Puigjaner L. (ed.) Syngas from Waste

Подождите немного. Документ загружается.

3.3 Environmental Point of View

Each one of the former scenarios was compared in terms of environmental impact

following the ISO standards as in chapter ‘‘Global Clean Gas Process Synthesis

and Optimization’’ for compiling a LCA. Regarding the functional unit, given that

co-production is feasible in some of those options, the functional unit used is 1 MJ

of equivalent energy which could be from electricity or from H

. In this sense,

environmental impacts which are proportional to mass/energy ﬂows are norma-

lised by the total amount of energy produced in each scenario. We recall that the

composition of the base case coincides with the base composition of ELCOGAS; it

corresponds to a mixture of coal and petcoke, 50%/50% in mass basis, where coal

is supposed to come from the local ENCASUR mines. The petroleum coke is from

the Puertollano REPSOL reﬁnery, obtained as a by-product, with high sulphur

content, as described in chapter ‘‘Modelling Syngas Generation’’. The residual

biomass used is olive pomace or orujillo, which is the solid residue that remains

after pressing olives, a very abundant industrial residue in the south of Spain. The

system boundaries have been drawn from cradle-to-gate with the following

considerations:

• Transport of fuel materials has been disregarded, mimicking the geographical

considerations of ELCOGAS.

• CO

disposal does not consider its transportation and injection to formation, but

it considers its liquefaction.

• Hydrogen transport is not considered, and it is available at high pressure at

plant.

Fig. 9 Total and global efﬁciencies for the different considered scenarios

268 A. D. Bojarski and M. Pérez-Fortes

• Electricity consumption for the cases where net power production was found

negative is considered to be from the Spanish grid. Natural gas use is repre-

sented using Spanish data.

• No allocation of the emissions is done for other possible co-products such as

and sulphur. Moreover electricity and Hydrogen production are added up

considering their energy content together and considered indistinctively.

• Waste water treatment and slag disposal are considered, and emissions asso-

ciated to their treatment are included within boundaries.

In all cases the life cycle inventories (LCIs) for the use of raw materials,

electricity and others are gathered from the Ecoinvent database [8].

Using the results gathered in Table 1 together with the results from each sce-

nario the LCIs are gathered and on those values the LCIA can be calculated. In this

case the environmental impact assessment technique used is the Impact 2002+ [9].

Figure 10 shows the results of the total environmental impact for each scenario.

The highest values are obtained for the case of electricity production using coal

(C21), while the lowest is found for the cases C43 and C44 where biomass is used

for the production of hydrogen. By comparing cases Ci2 and Ci1 it can be seen that

the production of electricity directly from syngas is less environmental friendly

than its production with H

, which is mainly because of the use of a hydrogen

turbine more environmental friendly than the direct combustion of syngas, and the

reduction of climate change impacts because of the CO

capture.

The environmental impact can be subdivided in terms of endpoint categories;

consequently impacts to different areas of protection can be grasped: human

health, ecosystem quality, climate change and natural resource use (as discussed in

chapter ‘‘Environmental Impact Estimation’’ i n Sect. 2.3.3). Furthermore, the same

ﬁgure can be distributed along the different activities in the supply chain: raw

Fig. 10 Environmental impact for each scenario

Selection of Best Designs for Speciﬁc Applications 269

materials (fuel consumption), energy consumption (electricity from grid and nat-

ural gas), utilities and IGCC operation. The utilities category encompass the

consumption of: limestone, NaOH, H

, water pre- and post-treatment and slag

disposal, while IGCC operation gathers all the impacts associated directly to the

IGCC, which in this case are those related to air emissions (CO

, CO and other

species).

