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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
4TH GENERATION DISTRICT HEATING (DH)
Time
En
erg
y
effi
cien
cy
Bu
ild
ing
en
erg
y
con
sum
pti
on
1st
Gen.
1930 1880 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
Swedish DH systems
Source: Statistics Sweden & Swedish Energy Agency
0
10
20
30
40
50
60
70
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
Fu
el u
se
[T
Wh
]
Excess heat
Heat pumps
Electric boilers
Biofuels, Municipal solidwaste, peat
Energy coal including cokeoven and blast furnace gas
Natural gas including LPG
Oil
0
10
20
30
40
50
1980 1985 1990 1995 2000 2005 2010
Fue
l su
pp
ly [
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
Fu
el u
se [
TW
h]
Industrial EH
Heat pumps
Electric boilers
Biofuels, Municipal solidwaste, peat
Energy coal including cokeoven and blast furnace gas
Natural gas including LPG
Oil
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
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
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?
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?
Methodology
• Regional level (regional market for biomass)
• Case (diverse DH systems in terms of fuel use
and DH production technology)
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
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)
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”
Climate policy scenarios
• 450PPM (450 ppm)
• NEWPOL (New Policies)
(Energy prices and CO2 charge calculated by ENPAC tool)
International Energy
Agency (World Energy
Outlook)
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)
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)
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”
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
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)
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).
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
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
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