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Industrial Engineering ResearchGroup
Economic, social and environmental optimization of a forest biomass supply chain
Claudia Cambero, PhD Student
Dr. Taraneh Sowlati
April 16, 2013
2
VCO project Project Title: Economic, social and environmental optimization of forest biomass value chain in British
Columbia, Canada.
Project Start Date: January 2013 Estimated Completion Date: March 2015
Name of Principal Investigator:
Taraneh Sowlati
Institution:
University of British Columbia
Names of Co-Investigators:
Robert Kozak
Institution:
University of British Columbia
Names of Collaborators:
Jean Favreau, Denis Cormier, Jennifer O’Connor,
Mihai Pavel, Dominik Roser
Institution:
FPInnovations
Network Theme:
T3-F1 : VCO Network Research Theme 3-Integrated and collaborative planning; Focus area 1-Integrated
value chain planning. Support to themes T1-F2 and T2-F3
HQP (Ph.D., Master’s, PDF, Internship):
Ph.D.
Student name:
Claudia Cambero
3
• “Forest products industry at a crossroads” (CFS, 2012)
• “The Bio-pathways project” (FPAC, 2010)
• Electricity
• Heat
• Transportation fuels
• Bio-chemicals
• Bio-materials
• Integrate the production of traditional and
Innovative products
• Maximize the value from wood fiber cfs.nrcan.gc.ca
Research motivation
The problem…
In order to maximize the value from the wood fiber, we need to:
• Find the best product/technology
• Find the best arrangement of the forest biomass supply chain
• Consider multiple factors:
- Economic
- Social
- Environmental
biv.com
wellonsfei.ca/en/is-biomass-green.aspx
4
Previous studies - assessment 5
Area Description Examples Drawbacks
Economic
feasibility
Estimate total production costs,
cost per unit of energy, net present
value or rate of return of forest
biomass supply chains from
biomass collection/harvesting to the
gate of the plant, or to its
conversion into a final product.
Scenario-based analysis.
• Danon et al. (2012) . Possibilities of
implementation of CHP in the wood industry in
Serbia
• Sarkar et al. (2011). Biofuels and biochemicals
production from forest biomass in Western
Canada
• Ghezzaz & Stuart, (2011). Biomass availability
and process selection for an integrated forest
biorefinery
Considered
single criteria &
did not find the
optimal design
of the value
chain
Environ-
mental
evaluation
Life Cycle emissions, resources
depletion and environmental
impacts of forest biomass supply
chains from biomass
collection/harvesting to its
conversion into a product (cradle-
to-gate) or to its final use (cradle-
to-grave). Scenario based analysis
• Steele et al. (2012). LCA of pyrolysis for bio-oil
production
• Pa et al. (2013). Evaluation of wood pellet
application for residential heating in BC based
on a streamlined LCA
• Tabata & Okuda (2012). LCA of woody
biomass energy utilization: case study in Gifu
Prefecture, Japan
Considered
single criteria &
did not find the
optimal design
of the value
chain
Social
evaluation
Social indicators included in multi
criteria analysis. Most used are
employment and “food-to-energy”
• Krajng & Domac, (2007). How to model
different socio-economic and environmental
aspects of biomass utilisation: Case study in
selected regions in Slovenia and Croatia
• Pavinen et al. (2010). A concept for assessing
sustainability impacts of forestry-wood chains
• den Herder et al. (2012). Sustainability impact
assessment on the production and use of
different wood and fossil fuels employed for
energy production in North Karelia, Finland.
Did not find the
optimal design
of the value
chain
Sustain-
ability
evaluation
Evaluate economic, social and
environmental factors of forest
biomass supply chains from
biomass harvesting/collection to its
conversion into a product or final
use. Scenario-based analysis.
Previous studies - optimization 6
Area Description Examples Drawbacks
Mathematical
programming
Use of LP or MILP models
to minimize cost or
maximize profit of the
supply chain, from biomass
collection/harvesting to the
gate of the plant or to its
conversion and sometimes
distribution.
Typical decisions are plant
location and capacity,
biomass supply area,
selection of technologies,
storage and logistic
decisions.
• Feppaz et al. (2004) Optimizing forest
biomass exploitation for energy supply at
a regional level
• Gunnarson et al. (2004) Supply chain
modelling of forest fuel
• Leduc et al. (2010) Optimal location of
lignocellulosic ethanol refineries in
Sweden
• Feng et al. (2010) Integrated bio-refinery
and forest products supply chain network
design using mathematical programming
approach
• Keirstead et al. (2012) Evaluating
biomass energy strategies for a UK eco-
town with an MILP optimization model
Did not consider
economic, social and
environmental objectives
simultaneously
Multi-
objective
optimization
Integration of economic ,
social and life cycle
environmental impacts for
the design of forest
biomass supply chains.
Typical decisions are
related to technology and
product selection.