In terms of environmental impact to different areas of protection Figs. 11–14

show the clear reduction in the climate change category obtained by shifting from

electricity directly from syngas to its production via H

, where CO

is captured. In

the case of abiotic fuels use the areas of protection more impacted are the global

Fig. 11 Environmental impact for coal–petcoke blend-based options (C

) distributed along

endpoint categories and supply chain activities

Fig. 12 Environmental impact for coal blend-based options (C

) distributed along endpoint

categories and supply chain activities

270 A. D. Bojarski and M. Pérez-Fortes

climate change and the resource use, while in the case of the biomass use, the

resource use impact is nearly negligible (see Fig. 14). Regarding the items of the

SC responsible for the environmental impact, it can be seen that in the case of

abiotic resource use (coal and petcoke), the production of fuels under the raw

materials category encompasses the largest portion of the impact, while in the case

of biomass use IGCC operation is the most important aspect (see Fig. 14). In all

cases utilities use impacts are very little, while energy consumption is noticeable in

the case of options C13, C23 and C33, where electricity from the grid is required.

Fig. 14 Environmental impact for orujillo-based options (C

) distributed along endpoint

categories and supply chain activities. Please note that vertical scale in this case has been reduced

for better representation

Fig. 13 Environmental impact for petcoke-based options (C

) distributed along endpoint

categories and supply chain activities

Selection of Best Designs for Speciﬁc Applications 271

4 Performance Assessment in Terms of Pareto Efﬁcient

Solutions

As previously discussed chapter ‘‘Global Clean Gas Process Synthesis and

Optimization’’ , Sect. 3, one of the possible ways of tackling with multicriteria

decision-making problems is the generation of Pareto frontiers (PFs), by classi-

fying alternatives in two sets: dominating and dominated solutions. This action

allows for focusing attention on a lower number of scenarios from where a

decision can be made.

In this case three KPIs have been selected for consideration: energy efﬁciency

use by considering the Eff

total

values, economic concerns are measured using the

COE, as calculated in previous sections, while environmental concerns are tackled

by using the environmental impact (EI) per unit of energy produced. In the case of

COE two considerations were done (a) one where the feedstock input is ﬁxed

disregarding the amount of power produced, while in the second case (b) the

feedstock amount is modiﬁed to attain a certain amount of total power produced.

The following Table 3 summarises the results for the scenarios considered.

Bold values in Table 3 show the best scenario for each metric, showing that

scenario C43 is the best when considering the environmental impact and the COE-

based on feed, while C34 is the best when maximising efﬁciency and minimising

COE calculated considering a ﬁxed amount of energy. Given that there is no

coincidence between the selected best scenarios for each metric, a given decision

rule has to be applied. These rules were discussed in chapter ‘‘Global Clean Gas

Process Synthesis and Optimization’’ , Sect. 3.2, where different MCDA techniques

were presented. One possibility is to apply the technique for order by similarity to

Table 3 Scenarios results

for the different metrics

considered

Eff

total

(%)

(lPts/MJ)

COE (a)

(cts €/kWh

)

COE (b)

(cts €/kWh

)

C11 42.05 72.13 5.62 5.62

C21 34.28 80.35 7.97 7.21

C31 45.72 68.72 4.58 4.89

C41 36.83 29.62 6.38 6.22

C12 33.25 65.12 7.73 7.43

C22 26.02 76.59 11.26 9.75

C32 35.82 62.01 6.45 6.61

C42 29.46 16.99 8.57 8.08

C13 44.24 48.42 3.97 4.51

C23 40.08 45.76 6.38 5.96

C33 42.85 50.53 4.33 4.53

C43 43.56 3.05 5.01 5.02

C14 54.12 32.74 3.98 4.26

C24 41.67 45.00 6.35 6.16

C34 56.70 33.46 3.67 4.16

C44 46.86 4.38 5.01 5.21

272 A. D. Bojarski and M. Pérez-Fortes

ideal solution (TOPSIS). This technique, proposed by Hwang and Yoon [10], uses

the euclidean distances from each scenario to the ‘utopian’ and ‘nadir’ solutions are

to select better solutions; two possibilities can be selected: the solution from the

Pareto fsront (PF) which is closest to the utopian point or the one farthest from

the nadir point. Please note that the utopian and nadir points are deﬁned considering

the values of the solutions only pertaining to the PF. Regarding the utopian solution

it would be formed by and hypothetical scenario that would achieve the best possible

value for all criteria considered. The analysis of efﬁcient solutions in terms of

efﬁciency and environmental impact can be seen in Fig. 15.

