New Measuring Methods for Commercial Scale

Biogas Plants

Marcel Pohl, Jan Postel

Large Scale Bioenergy Lab 2 workshop, 29.01.2018, Sankelmark Academy

The Deutsches Biomasseforschungszentrum

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As per: summer 2015

Pictures: DBFZ / Jan Gutzeit

Applied scientific research at the DBFZ

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Research biogas plant Combustion lab Fuel conditioning lab

Fuel technical centre Engine test bed Analytical lab

What we can do for you

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Applied R&D troughout the value chain

National and international networking across the whole research landscape

Creation of scientifically sound decision-making aids for policy-makers,

businesses and other institutions

In short: we are the leading institute in bioenergy research

Ownership and decision-making structure

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MINISTRIES IN THE DBFZ SUPERVISORY BOARD

BMEL: Federal Ministry of Food and Agriculture

BMBF: Federal Ministry of Education and Research

BMUB: Federal Ministry for the Environment, Nature Conservation,

Building and Nuclear Safety

BMVI: Federal Ministry of Transport and Digital Infrastructure

BMWi: Federal Ministry of Economics and Energy

SMUL: Saxon Ministry of the Environment and Agriculture

Steps towards smart bioenergy

6Picture: DBFZ according to Daniela Thrän (Ed.): "Smart Bioenergy", Springer 2015

The research focus areas at the DBFZ

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Paths from biomass into the energy system

8Copyright: DBFZ, 2012

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Focus: waste and residues

151.1 Mio. t DM Theoretical potential

- 43.1 Mio. t DM Not usable (Restriction)

- 09.7 Mio. t DM Unclear data

= 98.4 Mio. t DM Technical potential

- 29.7 Mio. t DM Material use

- 26.9 Mio. t DM Energetic use

- 07.3 Mio. t DM Material or energetic use

- 03.5 Mio. t DM Unclear usage

= 30.9 Mio. t TS Unused potential

(Discrepancies due to rounding)

Biomass potentials from Waste and residues

And their actual use – Status quo in Germany

77 Single biomasses have been considered

Time references are not uniform

Source: Brosowski et al. 2015

Current challenges for biogas technology

● Flexibilisation, on-demand energy supply

● High efficiency of conversion processes

● Utilisation of currently un(der)used potential

• Adaptation of process technologies to „new“ substrate streams

● High utilization ratios of the energy provided (electricity and heat)

● Reduction of emissions and losses (GWPCH4 = 86 * GWPCO2)

● Coupling of material and energetic use of biomass11

Run times of back up flares

12 (Source: DBFZ operator‘s survey, 2015)

• Run times define losses

• If not automatically triggered emissions climate-relevant

class

Avg. gas storage filling level at normal operation, upper and lower limit [%]

Flare events [count/yr]

Run times, median [h/yr]

Ga

s s

tora

ge

fillin

g le

vel [%

]

Fla

re e

ven

ts [

co

un

t/yr

]

an

d

Ru

n t

ime

s,

me

dia

n [

h/yr

]

Pressure relief valves

13

From operator‘s statements, unverified. Volumetric flows remain unclear.(Source: DBFZ operator‘s survey, 2015)

Relative abundance [%]

Cla

ss [

kW

el]

> once a week

once a week

once a month

once a quarter

once a year

Pressure relief valve release events

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(Source: DBFZ operator‘s survey, 2015), n = 31

No gas utilization

Weather conditions

CHP downtime

Flare failure

Substrate change

No knowledge

others

Efficiency - approach

What data is required to evaluate a biogas plant?

1. Mass balance of in- and output

2. Energy balance of the biogas plant

3. Data of the plant performance and reliability of the equipment (hours/year)

4. Normative-actual value comparison

What is needed for the mass/energy balances and the reliability data?

1. Characterization of substrates

2. Analysis and evaluation of process characteristics & plant concept

3. Theoretical energy output as basis for the biogas plant evaluation

4. Assessment and monitoring of losses during the fermentation process

5. Possibilities for system optimization / performance improvements

15

16

Energy balancing of an

AD plant

System boundary

Error analysis – data acquisition on site

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Measuring system Data collection Source of error Suitable for balancing?

Constant weighing of solids

input

automatic Load cells Yes

manual Load cells

Transcription error

Yes

Singular weighing +

consequent counting of

volumetric flow

manual Load cells

Transcription error

Filling level

Properties of substrate

Doubtful

Solids input

Measuring system Data collection Source of error Suitable for balancing?

