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OPTIMIZATION OF A COGENERATIVE BIOMASS PLANT LOCATION USING OPEN SOURCE GIS
TECHNIQUES. TECHNICAL, ECONOMICAL AND ENVIRONMENTAL VALIDATION METHODOLOGY
Agostino Tommasi1, Raffaela Cefalo1, Aldo Grazioli2, Dario Pozzetto2, Yaneth M. Alvarez Serrano3, Michel Zuliani4
1 GeoSNaV Laboratory, Department of Engineering and Architecture, University of Trieste, Italy2 Department of Civil and Industrial Engineering, University of Pisa, Italy3 Department of Electronical, Mechanical and Management, University of Udine, Italy4Comunità Montana della Carnia, Italy
New advanced GNSS and 3D spatial techniquesTrieste, 18-20 February 2016
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Carnia Mountain Community
Public institution representing 28 Municipalities in a 1.200 km2-wide region in North-East of Friuli Venezia Giulia. The population is slightly less than 40.000 people.
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Wood biomass in Carnia
Total forest coverage: 72.655 ha (about 60% of the entire area!)
Actual wood biomass exploitation: 15%
Annual biomass potentially available for energetic purposes: 12.463 t/year
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Purpose of the study
Identify and validate, inside the administrative territory of the Carnia Mountain Community, Friuli Venezia Giulia Region, Italy, the optimal location of a new cogenerative biomass plant, using:
Georeferenced data
Integrated GIS and DBMS applications
Feasibility verification methodologies
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The study is structured in 2 different parts:
1) Optimal plant location using GIS and DBMS techniques
2) Verification and validation of the results, taking into account the technical, economical and environmental feasibility of the proposed plant location
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Input georeferenced
data
PreparationHomogenization
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Georeferenced data
Road network
Public buildings:
Schools
Rest homes
Town halls
Museums
Hospitals
Local strategic plans
Building numbers
Digital Elevation Model
Exploitable biomass
Attainable biomass
Existing biomass plants
Candidate sites
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Input georeferenced
data
PreparationHomogenization
Public usersMap
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Public users
town hall
hospital
school
rest home
museum
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Input georeferenced
data
PreparationHomogenization
Public usersMap
Private usersMap
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Private usersBuilding numberBuilding number
Industrial area
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Input georeferenced
data
PreparationHomogenization
Energeticdemand
Map
Public usersMap
Private usersMap
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Private users
Public users
Energetic Demand
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Input georeferenced
data
PreparationHomogenization
Energeticdemand
Map
Public usersMap
Private usersMap
3DRoad
NetworkModel
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3D Road Network Model
Road Network characteristics:
dimensions
categories
classifications
Arc lenght
3D Nodes coordinates (using DEM data)
Arc slope calculation
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Road network
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Elevation
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Mean Slope
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Input georeferenced
data
PreparationHomogenization
Energeticdemand
Map
Public usersMap
Private usersMap
Exploitable and
attainable biomass
map
3DRoad
NetworkModel
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Exploitable Biomass
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Attainable Biomass
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Attainable and Exploitable Biomass
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Biomass reference point
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Input georeferenced
data
PreparationHomogenization
Energeticdemand
MapEnergetic
offerMap
Public usersMap
Private usersMap
Exploitable and
attainable biomass
map
Reference pointstrasformation
3DRoad
NetworkModel
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Naturally available Biomass
Waste wood biomass
Naturally available BiomassForest wood Biomass
Energetic Offer
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Part 1: Optimal plant location using GIS and DBMS techniques
SECOND STEP:
Index Rating calculation for every sub-optimal location
Comparison of results
Optimal plant location identification
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Energeticdemand
Map
EnergeticofferMap
ExistingBiomass
Plants
3DRoad
NetworkModel
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Existing
In construction
Preliminary design
Feasibility study
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Energeticdemand
Map
EnergeticofferMap
CandidateLocations
ExistingBiomass
Plants
3DRoad
NetworkModel
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Energeticdemand
Map
EnergeticofferMap
CandidateLocations
ExistingBiomass
Plants
3DRoad
NetworkModel
Costfunction
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Cost function
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Energeticdemand
Map
EnergeticofferMap
CandidateLocations
ExistingBiomass
Plants
3DRoad
NetworkModel
Costfunction
INDEXRATING
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Energeticdemand
Map
EnergeticofferMap
CandidateLocations
ExistingBiomass
Plants
3DRoad
NetworkModel
Costfunction
INDEXRATING
SiteIndex
Comparison
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Energeticdemand
Map
EnergeticofferMap
CandidateLocations
ExistingBiomass
Plants
3DRoad
NetworkModel
Costfunction
INDEXRATING
SiteIndex
Comparison
OPTIMAL BIOMASS PLANT LOCATION
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Part 2: Feasibility study
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Feasibility study
Design of a cogeneration plant and district heating network serving the thermal loads
Economic evaluation of the investment among the alternative
Environmental sustainability of the cogeneration plant and the district heating network compared to conventional systems
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Design of the cogeneration plant
Public and private buildings district heating
Power demand evaluation:
Thermal Load: 30 W/m3
Volume of the buildings: from the Technical Map of FVG
Project Outside Temperature: - 12 °C
200 days/year of winter heating (24/24)
Annual total heating: 5.200 hours
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Technical feasibility
Theorical energy required: 28,5 MWt
Expected energy required: 23,6 MWt
Duration curve of energy demand vs operative hours, based on:
Outside temperature variation
Operative hours of the plant
Energy demand variation
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Technical feasibility
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Technical feasibility
Cogeneration plant with steam turbine, with an estimated power of 4 Mwt
Integration and reserve plant, composed of 3 heat generators, 10 Mwt each
Expected integration plant functioning time: 5.031 hours, with a gross power supply of 12,501 MWh
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Technical feasibility
Input water heat: 90°C
Output water heat: 70°C
City network lenght: 14.144 m
First pipe diameter: 400 mm
Load loss of the network: 723,7 kPa
Wood biomass consumption: 10.018 t/year
Natural gas consumption: 1,254,281 Nm3
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Economical feasability
The analisys is based on NPV (Net Present Value) methodology
The result is a negative present value of 8.157.512 €
Amortization schedule: 10 years
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Economical feasability
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Environmental sustainability
Methodology: Life Cycle Assessment (ISO 14040, ISO 14044)
Annual CO2
emissions: designed plant vs traditional gas systems
Total annual CO2
emission savings using the designed plant and network: 5.873,2 t
CO2/year
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Conclusions
The optimal plant location coincides with the biggest existing cogeneration biomass plant of the area
The second sub-optimal site is located near the city of Villa Santina (UD)
The application of feasibility verification methodologies confirms the validity of the result, with a ROI (return of investyment) time of 10 years
The results of the study are consistent and could be replicate in any area with comparable energetic and geografical characteristics
