Geographical analyses of wood chip potentials, costs and supply for

Geographical analyses
of wood chip potentials,
costs and supply for
sustainable energy
production in Denmark
Dr. Bernd Moeller, Aalborg
University Denmark
Dr. Per S. Nielsen, Forest Research
Acknowledgement
 Bruce Talbot, Hans SkovPetersen and Niels Heding of
the Danish Centre for Forest,
Landscape and Planning –
KVL
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Introduction
 Determine the transport costs
of wood chips from forest to
location of energy plants in
Denmark
 Spatial relation between supply
transportation, and costs
 Spatial models with raster GIS
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Biomass in the Danish
system
 Wood covered 3.5% of primary
fuel consumption in Denmark
2002
 350,000 wet tons/year
 In 80 energy plants
 Very little un-used
 9 US$/GJ
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Biomass from forests
 Forests cover 11.3% of land
area
 20%<5 ha, 50%<50ha
 Chips are from either summer
dried logs or thinnings with a
required moisture content of
40-55% (wet basis)
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Transportation of wood
chips






Bin containers 40m3
maximum load assumed
Costs includes in-forest transportation.
Costs includes costs independent on
location (loading, chipping etc)
Does not include revenue a forest
owner might receive.
Which means that the final cost curves
does not reflect the wood chips market
price
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How GIS are applied
In-forest biomass, costs of
transportation, possible plant
locations and other issues are
mapped in raster-GIS. Image goes here
Using layers of raster data, each
geographically distributed aspect
is analysed using cell-to-cell
maths, neighborhood statistics
and zonal geometry.
The results are intensity maps or
distributions of site-specific costs.
Biomass resource
mapping
LCP code
14
15
16
26
27
28
29
30
32
33
34
Description
Shrub / forest
Deciduous forest
Coniferous forest
Beech forest
Young trees
Spruce plantation
Mixed forest
Mountain pine woodland
Larch forest
Recently felled forest
Thin coniferous forest
Comments
Total area [ha] % of forest area
No wood chip production
83,534
16.8
Tops and large branches from felling
137,718
27.8
Tops and large branches from felling
71,404
14.4
Tops and large branches from felling
49,011
9.9
Thinning
14,688
3.0
Tops and large branches from felling
60,587
12.2
Assumed 35% deciduous, 65% coniferous
8,511
1.7
Wood chips from whole trees
32,433
6.5
Tops and large branches from felling
2,037
0.4
No wood chip production
2,394
0.5
No wood chip production
33,564
6.8
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Annual recoverable
resources
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Selected energy plants
Plant
name
Hals
Skørping
Ensted
Herning
Plant type
Composition of fuel consumption
District heating
District heating
Power plant
Cogeneration
64% wood, 31% straw, 5% oil
95% wood, 5% oil
93% coal, 5% straw, 1% wood, 1% oil
55% wood, 45% natural gas
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Rated power and
Annual wood chip
heat output
consumption
0 MW, 8 MJ/s
5,500 tons dry matter
0 MW, 7 MJ/s
9,000 tons dry matter
600 MW, 80 MJ/s
15,000 tons dry matter
89 MW, 174 MJ/s
50,000 tons dry matter
Transport cost modeling
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Average costs / accumulated supply
Transport costs [US$/ton dm]
30
25
20
$20
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$19
$18
15
$14
10
5
0
0
5000
10000
Herning
15000
Hals
20000
25000
Skørping
30000
Ensted
35000
40000
45000
50000
Supply [tons dm]
Interpretation of results
Average fuel transport costs
$21
$20
Ensted
$19
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$18
Herning
$17
$16
Hals
$15
$14
-20%
-10%
0%
10%
Variation in fuel demand
$13
20%
Skørping
Conclusions
 Forest owners can assess the value of



un-used residues
Hauling companies can use it for
improve efficiency
Energy plants can use it to assess
resources availability for new
investments or upgrades (cogen)
Policy makers can use it to assess
environmental and socio-economic
aspects of local wood resources
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Conclusions (continued)
 Although transportation cost is



important other issues may be more
important for the individual operator
The reality does not always the most
optimal solution
Many players with different prices
Harvesting intervals of many small
forests - challenge long term fuel supply
demand from energy plants.
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