value is 4 kWh/m2 [28]. Ventilation heat recovery gives the biggest single decrease in the final heat use, followed by energy-efficient windows and doors. 3.2. Supply side Table 4 shows the calculated cost of electricity from the condensing power plants under the various taxation scenarios. The

Table 4 The cost of electricity production for the various taxation scenarios (D /MWhelec ). Technology

No tax

Swedish tax

Social cost-550 ppm

Social cost-BAU

CST CST with CCS NGCC BST BIGCC

40.2 66.7 69.2 57.4 65.4

44.6 66.7 76.5 44.9 52.9

56.1 68.9 76.4 57.8 65.8

85.4 72.9 89.7 58.6 66.5

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Table 5 Production units characteristics of the reference and minimum cost district heat productions systems. Production unit of district heat Reference CHP–BST Boiler-biomass Boiler-biomass Minimum cost productions No tax CHP–CST Boiler-coal Boiler-oil Swedish tax CHP–BST Boiler-biomass Boiler-oil Social cost-550 ppm CHP–BST Boiler-biomass Boiler-oil Social cost-BAU CHP–BST Boiler-biomass Boiler-oil

Capacity (MWheat )

Operating time (h/year)

110 25 25

7200 2568 768

62 34 64

Utilization factor (%)

Heat generation (GWh)

Electricity generation (GWh)

Primary energy use (GWh)

58.1% 21.5% 2.3%

560 47 5

210 – –

725 44 5

7200 6624 1944

76.9 52.5 6.8

418 156 38

212 – –

793 159 47

84 36 40

7200 4608 672

69.2 29.8 2.6

509 94 9

191 – –

658 88 11

79 28 53

7200 5160 1464

71.2 39.8 4.8

492 98 22

185 – –

637 92 27

82 33 45

7200 4776 1032

70.0 33.4 3.3

503 96 13

188 – –

650 91 16

Table 6 Primary energy used by different production units for heating the case-study building without energy efficiency measures, and cogenerated electricity. District heat production

Reference CHP–BST Boiler-biomass Boiler-biomass Total No tax CHP–CST Boiler-coal Boiler-oil Total Swedish tax CHP–BST Boiler-biomass Boiler-oil Total Social cost-550 ppm CHP–BST Boiler-biomass Boiler-oil Total Social cost-BAU CHP–BST Boiler-biomass Boiler-oil Total

Primary energy use of case-study building

Cogenerated electricity (MWh)

MWh

%

181.9 9.6 1.1 192.6

94.4 5.0 0.6 100

52.7 – – 52.7

187.9 50.8 14.9 253.6

74.1 20.0 5.9 100

50.3 – – 50.3

161.6 22.6 3.7 188.0

86.0 12.0 2.0 100

46.8 – – 46.8

155.3 23.6 8.4 187.3

82.9 12.6 4.5 100

45.0 – – 45.0

159.2 23.3 5.2 187.6

84.8 12.4 2.8 100

46.1 – – –

numbers in bold show the lowest production cost for each taxation scenario, and hence become the reference condensing power plant for each scenario. CST emerges as the reference condensing power plant for electricity production in all scenarios except for the Social cost-BAU scenario. For the Social cost-BAU scenario, BST

emerges as the reference condensing power plant. However, the cost difference between BST and CST is small for the Swedish tax and Social cost-BAU scenarios. The cost of district heat production units under the No tax scenario as a function of the utilization time is shown in Fig. 4. The units

Table 7 Effects of cumulatively applied energy efficiency measures on heat demand, electricity use and cogenerated electricity (MWh/year). Applied end-use energy efficiency measures

Reduced heat demand

Increased electricity use

Improved taps + Improved windows & doors + Additional roof insulation + Additional external walls insulation + Ventilation heat recovery

11.9 41.2 44.8 51.7 94.1

– – – – 13

Reduced cogenerated electricity Reference

No tax

Swedish tax

Social cost-550 ppm

Social cost-BAU

3.2 11.4 12.3 14.3 25.8

1.5 3.1 3.2 3.5 4.3

2.1 6.3 6.7 7.8 12.3

1.8 5.1 5.4 6.2 9.3

2.0 6.0 6.3 7.3 11.4

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Fig. 6. Heat production costs of the reference and minimum cost district heat production systems under different taxation scenarios.