Flow meters

Weighing of volumes

automatic Counter Yes

manual Counter

Transcription error

Yes

Counting of solid volumes manual Filling level Doubtful

No measurement No

Digestate amount

System boundaries

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Substrate

provision

Biogas

production

Biogas

conversion

Biogas plant

Gross energy

Net energy

Usable energy

Heat use

Power grid

© DBFZ, 2016

Mean fuel efficiency based energy balanceApplying an energy industry`s assessment standard

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Efficiency assessmentFoTS-related gross energy yields

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0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

0,4 0,5 0,6 0,7 0,8 0,9 1,0 1,1 1,2

Arb

eit

sau

snu

tzu

ng

[-]

Kapazitätszahl [-] (FoTS-Bezug)

BGA06BGA 05

BGA 09

BGA 01

BGA 04

BGA 03

BGA 07

BGA 08

BGA 02

BGA 10

𝐾 =𝑃𝑁 + 𝑄 𝑁Σ 𝑚 𝑖 ∙ 𝐻𝑆,𝑖

𝑛𝐴

=𝑊

𝑒𝑙,𝑏𝑟𝑢𝑡𝑡𝑜

+𝑄𝑏𝑟𝑢𝑡𝑡𝑜

(𝑃𝑁

+𝑄 𝑁

)∙𝑇

𝑁

Insufficient

biogas utilizationPlant not used to

capacity / over-built

Desired domain

Uti

liza

tio

n f

acto

r o

f m

axi

mu

m c

ap

acit

y [-

]

Capacity figure [-]

Technical appraisal based on mean fuel

efficiency ( 𝜔)

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Uti

liza

tio

n f

acto

r o

f m

axi

mu

m c

ap

acit

y [-

]

Capacity figure [-]

© DBFZ, 2016

Relative changes of energy yields

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© DBFZ, 2016

Re

lati

ve c

ha

nge

Gross energy yield Net energy yield Mean fuel efficiency

Mechanical pre-

treatment,

stirring replaced

Installation of

secondary

fermenter

Frequent

substrate changes

equalized

Direct utilization to

grid injection

Technical appraisal based on mean fuel

efficiency ( 𝜔) – sensitivity analysis

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0,00

0,20

0,40

0,60

0,80

1,00

+100%+80%+60%+40%+20%0%-20%-40%-60%-80%-100%

Bre

nn

sto

ffau

snu

tzu

ngs

grad

[-]

ParametervariationSubstratleistung Gasleistung EigenstrombedarfEigenwärmebedarf Nutzwärmemenge

© DBFZ, 2016

me

an

fu

el e

ffic

ien

cy

[-]

50 % net heat utlization

parameter variation

Substrate input

Parasitic load (heat)

Parasitic load (electricity)Gas utilization

Usable heat

AD plant balancing - conclusion

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• Mass balance as a critical point

• Actual mode of operation and key figures of AD plants often poorly measured

• Analytical (lab) errors insignificant in comparison to errors made on site

• Recommended measuring technology for upgrading

• Load cells for solids streams

• Measurement of digestate amount

• Gas quantity measurement at standard conditions (CHP and flare)

• Count of pressure relief valve events

• Influence of substrate by different degrees of fermentability

• Plant or operating state comparison based on fermentable oDM

Substrate independent balancing

Research project: BiogasFingerprint

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Objectives:

1) Establishing a quasi online cytometric method for monitoring microbial

communities (in a plug-flow digester)

2) Examining spatial distribution of microorganisms

3) Monitoring of the stability of microbial consortia during changes in

temperature, OLR or substrate composition

4) Utilization of interrelationships to evaluate process stability and

process flexibilisation

SEITE 26

Exemplified workflow

Flow cytometric measurement

The working hypothesis

Abiotic parameters

Process parameter

Feeding

o Substrate

o Organic loading

o Regime

Mixing

Temperature

Reactor design

Methane yield

FOS/TAC value

Gas composition

pH-value

org. dry matter in

sludge [%]

VFA range

Established control circuit

“Community” Sensor Feedback loop

Microbial community

Biosensor for VFA measurement in

anaerobic digestion

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• Receptor: Geobacter sp. dominated biofilm

• Transducer: Three electrode arrangement

• Signal Processing: Potentiostat / adapted switching circuit

• Signal: I / µA

Re

ce

pto

rTransducer/

Signal Processing

Signal

CH3COOH + 10 H2O

2 CO2 + 8 H3O+

8 e-

Underlying principle

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H+ Reduktion,

z.B. zu H2

e-

e-

e-

reduzierter Analyt

oxidierter Analyt + H+

Anode mit Biofilm (Rezeptor) Kathode

e- e-Strommessung

e-

e-

e-

Measurement range

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Measurement range:

0.5 – 5 mmol L-1 acetate

Measurement resolution:

> 0.25 < 1 mmol L-1 acetate

J. Kretzschmar, L.F.M. Rosa, J. Zosel, M. Mertig, J. Liebetrau, F. Harnisch, A microbial biosensor platform for in-line quantification of acetate in anaerobic digestion: potential and challenges, Chem. Eng. Technol., 39(4),

637–642, 2016

Figure: Biofilm current response on changing acetate concentrations,

data from CA and CV measurements, the boxes represent the middle

50% of each data set, whiskers indicate min and max, n=12

Proof of concept

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Figure: Biofilm current response within a semi continuous biogas

process, 10 L CSTR with maize silage and cow manure, HRT: 30 d,

OLR: 4 gVS (L d)-1, vfa measurement with GC-FID

0 200 400 600 800 1000 1200 14000

100

200

300

400

500

600

c /

mg

L-1

t / min

acetic acid (GC-FID)

sensor signal

0.02

0.04

0.06

0.08

0.10

j /

mA

cm

-2

Do promise:

• Reliable early warning indicators for process failure

• Fast response on changing process parameters (-> flexibilisation)

• Cheap alternatives to chemical analyses

But do need:

• A thorough check for cross-sensitivities

• Greater lifespans

• Higher measurement ranges

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Lab methods…

Footer

Process modelling and control

© DBFZ

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Mauky, Eric; Weinrich, Sören; Nägele, Hans-Joachim; Jacobi, Hans-

Fabian; Liebetrau, Jan; Nelles, Michael (2016): Model Predictive Control

for Demand-Driven Biogas Production in Full Scale. In: Chemical

Engineering & Technology39 (4), S. 652–664.

ManBio - Development of technical measures for

improving gas management on biogas plants

Research project ManBio 03KB094A

Background

• Control and monitoring of demand driven biogas

plants necessary

• Need for consumption and production data of the

biogas plus gas storage filling level

• Detectability of the gas storage filling level

• Operational emissions

Aims

• Minimizing gas losses

• Forecast of gas storage filling level

• higher capacity utilisation

• Development of gas extraction

strategies

• technical improvement of the storage

filling level measurement

• Development of integrated systems for

coupling the gas storage with the gas

production and the conversion units

Fermenter with gas storage

All pictures: DBFZ 35

Measurement methods

Remote sensing (overall plant emissions measurement)

On-Site (single source measurement)

Inverse dispersion modelling in combination with tunable diode laser absorption spectroscopy

Operational methane emissions on biogas

plants – pressure relief valves (PRV)

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• Main digester: sole PRV equipped with flow sensor and

temperature probe

• Digestate storage: 2 PRVs equipped with a thermocouple each

Operational methane emissions on biogas

plants – pressure relief valves

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0

10

20

30

40

50

0

30

60

90

120

150

15.08.2016 00:00 15.08.2016 06:00 15.08.2016 12:00 15.08.2016 18:00 16.08.2016 00:00

Te

mp

era

tur

in

C

Em

issi

on

sra

te

in m

3C

H4

h-1

Datum/Zeit

Emissionsrate ÜUDS Temperatur ÜUDS Lufttemperatur

Operational methane emissions on biogas

plants – reasons for PRV events

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• Changing personnel

• Ambient temperature / sun exposure

• Outage of conversion units

• Lack of knowledge on the working principle of (combined) gas

storages

• High gas storage filling levels during normal operation

DBFZ Deutsches

Biomasseforschungszentrum

gemeinnützige GmbHTorgauer Straße 116

D-04347 Leipzig

Phone: +49 (0)341 2434-112

E-Mail: info@dbfz.de

www.dbfz.de

Thank you for your attention!

Many thanks to Jörg Kretzschmar, Torsten Reinelt, and Johannes Lambrecht

for their contributions!

Contact person

Dipl.-Ing. Marcel Pohl

Group leader „biogas technology“

Biochemical conversion department

Tel.: +49 (0)341 2434-471

E-Mail: marcel.pohl@dbfz.de

Fotos: DBFZ, Jan Gutzeit, DREWAG/Peter Schubert (Titelfolie, rechts), Pixabay / CC0 Public Domain