The Pareto front for the case of efﬁciency and environmental impact considers

scenarios: C43, C44, C14 and C34, clearly showing that from these points of view

option 4 for blends, petcoke and biomass dominates all other scenarios. The closest

scenario to utopian point is C44, while the farthest from nadir is C43, showing that

biomass is the fuel to use when considering these two objectives. In the case of

efﬁciency and COE, two Pareto analyses can be performed; one considering each

COE, results are shown in Fig. 16.

In the case of comparing COE and efﬁciency, scenario C34 dominates all others

showing that petcoke use for producing hydrogen is the most efﬁcient and more

proﬁtable in terms of COE. In the case of comparing COE and environmental

impact, the trade-offs are shown in Fig. 17.

The Pareto front for the case of COE and environmental impact considers

scenarios: C43, C44, C14 and C34, which coincides with the one found for the

case of efﬁciency and environmental impact. Note that in the case of the calcu-

lation of COE based on the same amount of energy scenario C44 is not included in

the PF. In both cases the solution is that TOPSIS will select C43, which is closest

to utopian point and also is farthest from nadir.

25 30 35 40 45 50 55 60

nadir

utopian

C11

C21

C31

C41

C12

C22

C32

C42

C13

C23

C33

C43

C14

C24

C34

C44

Eff

total

[%]

Environmental impact [µPts/MJ]

Fig. 15 Pareto front

considering the efﬁciency and

environmental impact of the

scenarios. Blue circles show

dominated scenarios, blue

dots show dominating

solutions and stars denote

utopian and nadir points. Red

cross shows scenarios farthest

from nadir and red circle

shows scenarios closest to

utopian point

Selection of Best Designs for Speciﬁc Applications 273

5 Conclusion

The most representative output data is shown, and the described points of view,

discussed in chapter ‘‘Global Clean Gas Process Synthesis and Optimization’’, are

here evaluated under a techno-economic and environmental assessment. Sixteen

scenarios are considered encompassing four different feedstocks’ combined with

25 30 35 40 45 50 55 60

C11

C21

C31

C41

C12

C22

C32

C42

C13

C23

C33

C43

C14

C24

C34

C44

Eff

total

[%]

COE [cts /kWh

]

25 30 35 40 45 50 55 60

C11

C21

C31

C41

C12

C22

C32

C42

C13

C23

C33

C43

C14

C24

C34

C44

Eff

total

[%]

COE [cts /kWh

]

(a)

(b)

Fig. 16 Pareto front considering the scenarios efﬁciency and cost of energy. Left ﬁgure shows

COE based on ﬁxed feedstock input, whereas right shows COE based on ﬁxed amount of energy.

Blue circles show dominated scenarios and blue dots show dominating solutions

0 10 20 30 40 50 60 70 80 90

nadir

utopian

C11

C21

C31

C41

C12

C22

C32

C42

C13

C23

C33

C43

C14

C24

C34

C44

Environmental impact [µPts/MJ]

COE [cts /kWh

]

0 10 20 30 40 50 60 70 80 90

nadir

utopian

C11

C21

C31

C41

C12

C22

C32

C42

C13

C23

C33

C43

C14

C24

C34

C44

Environmental impact [µPts/MJ]

COE [cts /kWh

]

(a)

(b)

Fig. 17 Pareto front considering the environmental impact and cost of energy of the scenarios.

Left ﬁgure shows COE based on ﬁxed feedstock input, whereas right shows COE based on ﬁxed

amount of energy. Blue circles show dominated scenarios, blue dots show dominating solutions

and stars denote utopian and nadir points. The red cross shows scenarios farthest from nadir and

red circle shows scenarios closest to utopian point

274 A. D. Bojarski and M. Pérez-Fortes

four different plant topologies; electricity generation with syngas, electricity

generation with hydrogen, hydrogen production and hydrogen production with

PSA ﬂue gas proﬁt in the CC. This chapter has discussed the selection of pro-

cessing options in terms of different metrics. The approach used considers all

objectives to be equally important, but this can be easily modiﬁed if different

trade-offs are required. The former approach is readily used as a decision-making

aid tool.