Fig. 5. (a) Heat production cost of different production units under the Social costBAU scenario, and operation periods of the units with the minimum heat production cost, and units applied to the heat load duration curve. (b) Production units and operation periods for the units with minimum heat production cost under the Social cost-BAU scenario.

with the lowest heat production cost are applied to the heat load profile to minimize the overall heat production cost. That results in a CHP–CST plant of 62 MWheat with utilization factor (Uf ) of 76.9% for base load, a coal boiler of 34 MWheat with Uf of 52.5% for medium load and a light fuel oil boiler of 64 MWheat with Uf of 6.8% for peak load. The base load unit is shut down after 300 days (7200 h) and the heat demand has to be met by the medium load unit. The cost of district heat production units as a function of the utilization time under the Social cost-BAU scenario is shown in Fig. 5a. The figure shows that five different units, including light fuel oil boiler for the peak load, wood powder boiler and biomass boiler for the medium load, and CHP–BST and CHP–BIGCC for base load will give the minimum heat production cost. However, the CHP–BIGCC technology is still at the development and demonstration stage and is not yet commercialized [29–31]. Thus a more feasible unit for the base load production is CHP–BST technology. Therefore we select

the CHP–BST plant for the base load production. In a sensitivity analysis we explore the effect if CHP–BIGCC plant is used. During periods when the base load unit is shut down (after 300 days) heat demand has to be met by the medium load unit, increasing the utilization time for the unit. If this utilization time is also considered, the wood powder boiler becomes less competitive than the biomass boiler for the medium load production. Therefore a combination of CHP–BST plant for base load, biomass boiler for medium load and light fuel oil boiler for peak load gives the minimum heat production cost for the Social cost-BAU scenario (Fig. 5b). Similar analyzes for the Swedish tax and Social cost-550 ppm scenarios give the selections and capacities of the production units shown in Table 5. Table 5 also shows the annual primary energy use, heat and electricity productions for the reference and the minimum cost district heat production systems. Fig. 6 shows the annual average district heat production cost for the reference system and minimum cost district heat production systems under the different taxation scenarios. The reference system gives higher heat production cost compared to the other systems under all the taxation scenarios. The variation of heat production cost for the minimum cost district heat production systems is small as different technologies, fuels and electricity production systems are used. Hence the minimum district heat production cost is very robust for different taxation scenarios. The variation in the heat production cost for the reference system is more significant as the production is based on the same technology and fuel. Fig. 7 shows the primary energy use to produce the annual amount of district heat. There is no variation in the primary energy use for the reference production except due to variation in credit electricity production. For all the taxation scenarios the credit electricity production system is the CST, except the Social cost-BAU

Fig. 7. Primary energy use for heat production by the reference and minimum cost district heat production systems.

L. Gustavsson et al. / Energy and Buildings 43 (2011) 38–48

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Table 8 Primary energy balance (MWh/year) of cumulatively applied energy efficiency measures. Description Reference Reduced district heat production CHP–BST Boiler-biomass Boiler-biomass Increased electricity use Reduced cogenerated electricitya Primary energy savings No tax Reduced district heat production CHP–CST Boiler-coal Boiler-oil Increased electricity use Reduced cogenerated electricitya Primary energy savings Swedish tax Reduced district heat production CHP–BST Boiler-biomass Boiler-oil Increased electricity use Reduced cogenerated electricitya Primary energy savings Social cost-550 ppm Reduced district heat production CHP–BST Boiler-biomass Boiler-oil Increased electricity use Reduced cogenerated electricitya Primary energy savings Social cost-BAU Reduced district heat production CHP–BST Boiler-biomass Boiler-oil Increased electricity use Reduced cogenerated electricitya Primary energy savings a b