• Čuček et al. (2011) Total footprints-based
multi-criteria optimisation of regional
biomass energy supply chains
• You et al. (2012) Life cycle optimization of
biomass-to-liquid supply chains with
distributed-centralized processing
networks
• Santibanez-Aguilar et al. (2011) Optimal
planning of a biomass conversion system
considering economic and environmental
aspects
Did not integrate
decisions on: biomass
types and sources,
preprocessing and
conversion facilities
location, type and size,
and product type,
addressing economic
performance, social and
environmental life cycle
impacts
Develop a model that optimizes economic, social and environmental aspects of a forest biomass supply chain.
Research objective
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• Perform a Life Cycle Assessment of value alternatives for forest biomass utilization in a region
• Optimize the design of the forest biomass value chain considering the economic, social and environmental factors simultaneously
• Apply the model to a case study in BC
Grave
Approach Cradle
Nat
ura
l Res
ou
rces
an
d E
ner
gy
Emis
sio
ns
and
Was
te
washingtondnr.wordpress.com; Microsoft Clip Art; biv.com; paperadvance.com; cfs.nrcan.gc.caz
MODELING FRAMEWORK
Life Cycle Assessment LCA
Environmental evaluation 1
8
Multi Objective Optimization MOO
Supply chain design 2
MODELING FRAMEWORK
Approach
Life Cycle Assessment LCA
Environmental evaluation 1
Biomass procurement
Transportation and Pre-
processing Conversion
Final markets
Enviro
nm
ent
Econ
om
y So
ciety
Economy Max. profit
(NPV)
Society Max. direct jobs (# of new jobs)
Environment Min. GWP
(CO2 equivalents)
9 washingtondnr.wordpress.com; wellonsfei.ca/en/is-biomass-green.aspx; Microsoft Clip Art; biv.com; paperadvance.com; cfs.nrcan.gc.caz
Multi Objective Optimization MOO
Supply chain design 2
MODELING FRAMEWORK
INPUTS • Available biomass, • Potential value alternatives, • Potential location of facilities, • Estimated demand
Approach
Life Cycle Assessment LCA
Environmental evaluation 1
OUTPUTS Analysis of trade-offs among economic, social and environmental aspects
Objective 1 $NPV
Ob
ject
ive
2 #
Jo
bs Pareto
optimal
10
Source: http://www.for.gov.bc.ca/hts/tsa/tsa29/map.gif
Case study: Williams Lake TSA
11
Interior BC One of the largest TSA in BC
Largely affected by MPB 4.9 million hectares
AAC: 5.7 million cubic meters
Source: http://www.for.gov.bc.ca/hfp/mountain_pine_beetle/
mid-term-timber-supply-project/Williams%20Lake%20TSA.pdf
Major Centers or Mill Locations
Private Lands or Indian Reserves
Parks, Ecological Reserves
TFL, Community Forests or Woodlots
Timber Harvesting Land Base
Case study: Williams Lake TSA
12
• Population: 300 • Lots of biomass • Current sawmill owned by
First Nation (West Chilcotin Forest Products)
• Local electricity by diesel generators
• Interested in bio-energy • Large potential for new
products (e.g. pyrolysis, pellets)
• Population: 100 • Forestry 2nd economic
activity • Current sawmill owned by
First Nation (River West Forest Products)
• 50% of electricity by diesel generators
• Interested in bio-energy and new products (e.g. pellets)
• Population: 12,000 • Forestry 1st economic
activity • Hosts lumber, plywood,
veneer, pellet and chip mills.
• Most efficient bio-power plant in North America
• Limited availability of low cost logging residues
• Interested in district heat • Potential for pellet mill
expansion
Case study: alternatives
Region Potential locations
Technologies Products and Markets
Williams Lake TSA
Anahim Lake
Combined heat and power
• Heat for local supply
• Power for local supply
Pelletization
• Local domestic use
• Export through Bella Coola
• Export through Williams Lake
Pyrolysis • Local supply
• Williams Lake
Hanceville
Combined heat and power
• Heat for local supply
• Power for local supply
Pelletization • Export through Williams Lake
Williams Lake
District heating • Local heat supply Pelletization • Export
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The model
Objective function: max NPV; max created jobs; min GWP
Subject to: • Residues availability • Capacity (conversion) • Demand • Flow constraints (conversion) • Logic constraints (conversion)
14
Continuous variables
Set of potential technologies
K
Set of biomass sources
I
Set of potential markets
M
Supply chain configuration Set of potential plant locations
J
Set of potential products
L
Anahim production Hanceville production
Williams Lake production
15
Binary variables
Aggregated cutting blocks (2000)
Hanceville
Bella Coola
Anahim
Hanceville
Pelletization
Williams Lake
District Heating
Williams Lake
Anahim
Pyrolysis
CHP Heat
High quality pellets
Power
Pyrolysis bio-oil
Low quality pellets
CHP
Project progress
16
Year Milestones/Deliverable Expected
Delivery Date 2013
• Review of the literature on studies relevant to optimization,
LCA, and multi-objective optimization of forest biomass supply
chain. Write a review paper.
