This document summarizes a study assessing the economic impacts of utilizing excess heat from industries through regional heat networks. The study uses energy system modeling to analyze scenarios with and without a large heat network connecting chemical industries to district heating systems in Gothenburg and Kungälv, Sweden. The results show that investing in the heat network reduces the total and marginal costs of district heating supply in most cases. However, the investment is only cost-effective if other excess heat sources are not more localized or biomass is not abundantly and cheaply available in the region.

1. Economic Impacts of Large-Scale
Utilization of Excess Heat -
Assessment through Regional
Modeling
Akram Sandvall, Erik Ahlgren, Tomas Ekvall
Energy Technology, Energy and Environment Department,
Chalmers University of Technology
Swedish Environmental Research Institutes (IVL)
IEA ETSAP Workshop, Nov.17-19, 2014, Copenhagen

2. 4TH GENERATION DISTRICT HEATING (DH)
Time
Energy
efficiency
Buildingenergy
consumption
1st
Gen.
19301880 1970 Now Future
2nd
Gen.
3rd
Gen.
4th
Gen.
Steam
• Pressurized
hot water
(over 100ºC)
• Utilizing
CHPs
Pressurized hot
water
(below100ºC)
• Pressurized hot
water (about 50 ºC)
• Heat recovery (e.g.
industrial excess
heat)
• Use of renewable
sources

3. Swedish DH systems
Source: Statistics Sweden & Swedish Energy Agency
0
10
20
30
40
50
60
70
1970
1975
1980
1985
1990
1995
2000
2005
2010
Fueluse[TWh]
Excess heat
Heat pumps
Electric boilers
Biofuels, Municipal solid
waste, peat
Energy coal including coke
oven and blast furnace gas
Natural gas including LPG
Oil
0
10
20
30
40
50
1980 1985 1990 1995 2000 2005 2010
Fuelsupply[TWh]
Peat
Tall oil pitch
Forest residues
Municipal solid waste
(MSW)
0
10
20
30
40
50
60
70
1970
1975
1980
1985
1990
1995
2000
2005
2010
Fueluse[TWh]
Industrial EH
Heat pumps
Electric boilers
Biofuels, Municipal solid
waste, peat
Energy coal including coke
oven and blast furnace gas
Natural gas including LPG
Oil

4. Biomass (forest residues &
energy crops)
• Renewable source
–Competition between the heat, power and transport
sectors
• Transported over short distances by trucks
–Regional market  Limited resource

5. Heat synergy collaborations
Power
• Combined heat and power
(CHP)
• Intermittent technologies
(wind, solar)
Transport
• Bio refineries (e.g.
SNG production)
Waste management
Industries
• Industrial excess heat (EH)
District
heating

6. Industrial EH
• Challenges
– High investment cost of building heat networks
– Possible lock-in effects
Could construction of large heat networks, shared
between several industries and DH systems be a
solution?

7. Research Questions
• How would the system cost of DH supply be affected at a
regional level by the construction of a large heat network
allowing for long-distance transmission of EH?
• How is the marginal cost of DH supply affected by such a large
heat network?

8. Methodology
• Regional level (regional market for biomass)
• Case (diverse DH systems in terms of fuel use
and DH production technology)

9. Västra Götaland
CASE

10. Methodology
• Regional level (regional market for biomass)
• Case (diverse DH systems in terms of fuel use and DH
production technology)
• Reference group
–Learning for researchers and stakeholders
–Solving imperfect information problem
Build trust

11. Reference Group
Stakeholders including:
–Chemical industries in Stenungsund
–Energy utility companies in Stenungsund, Kungälv,
Gothenburg
Researchers at:
–Heat and Power Technology & Energy Technology at
Chalmers
–Swedish Environmental Research Institutes (IVL)
–Sweden’s Technical Research Institute (SP)

12. Methodology
• Regional level (regional market for biomass)
• Case (diverse DH systems in terms of fuel use and DH
production technology)
• Reference group
• Scenario analysis (to explore not to predict)
• Sensitivity analysis
Two options:
–“Connection”
– “No-connection”

13. Climate policy scenarios
• 450PPM (450 ppm)
• NEWPOL (New Policies)
(Energy prices and CO2 charge calculated by ENPAC tool)
International Energy
Agency (World Energy
Outlook)

14. Sensitivity analysis (I)
• NONG
NG use is not allowed after 2030
• REHD (Reduced Heat Demand)
2010-2030 10% linear reduction
2030-2050 10% linear reduction
• LIC (Low Investment Cost)
About 50% lower pipeline cost
• INTRATE (INTerest RATE)
(2.5% and 30 yrs for pipelines &
11% and 15 yrs for heat exchangers)

15. Sensitivity analysis (II)
• REFINERY
Refineries in Gothenburg supply heat until 2050
• RES-S (Renewable Energy Sources Support)
Constant subsidies for renewable electricity at level
of 2010
• NOSNG
No alternative regional biomass demand
(single-sector perspective)

16. Methodology
• Regional level (regional market for biomass)
• Case (diverse DH systems in terms of fuel use and DH production
technology)
• Reference group
• Scenario analysis
• Energy system modeling (MARKAL - optimization
bottom-up model)
–Optimization (including the new infrastructure
capacity)
–Comparison of “connection” to “no-
connection”

17. Model
MARKAL_West_Sweden (MARKAL_WS) model
representing the energy system of the Västra Götaland
Region
• Time horizon: 2010-2050
–4 seasons per year
• Cold winter (1 month)
• Winter (2 months)
• Spring and fall (4 months)
• Summer (5 months)
• 37 DH systems with different system characteristics:
–Demand levels
–Installed capacities
–Investment options for District heating supply