+ Improved taps

+ Improved windows & doors

+ Additional roof insulation

+ Additional external walls insulation

+ Ventilation heat recovery

10.9 2.3 1.0 – 7.5 (7.3)b 6.6 (6.9)b

39.3 6.7 3.4 – 27.2 (26.2)b 22.3 (23.3)b

42.6 7.3 3.8 – 29.4 (28.4)b 24.3 (25.4)b

49.4 8.4 4.4 – 34.1 (32.9)b 28.0 (29.2)b

88.9 15.7 8.2 31.0 (29.9)b 61.4 (59.3)b 20.4 (23.6)b

5.5 6.5 3.2 – 3.5 11.7

11.5 20.3 18.6 – 7.4 43.0

11.9 21.9 20.8 – 7.6 47.0

13.1 25.3 24.3 – 8.4 54.4

15.9 45.8 49.8 31.0 10.2 70.4

7.3 5.0 1.1 – 5.0 8.4

21.9 17.2 7.4 – 15.1 31.3

23.2 18.8 8.3 – 16.0 34.3

26.7 21.7 9.8 – 18.5 39.7

42.5 42.4 19.9 31.0 29.3 44.4

6.3 4.7 2.4 – 4,4 9.1

17.7 16.3 12.4 – 12.3 34.2

18.7 17.8 13.9 – 12.9 37.5

21.4 20.6 16.2 – 14.8 43.4

32.0 40.3 32.4 31.0 22.1 51.7

7.0 4.8 1.7 – 4,7 8.8

20.6 16.5 9.5 – 13.7 32.9

21.8 18.1 10.6 – 14.5 36.0

25.1 20.8 12.4 – 16.7 41.6

39.2 40.7 25.1 29.9 26.1 49.0

Primary energy used by condensing power plants to compensate the reduction of cogenerated electricity. The first number is when CST is the reference power plant; the second number (in parenthesis) is when BST is the reference power plant.

scenario where the credit is from BST (see Table 4), influencing the primary energy use. For the minimum cost district heat production systems the primary energy use varies strongly as different technologies and fuels are used under the different taxation scenarios.

The primary energy use in the No tax scenario is about 50% higher than in the other scenarios. This is because CHP is less cost-effective without any taxation, resulting in a higher use of the less efficient boilers.

Fig. 8. Primary energy savings of cumulatively applied energy efficiency measures. The main bars for the reference production show the savings if CST is the reference power plant; the error bars show the increased primary energy savings if BST is the reference power plant.

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Fig. 9. Ratio of primary energy and final energy savings of cumulatively applied energy efficiency measures. The main bars for the reference production show the savings if CST is the reference power plant; the error bars show the increased primary energy savings if BST is the reference power plant

Table 9 Production unit characteristics of the minimum cost district heat production systems if CHP–BIGCC is used for base load production. Production unit of district heat Swedish tax CHP–BIGCC Boiler-biomass Boiler-oil Social cost-550 ppm CHP–BIGCC Boiler-biomass Boiler-oil Social cost-BAU CHP–BIGCC Boiler-biomass Boiler-oil

Capacity (MW)

Operating time (hrs/year)

Utilization factor (%)

Heat generation (GWh)

Electricity generation (GWh)

Primary energy use (GWh)

74 46 40

7200 5664 672

73.0 32.2 2.6

473 130 9

433 – –

1042 122 11

72 33 55

7200 5784 1536

73.7 42.8 4.9

465 124 23

425 – –

1024 117 29

75 36 49

7200 5544 960

72.6 26.6 3.9

477 118 17

437 – –

1051 111 20

3.3. Demand and supply side interactions Table 6 shows the distribution of the annual primary energy use of the case-study building for different taxation scenarios with a final energy use of 133.6 MWh. The cogenerated electricity from the CHP units is also shown.

Table 7 shows the reduced heat demand, increased electricity use and reduced cogenerated electricity when the end-use energy efficiency measures are applied. The impact of the energy efficiency measures on primary energy use is presented in Table 8. The reduced district heat production is shown for the different production units. The reduced

Table 10 Distribution of primary energy use for heating the case-study building without energy efficiency measures on different production units and cogenerated electricity if CHP–BIGCC is used for base load production. District heat production

Swedish tax CHP–BIGCC Boiler-biomass Boiler-oil Total Social cost-550 ppm CHP–BIGCC Boiler-biomass Boiler-oil Total Social cost-BAU CHP–BIGCC Boiler-biomass Boiler-oil Total

Primary energy use of case-study building

Cogenerated electricity (MWh)

