Rudolf Braun and Roland Kirchmayr · 2013. 7. 31. · • Benchmarking with Data Envelopment...

IEA Seminar Ludlow – April 17, 2008 R. Braun & R. Kirchmayr

Results

of 41 Co-digestion Digestion Plants

in AustriaRudolf Braun and Roland Kirchmayr

BOKU - University of Natural Resources and Applied Life Sciences, Vienna Department for Agrobiotechnology, IFA-Tulln Institute for Environmental Biotechnology

Ludlow, April 17, 2008


CONTENTS

• Development of energy crop digestion• Acquisition of performance data from 41 biogas plants• Evaluation parameters elaborated• Compiled performance data • Benchmarking with Data Envelopment Analysis• Conclusions


Development

of energy

crop

digestion

in Austria

0

50

100

150

200

250

300

350

2003 2004 2005YEAR

Num

ber,

inst

. cap

acity

[MW

el]

Number of plants Installed capacity

Austrian Eco Electricity Act (2002)

Ökostromgesetz

BGBl. I Nr. 2002/149Inst. capacity

(kW)

Feed-in tariff

(ct./kWh)*

< 100 16.5100-500 14.5

500-1000 12.5> 1,000 10.3

*) 25 % reduction in case of co-digestion of defined co-substrates; consent must be achieved by end of 2004


Biogas Plants in AustriaData: e-control Austria

0

10

20

30

40

50

60

70

80

90

100

Dez.01 Apr.02 Aug.02 Dez.02 Apr.03 Aug.03 Dez.03 Apr.04 Aug.04 Dez.04 Apr.05 Aug.05 Dez.05 Apr.06 Aug.06 Dez.06

YEAR

Pow

er [

MW

]

0

40

80

120

160

200

240

280

320

360

400

Num

ber o

f Pla

nts

Power approvedPower constructedNumber approvedNumber constructed


Plants

in operation

Plants

under construction

Plants

shutdown

Approximately

350 Agricultural

biogas

plants

in Austria


1 A

1 B

2 A

2 B

3

4

Renewable raw materials

Bio-waste, by-products

Substrate preparation & dosage into digesters

Biogas use for power generation and /or upgrading to fuel

Use of digestate as fertilzer and/or compost


23 % of existing biogas plants (2004)43 % of biogas electricity supplied (2004)

1. Representative sample of 41 biogas plants


General functional description Measurable process conditions Calculable variables SUBSTRATE

Quality / quantity Transport, Storage

Pretreatment Costs

COD1

TKN2, NH4-N TS3, VS4

t / year Costs/year

DIGESTER Startup

Investment costs, Annual costs Subsidies

Process steps, Substrate dosage Digester type

Digester equipment Digester mixing

T, Self heating pH, VFA5,

COD, TS, VS TKN, NH4-N

Process energy demand Sludge recirculation

Residence time Hydraulic loading VS degradation

Biogas yield

DIGESTATE Storage type / cover

Treatment / Dewatering Use

pH, COD, TS, VS VFA, TKN, NH4-N, CH4-formation

Hygienic status

t / year

BIOGAS Quantity /utilisation

Gas holder, Upgrading CH4, H2S Calorific value

Electrical efficiency

PERSONNEL EXPENDITURE SALES REVENUES / OVERALL ECONOMICS

ECOLOGICAL / SOCIO-ECONOMIC PERFORMANCE

1) Chemical Oxygen Demand; 2) Total Kjelldahl Nitrogen; 3) Total Solids; 4) Volatile Solids; 5) Volatile Fatty Acids

2. Parameters applied for evaluation of the biogas plants


Parameter Unit Median min. max.