• Identification and characterization of the case study in
collaboration with FPInnovations
March 2013
June 2013
2014
2014
• Development of the Life Cycle Assessment (LCA) model:
1. Model development
2. Verification and validation
3. Analysis of results and identification of major findings
4. Sensitivity analysis
5. Write a paper
• Development of Multi Objective Optimization (MOO) model:
1. Model development and solution
2. Verification and validation
3. Analysis of results and identification of major findings
4. Sensitivity analysis
5. Write a paper
March 2014
Dec. 2014
2015 Final report to VCO March 2015
Next steps
• Gather data/ information
• Develop the LCA model
• Develop the MOO model
17
18
Acknowledgements
References
20
• Canadian Forest Service CFS. (2012). Industry: a sector in transition. Retrieved October/12, 2012, from http://cfs.nrcan.gc.ca
• Čuček, L., Varbanov, P. S., Klemeš, J. J., & Kravanja, Z. (2012). Total footprints-based multi-criteria optimisation of regional biomass energy supply chains. Energy, 44(1), 135-145.
• Danon, G., Furtula, M., & Mandić, (2012) M. Possibilities of implementation of CHP (combined heat and power) in the wood industry in Serbia. Energy, (0)
• den Herder, M., Kolström, M., Lindner, M., Suominen, T., Tuomasjukka, D., & Pekkanen, M. (2012). Sustainability impact assessment on the production and use of different wood and fossil fuels employed for energy production in North Karelia, Finland. Energies, 5(11), 4870-4891.
• Feng, Y., D'Amours, S., LeBel, L., & Nourelfath, M. (2010). Integrated bio-refinery and forest products supply chain network design using mathematical programming approach. ( No. 50). Montreal: CIRRELT .
• FPAC. (2010). Transforming Canada's forest products industry: Summary of findings from the future bio-pathways project. ( No. 1).Forest Products Association of Canada. Retrieved February 14, 2013 from http://www.fpac.ca/index.php/en/value-pathways/
• Freppaz, D., Minciardi, R., Robba, M., Rovatti, M., Sacile, R., & Taramasso, A. (2004). Optimizing forest biomass exploitation for energy supply at a regional level. Biomass and Bioenergy, 26(1), 15-25.
• Ghezzaz, Hakim & Stuart. Paul (2011). Biomass availability and process selection for an integrated forest biorefinery. Pulp & Paper Canada, 112(3), 19-26.
• Gunnarsson, H., Ronnqvist, M., & Lundgren, J. (2004). Supply chain modeling of forest fuel. European Journal of Operational Research, 158(1), 103-123.
• Keirstead, J., Samsatli, N., Pantaleo, A. M., & Shah, N. (2012). Evaluating biomass energy strategies for a UK eco-town with an MILP optimization model. Biomass and Bioenergy, 39(0), 306-316.
References
21
• Krajnc, N., & Domac, J. (2007). How to model different socio-economic and environmental aspects of biomass utilisation: Case study in selected regions in Slovenia and Croatia. Energy Policy, 35(12), 6010-6020.
• Leduc, S., Starfelt, F., Dotzauer, E., Kindermann, G., McCallum, I., Obersteiner, M., & Lundgren, J. (2010). Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden. Energy, 35(6), 2709-2716.
• Pa et al. (2013). Evaluation of wood pellet application for residential heating in BC based on a streamlined life cycle analysis. Biomass and Bioenergy, 49, 109-122
• Päivinen, R., Lindner, M., Rosén, K., & Lexer, M. J. (2012). A concept for assessing sustainability impacts of forestry-wood chains. European Journal of Forest Research, 131(1), 7-19.
• Santibanez-Aguilar, J. E., Gonzalez-Campos, J. B., Ponce-Ortega, J. M., Serna-Gonzalez, M., & El-Halwagi, M. M. (2011). Optimal planning of a biomass conversion system considering economic and environmental aspects. Industrial & Engineering Chemistry Research, 50(14), 8558-8570.
• Sarkar, S., Kumar, A., & Sultana, A. (2011). Biofuels and biochemicals production from forest biomass in western Canada. Energy, 36(10), 6251-6262.
• Steele, P., Puettmann, M.E., Kanthi, V., & Cooper, J. E. (2012). Life-cycle assessment of pyrolysis for bio-oil production. Forest Products Journal, 62 (4), 326-334.
• Tabata, T., & Okuda, T. (2012). Life cycle assessment of woody biomass energy utilization: Case study in Gifu prefecture, Japan. Energy, 45(1), 944-951.
• You, F., & Wang, B. (2011). Life cycle optimization of biomass-to-liquid supply chains with distributed–centralized processing networks. Industrial & Engineering Chemistry Research, 50(17), 10102-10127.