MWh

%

252.0 32.5 3.7 288.2

87.4 11.3 1.3 100

104.7 – – 104.7

246.8 30.4 9.3 286.5

86.1 10.6 3.2 100

102.5 – – 102.5

254.6 29.1 6.6 290.4

87.7 10.0 2.3 100

105.8 – – 105.8

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Table 11 Primary energy balance (MWh/year) of cumulatively applied energy efficiency measures if CHP–BIGCC technology is used for base load production. Description Swedish tax Reduced district heat production CHP–BIGCC Boiler-biomass Boiler-oil Increased electricity use Reduced cogenerated electricity Primary energy savings Social cost-550 ppm Reduced district heat production CHP–BIGCC Boiler-biomass Boiler-oil Increased electricity use Reduced cogenerated electricity Primary energy savings Social cost-BAU Reduced district heat production CHP–BIGCC Boiler-biomass Boiler-oil Increased electricity use Reduced cogenerated electricity Primary energy savings

+ Improved taps

+ Improved windows and doors

+ Additional roof insulation

+ Additional external walls insulation

+ Ventilation heat recovery

9.3 6.4 1.1 – 9.2 7.6

24.1 22.8 7.4 – 23.8 30.4

25.2 25.0 8.3 – 24.9 33.5

28.7 28.9 9.8 – 28.4 38.9

40.5 56.0 19.9 31.0 40.1 45.3

8.9 5.4 2.6 – 8.8 8.1

22.6 18.3 14.1 – 22.4 32.6

23.6 19.9 15.8 – 23.3 35.9

26.8 23.0 18.4 – 26.6 41.7

37.3 44.0 37.2 31.0 36.9 50.6

9.6 5.9 1.6 – 9.2 7.9

25.5 20.0 10.2 – 24.4 31.4

26.7 22.0 11.4 – 25.5 34.5

30.5 25.3 13.4 – 29.2 40.0

43.6 48.9 27.3 29.9 41.7 48.2

district heat production from the full range of end-use energy efficiency measures represents 44–59% of the primary energy use of the building before applying the measures. The peak load boiler accounts for 7% of the reduced district heat in the reference district heat production and 19–45% in the minimum cost district heat productions. Fig. 8 shows the primary energy savings of the various end-use energy efficiency measures for the different district heat production systems. Efficient windows and doors give the biggest primary energy savings. For the minimum cost district heat production systems, ventilation heat recovery is the next most effective measure. However, ventilation heat recovery increases primary energy use for the reference district heat production system. Fig. 9 shows the ratio of primary and final energy savings (primary energy efficiency) for the various end-use energy efficiency measures. Additional roof insulation gives the greatest primary energy reduction, followed by improved windows and doors. However, much smaller or no primary energy is achieved with ventilation heat recovery. 4. Sensitivity analysis To demonstrate the potential of CHP–BIGCC technology if it is commercialized, the CHP–BIGCC plant is used for the base load production for the Swedish tax, Social cost-550 ppm and Social cost-BAU scenarios as it gives the lowest district heat production cost for high utilization time. The optimal capacities for the production units are given in Table 9. When the CHP–BIGCC plant is used for the base load production the primary energy use and the cogenerated electricity increases by 413–425 GWh and 241–248 GWh, respectively, compared to the CHP–BST. The distribution of the annual primary energy use for the casestudy building and the cogenerated electricity with CHP–BIGCC technology is shown in Table 10. The primary energy use for heating the building increases compared to the CHP–BST technology. However, the increased primary energy is more than offset by the equivalent primary energy benefit of the cogenerated electricity with the CHP–BIGCC technology. The impact of the energy efficiency measures on the primary energy use is presented in Table 11. The savings with CHP–BIGCC