Amount of processed substrate tSubstrate/d 13.2 0.8 58.9 Hydraulic retention time m³RV/(tSubstrate/d) 131 44 483 Organic load (dry substance) kgVS/(m³RV·d) 3.59 1.04 7.97 COD load kgCOD/(m³RV·d) 5.64 1.62 11.95 Amount of VS tVS/d 2.34 0.33 13.78 Biogas generation Nm³biogas/d 1,461 233 10.115 Biogas productivity Nm³biogas/(m³RV·d) 0.96 0.22 2.17 Carbon degradation % 82.8 61.5 96.8 Average biogas yield Nm³biogas/kgVS 0.662 0.511 0.878 Methane content in biogas % 54.8 49.7 67.0 Electrical efficiency % 31.3 20.7 39.2 Use of heat (related to total input energy Hu, biogas)

% 16.5 0.0 42.6

Annual use efficiency (related to total input energy Hu, biogas)

% 47.3 30.5 72.3

RV: Reactor volume; Hu, biogas: Net calorific value of biogas; VS: Organic matter

3. Performance figures of the technical monitoring and benchmarking


Used substrates (% VS)

0%

20%

40%

60%

80%

100%

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41

biogas-plant-number

used

sub

stra

tes

[% V

S]

energy crops % manure % co-substrates % bio-waste %


Hydraulic retention time and organic load

2,92

4,614,15

3,473,18

0

7

14

21

28

35

42

49

< 30 30-60 60-90 90-120 120-150 > 150hydraulic retention time [d]

rel.

freq

uenc

y [%

]

0

1

2

3

4

5

6

7

orga

nic

load

[kg V

S/(m

³ RV.

d)]

hydraulic retention time organic load


Plant size (kWel) and reactor volume (RV)

0

4

8

12

16

20

24

28

32

36

1672≤ 1000≤ 500≤ 250≤ 100≤ 50installed electrical power [kWel]

rel.

freq

uenc

y [%

]

0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

16.000

18.000

tota

l RV

[m³]

el. power total RV


Utilisation of fuel energy

0

10

20

30

40

50

60

70

80

1672≤ 1000≤ 500≤ 250≤ 100≤ 50installed el. power [kWhel]

Deg

ree

of u

tilis

atio

n of

fuel

-ene

rgy

[%]

Degree of electrical efficiency Thermal usage of fuel energy


Methane-yield [VS]

0

5

10

15

20

25

30

35

40

> 500450-500400-450350-400300-350250-300CH4-yield [Nm³/tVS]

rel.

freq

uenc

y [%

]

carbohydrates proteins fats


Investvestment costs

0

2.000

4.000

6.000

8.000

10.000

12.000

0 200 400 600 800 1000 1200 1400 1600Plant size [kWel]

Inve

stm

ent c

osts

[€in

v/kW

inst

]

bio-waste

energy crops


• Best practise benchmarking model

• Non-parametric

linear programming

tool

• Comparative efficiency measurement

• Production efficiency frontier

investment costsrunning costs

personnel expenditureraw materials

fossil fuels

net energy production heat usesales revenuesmethane yieldemissions

Benchmarking by means of Data Envelopment Analysis (DEA)


(inputs used: amount of organic dry substance, time effort; outputs used: net electricity production and total heat production)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

30212

186

2036101922158

404

313

41169

12171

237

432414282933263234135

3542

Pla

nt N

o.

Efficiency Score

Relative efficiency

I


0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

30212

2018176

1512223610408

1941163

319

334

24287

231

431432293426135

4235

Pla

nt N

o.

Efficiency Score

Relative efficiency

II

(inputs used: organic dry substance and time effort; outputs used: electricity fed into the grid, total heat production)


CONCLUSIONS

• A clearer picture of the technical performance of energy crop digestion could be drawn

• Reasons for specifically good or poor performing plants could be identified

• Experiences from best practice biogas plants can avoid poor technological development and implementation


Acknowledgement

This project is accomplished within the framework of the research programme "Energy Systems of Tomorrow" - an initiative of the Austrian Federal Ministry for Transport, Innovation, and Technology (BMVIT).

Thank

you

for

your

attention!


Contact

Rudolf Braun

BOKU -

University of Natural Resources and Applied Life Sciences, Vienna

Department for Agrobiotechnology, IFA-TullnInstitute for Environmental Biotechnology

Konrad Lorenz-Straße 20 A-3430 TullnTel.: +43 2272 / 66280 / 501Fax: +43 2272 / 66280 / 503 [email protected]://www.ifa-tulln.ac.athttp://www.boku.ac.at

Rudolf Braun and Roland Kirchmayr · 2013. 7. 31. · • Benchmarking with Data Envelopment...

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