References

1. Hamelink CN, Faaij APC (2002) Future prospects for production of methanol and hydrogen

from biomass. J Power Sources 111:1–22

2. Chiesa P, Consonni S, Kreutz T, Williams R (2005) Co-production of hydrogen, electricity

and CO

from coal with commercially ready technology. Part A: performance and emissions.

Int J Hydrogen Energy 30:747–767

3. Kreutz T, Williams R, Consonni S, Chiesa P (2005) Co-production of hydrogen, electricity

and CO

from coal with commercially ready technology. Part B: economic analysis. Int J

Hydrogen Energy 30:769–784

4. Rubin ES, Chen C, Rao AB (2007) Cost and performance of fossil fuel power plants with

capture and storage. Energy Policy 35:4444–4454

5. Chen C, Rubin E (2009) CO

control technology effects on IGCC plant performance and cost.

Energy Policy 37:915–924

6. Brown D, Gassner M, Fuchino T, Maréchal F (2009) Thermo-economic analysis for the

optimal conceptual design of biomass gasiﬁcation energy conversion systems. Appl Therm

Eng 29:2137–2152

7. Van Vliet OPR, Faaij APC, Turkenburg WC (2009) Fischer–Tropsch diesel production in a

well-to-wheel perspective: a carbon, energy ﬂow and cost analysis. Energy Convers Manag

50:855–876

8. Ecoinvent (2008) The Ecoinvent database V2.0. Technical Report, Swiss Centre for Life

Cycle Inventories, Switzerland

9. Humbert S, Margni M, Jolliet O (2005) IMPACT 2002+: user guide draft for version 2.1.

Technical report from Industrial Ecology & Life Cycle Systems Group, GECOS, Swiss

Federal Institute of Technology Lausanne (EPFL). Lausanne, Switzerland

10. Hwang C, Yoon K (1981) Multiple attribute decision making. Springer-Verlag, Berlin

Selection of Best Designs for Speciﬁc Applications 275

Examples of Industrial Applications

Pilar Coca, Mar Pérez-Fortes and Aarón D. Bojarski

Abstract The description of the 335 MWe

ISO

coal-based Puertollano IGCC

power plant as example of industrial application of IGCC technology together

with its main lessons learnt are summarised in this chapter. This chapter includes

process description, syngas analysis, main operational real data (power production

and emissions), and main causes of unavailability as well as R&D lines. These

are mainly focused on improvement of IGCC technology taking into account

efﬁciency increase and emissions reduction. So, ﬁrst results of the CO

capture

and H

co-production 14MW

pilot plant installed in the Puertollano IGCC are

included.

Notation

ASU Air separation unit

CC Combined cycle

CCS Carbon capture and storage

CENIT National Strategic Consortia for Technical Research (Consorcios

Estratégicos Nacionales en Investigación Técnica)

CIEMAT Spanish Research Centre (Centro de Investigaciones Energéticas,

Medioambientales y Tecnológicas)

P. Coca (&)

ELCOGAS, S. A.Ctra. Calzada de Calatrava a Puertollano Km. 27,

Apdo. Correos 200, 13500 Puertollano – (Ciudad Real), Spain

e-mail: pcoca@elcogas.es

M. Pérez-Fortes  A. D. Bojarski

Universitat Politècnica de Catalunya, ETSEIB, Diagonal 647,

08028 Barcelona, Spain

e-mail: mar.perez-fortes@upc.edu

A. D. Bojarski

e-mail: aaron.david.bojarski@upc.edu

L. Puigjaner (ed.), Syngas from Waste, Green Energy and Technology,

DOI: 10.1007/978-0-85729-540-8_12,  Springer-Verlag London Limited 2011

277

Puigjaner L. (ed.) Syngas from Waste - Emerging Technologies

Подождите немного. Документ загружается.