follow the same trend as the earlier results with CHP–BST. The net primary energy savings from the full range of measures differ slightly between base load production with CHP–BIGCC or CHP–BST. This is because the CHP–BIGCC system is more efficient than the CHP–BST but also more capital intensive. Therefore, the optimal capacity for CHP–BIGCC is less than for CHP–BST, increasing the boiler capacity of the district heat production. 5. Discussion and conclusions In this study, we have explored how end-use energy efficiency measures in an apartment building affect primary energy use in district heat production systems. Our approach involves detailed hour-by-hour analysis of the interactions between end-use energy demand and district heat and electricity production. The minimum cost district heat production systems for the scenarios with environmental taxation all have biomass-based CHP for base load production, biomass boiler for medium load production and light fuel oil boiler for peak load production. The fossil fuels become less competitive as the environmental taxation increases. However, light fuel oil boiler for the peak load production remains viable due to low utilization and investment cost. The district heat production cost for the minimum cost district heat production systems are not sensitive to the environmental taxation. Thus, environmental taxation has a minimal effect on heat production cost for optimally-designed district heat production systems. CST emerges as the reference condensing power plant under all taxation scenarios except for the Social cost-BAU scenario, in which BST is the reference condensing power plant. When CST is the reference power production fossil coal is used instead of biomass and therefore fossil fuel for power production increases as cogenerated electricity is reduced and electricity use is increased due to the energy efficiency measures. However, when CST is the reference power production instead of BST more biomass can be used in other applications where it serves society’s goals most efficiently and needs to be considered in a system analysis. Gustavsson et al. [32] and Joelsson and Gustavsson [33] have analyzed the how biomass can be used efficiently to mitigate climate change and reduce oil use and have discussed these issue further.

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Ventilation heat recovery gave the largest final energy savings, followed by energy-efficient windows and doors. However, the primary energy savings are largest for energy-efficient windows and doors. The primary energy savings for ventilation heat recovery are significant for the minimum cost district heat productions, but for the reference district heat production system the ventilation heat recovery increases the primary energy use. Dodoo et al. [34] also found ventilation heat recovery to give low primary energy savings where district heating is based largely on CHP production. In the present study, the CHP production accounts for 68–83% of the total heat production for the minimum cost district heat production systems and 92% for the reference district heat production system. Hence, the oversized CHP production in the reference district heat production system results in low primary energy savings for the end-use energy efficiency measures. Therefore, it is important to design district heat production system based on the long-term heat demands. Otherwise, the district heat cost and primary energy use will be higher than necessary. This is clearly shown here by analyzing the interaction between individual end-use energy efficiency measures and the type of district heat production, in particular for ventilation heat recovery, as suggested by Gustavsson and Joelsson [17]. A significant amount of the primary energy savings of the energy efficiency measures is from the peak load production units, although these units cover only a small share of total heat load. These savings are more important for the minimum cost district heat production systems as more boiler production is used in these systems. This further stresses the importance of optimizing district heat production based on the demand side. Our analysis is based on the energy efficiency measures for an individual multi-storey building, but our conclusion may also be valid for other district heated buildings. Joelsson and Gustavsson [16] analyzed the primary energy savings of buildings of different construction, sizes and energy standards when implementing enduse energy efficiency measures. They found that the primary energy use is reduced significantly as the energy efficiency measures are implemented for all the different buildings. However, the implementation of energy efficiency measures in a significant share of the district heated building stock may change the profile of the heat load duration curve. This has not been analyzed here, and should be further studied. The primary energy savings of end-use energy efficiency measures depend on the characteristics of the district heat production system and the building energy efficiency measures. Therefore, both the demand and supply sides as well as their interaction need to be analyzed in order to minimize the primary energy use of district heated buildings. Acknowledgements We gratefully acknowledge funding support from the European Union, the Swedish Energy Agency, and the Jämtland County Council, and the assistance and helpful comments from Roger Sathre and from the anonymous reviewers. References [1] UNEP, Buildings and Climate Change Status, Challenges and Opportunities, United Nations Environment Programme, Paris, 2007, ISBN 9789280727951. [2] IPCC (Intergovernmental Panel on Climate Change), Climate change 2007: mitigation, in: Contribution of Working Group III to the Fourth Assessment Report, Cambridge University Press, Cambridge, UK, 2007. [3] European Commission, Green paper on energy efficiency: doing more with less, 2005. Web accessed at http://ec.europa.eu on October 16, 2009. [4] Energy Charter Secretariat, Sweden: indepth energy efficiency review, 2006. Web accessed at http://www.encharter.org on October 9, 2009. [5] Directive F 2002/91/E.C, The energy performance of buildings, Official Journal L 001, 04/01/2003 P. 0065—0071, European Parliament and of the Council of 16 December 2002. Web accessed at http://eurlex.europa.eu on June 15, 2009.

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