18. Model
• Investment options for the heat network between the cluster of
chemical industries in Stenungsund and the Gothenburg/
Kungälv DH systems.
• Bio-refinery, GoBiGas 1& 2, for SNG (synthetic natural gas)
production (biomass competitor)

19. Optimum timing and capacity
Results

20. Technology change in VG
Differences between “connection” and “no-connection”

21. Total system cost in VG
Differences between “connection” and “no-connection”

22. Marginal Cost in Gothenburg
Differences between “connection” and “no-connection”

23. Marginal Cost in Kungälv
Differences between “connection” and “no-connection”

24. Conclusion
• Investment in the large heat network is cost-effective except if:
– Other major sources of excess heat are more closely located.
– There is an abundance of low cost biomass available in the
region.
• Higher future fossil fuel prices are likely to increase the profitability
of the investments.
• Higher interest rates would reduce this profitability.
• Reduced marginal cost of DH supply in the Gothenburg and
Kungälv DH systems in most seasons (except for the cold
seasons).

25. Thank you!

26. NEWPOL
Policy tools 2010/2020/2030/2040/2050
CO2 charge EUR/tone 16.9/14.4/23.8/33.5/43
Renewable electricity subsidy EUR/MWh 20/20/0/0/0
Energy prices/costs (i) 2010/2020/2030/2050
NG EUR/MWh 28.7/29.2/30.2/33
EO1 EUR/MWh 64.2/66.2/70/80
EO5 EUR/MWh 41.6/43.1/46/53.5
Forest residues EUR/MWh Supply curves
Energy forest (willow) EUR/MWh 20
Wood chips EUR/MWh 21.8/29/32/38
Bio pellets EUR/MWh 35/41/45/53
Excess heat EUR/MWh 0.56
Municipal waste EUR/MWh -22
Electricity
Winter cold (1 month) EUR/MWh 70/87/96/106
Winter (2 months) EUR/MWh 64/80/88/97
Spring and fall (4 months) EUR/MWh 50/63/69/76
Summer (5 months) EUR/MWh 36/44/49/54
SNG EUR/MWh 53/71.3/76.5/88.9
Others
Land available for energy forest
(willow) Ha 1000/18950/36900/36900
Refineries in Gothenburg No excess heat delivery by 2025
NG import Allowed until 2050
Heat demand Constant (at 2010 level)
2010/2020/2030/2040/2050
16.9/25.2/68.4/110/153
450PPM
20/20/0/0/0
2010/2020/2030/2050
28.7/28.3/25.1/18.5
64.2/64.7/61.8/54.9
41.6/42/39.8/37.2/34.6
53/73/80/94
Supply curves
20
21.8/29/43/66
35/42/58/87
0.56
50/70/81/86
-22
70/97/113/119
64/89/103/109
36/49/58/61
1000/18950/36900/36900
Allowed until 2050
Constant (at 2010 level)
No excess heat delivery by 2025

27. SKG pipeline
Cap≤ 50 MW 1800/ 0.25 Cap≤ 50 MW 1100/ 0.25
50˂Cap≤ 100 MW 2200/ 0.12 50˂Cap≤ 100 MW 1200/0.12
100˂Cap≤ 150 MW 2600/ 0.08 100˂Cap≤ 150 MW 1300/ 0.08
Length km
SK pipeline
Investment/ Variable
O&M Cost
[EUR/m]/
[EUR/MWh
heat]
Cap≤ 50 MW 1800/ 0.16 Cap≤ 50 MW 1100/ 0.16
Length km
EH-CCIS extraction
Cap ≤ 20 MW 4.4 Cap ≤ 20 MW 4.4
20˂Cap ≤ 40 MW 6.7 20˂Cap ≤ 40 MW 6.7
40˂Cap ≤ 60 MW 12.8 40˂Cap ≤ 60 MW 12.8
60˂Cap ≤ 80 MW 20.6 60˂Cap ≤ 80 MW 20.6
80˂Cap ≤ 100 MW 26.7 80˂Cap ≤ 100 MW 26.7
100˂Cap ≤ 120 MW 37.8 100˂Cap ≤ 120 MW 37.8
120˂Cap ≤ 140 MW 51.1 120˂Cap ≤ 140 MW 51.1
140˂Cap ≤ 150 MW 61.1 140˂Cap ≤ 150 MW 61.1
450PPM and NEWPOL LIC
55
Investment/ Variable
O&M Cost
[EUR/m]/
[EUR/MWh
heat]
55
Investment cost
(80/50 hot water)
MEUR
35 35

28. DH technologies
Gas CC CHP 45-49 90 0.8-1.2 1 2.5
Gas Engine CHP 38 86 0.75 4.3
Biomass ST CHP 25-34 110 2.3-7.2 1.5 2.7
Waste ST CHP 22 91 5.9-8.2 3 -12
Gas HOB 0.05-1.0 2.5 0.7
Biomass HOB 0.34-0.56 1.5 2.0
Oil HOB 0.09-0.17 2.5 0.7
Waste HOB 1.0-1.1 3 -16
Heat pump 0.70 0.5 0.7
[MEUR/year] [EUR/MWh fuel]
Bio-refinery plants
SNG (iii) 2 3
[EUR/MWh fuel]
Heat plants
Fixed O&M cost Variable O&M cost
Electricity [%] Total [%] [kEUR/kW electricity] [% of inv. cost/year] [EUR/MWh fuel]
Heat [%] [kEUR/kW heat]
Specific investment
cost (ii)
Combined heat and power plants
91
SNG [%]
70
300 (COP)
[% of inv. cost/year]
90
Technology Conversion efficiency (i)
110
90