OPTIMIZATION OF A COGENERATIVE BIOMASS PLANT LOCATION USING OPEN SOURCE GIS TECHNIQUES. TECHNICAL, ECONOMICAL AND ENVIRONMENTAL VALIDATION METHODOLOGY

Transcription

1 OPTIMIZATION OF A COGENERATIVE BIOMASS PLANT LOCATION USING OPEN SOURCE GIS TECHNIQUES. TECHNICAL, ECONOMICAL AND ENVIRONMENTAL VALIDATION METHODOLOGY Agostino Tommasi 1, Raffaela Cefalo 1, Aldo Grazioli 2, Dario Pozzetto 2, M. Alvarez Serrano 3, Michel Zuliani 4 Yaneth 1 GeoSNaV Laboratory, Department of Engineering and Architecture, University of Trieste, Italy 2 Department of Civil and Industrial Engineering, University of Pisa, Italy 3 Department of Electronical, Mechanical and Management, University of Udine, Italy 4 Comunità Montana della Carnia, Italy New advanced GNSS and 3D spatial techniques Trieste, February 2016

2 Carnia Mountain Community Public institution representing 28 Municipalities in a km 2 -wide region in North-East of Friuli Venezia Giulia. The population is slightly less than people. 2

3 Wood biomass in Carnia Total forest coverage: ha (about 60% of the entire area!) Actual wood biomass exploitation: 15% Annual biomass potentially available for energetic purposes: t/year 3

4 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 4

5 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 5

6 Input georeferenced data Preparation Homogenization 6

7 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 7

8 Input georeferenced data Preparation Homogenization Public users Map 8

9 Public users town hall hospital school rest home museum 9

10 Input georeferenced data Preparation Homogenization Public users Map Private users Map 10

11 Private users Building number Industrial area 11

12 Input georeferenced data Preparation Homogenization Public users Map Private users Map Energetic demand Map 12

13 Energetic Demand Public users Private users 13

14 Input georeferenced data Preparation Homogenization Public users Map Private users Map 3D Road Network Model Energetic demand Map 14

15 3D Road Network Model Road Network characteristics: dimensions categories classifications Arc lenght 3D Nodes coordinates (using DEM data) Arc slope calculation 15

16 Road network 16

17 Elevation 17

18 Mean Slope 18

19 Input georeferenced data Preparation Homogenization Public users Map Private users Map Exploitable and attainable biomass map 3D Road Network Model Energetic demand Map 19

20 Exploitable Biomass 20

21 Attainable Biomass 21

22 Attainable and Exploitable Biomass 22

23 Biomass reference point 23

24 Input georeferenced data Preparation Homogenization Public users Map Private users Map Exploitable and attainable biomass map 3D Road Network Model Energetic demand Map Energetic offer Map Reference points trasformation 24

25 Energetic Offer Naturally Forest wood available Biomass Biomass Waste wood biomass 25

26 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 26

27 Energetic demand Map Energetic offer Map Existing Biomass Plants 3D Road Network Model 27

28 Existing In construction Preliminary design Feasibility study 28

29 Energetic demand Map Energetic offer Map Existing Biomass Plants 3D Road Network Model Candidate Locations 29

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32 Energetic demand Map Energetic offer Map Existing Biomass Plants 3D Road Network Model Candidate Locations Cost function 32

33 Cost function 33

34 Energetic demand Map Energetic offer Map Existing Biomass Plants 3D Road Network Model Candidate Locations INDEX RATING Cost function 34

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43 Energetic demand Map Energetic offer Map Existing Biomass Plants 3D Road Network Model Candidate Locations INDEX RATING Site Index Comparison Cost function 43

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45 Energetic demand Map Energetic offer Map Existing Biomass Plants 3D Road Network Model Candidate Locations INDEX RATING Site Index Comparison Cost function OPTIMAL BIOMASS PLANT LOCATION 45

46 Part 2: Feasibility study 46

47 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 47

48 Design of the cogeneration plant Public and private buildings district heating Power demand evaluation: Thermal Load: 30 W/m 3 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: hours 48

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50 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 50

51 Technical feasibility 51

52 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: hours, with a gross power supply of 12,501 MWh 52

53 Technical feasibility Input water heat: 90 C Output water heat: 70 C City network lenght: m First pipe diameter: 400 mm Load loss of the network: 723,7 kpa Wood biomass consumption: t/year Natural gas consumption: 1,254,281 Nm 3 53

54 Economical feasability The analisys is based on NPV (Net Present Value) methodology The result is a negative present value of Amortization schedule: 10 years 54

55 Economical feasability 55

56 Environmental sustainability Methodology: Life Cycle Assessment (ISO 14040, ISO 14044) Annual CO 2 emissions: designed plant vs traditional gas systems Total annual CO 2 emission savings using the designed plant and network: 5.873,2 t CO 2/year 56

57 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 57