Moisture content as a design and operational parameter for fast pyrolysis … · weekends spent working and keeping me company, my friends back in Karlsruhe Adelmo Filho, Anderson

Moisture content as a design and operational parameter for

fast pyrolysis

Frederico Gomes Fonseca

Thesis to obtain the Master of Science Degree in

Chemical Engineering

Supervisors Professora Ana Paula Vieira Soares Pereira Dias

Doctor Axel Funke

Examination Committee

Chairperson: Sebastião Manuel Tavares da Silva Alves

Member of the Committee: Professora Ana Paula Vieira Soares Pereira Dias

Member of the Committee: Doutor Abel Martins Rodrigues

December 2015

Instituto Superior Técnico & Karlsruhe Institute of Technology

ii

Figure 1: For the cover. Source: Pixabay


iii

“Mas é preciso morrer e nascer de novo

Semear no pó e voltar a colher

Há que ser trigo, depois ser restolho

Há que penar para aprender a viver”

Mafalda Veiga – Restolho

Dedicado à família e aos amigos.


iv


v

Acknowledgments

I would like to start by thanking Dr. Axel Funke for all the support he has given me during my work

in IKFT and the time he has taken to answer all my demands after I returned home. I’d like to thank Eng.

Daniel Richter and Andreas Niebel for their continuous work at the Technikum and for the availability to

answer my questions, also Eng. Nicole Troeger. The rest of the team in IKFT should also be thanked,

with no order in particular: Norbert Sickinger, Dr. Klaus Raffelt, Pia Griesheimer, Jessica Maier, Jessica

Heinrich and Prof. Nicolaus Dahmen. Special thanks should be given to Yannik Ille for his help with the

activity coefficients for the condensates.

Back in Lisbon, I’d like to give thanks to Prof. Ana Paula Soares Dias for the support from home

and for the time in the last stretch of the work.

This work wouldn’t have been possible without the support and all the days, the nights and

weekends spent working and keeping me company, my friends back in Karlsruhe Adelmo Filho,

Anderson Pires and Gustavo Crivelli, and in Lisbon João Filipe Falcão and Maria Leonor Jorge. Special

thanks go to Filipe Rego, for the symbiosis regarding the biomass pyrolysis theme and all the support

he’s given me, and to Nuno Bandeira, for the continuous care he has showed me during the process.

I’d also like to take time to praise the whole Erasmus experience and all the experiences I had,

and the people I met. It helped me grow as a person and greatly widened my horizons.

Last, but not the least, I’d like to thank my parents, for all the kind words, all the “saudade” we

shared and all the financial and psychological support.


vi

Resumo Analítico

Pretende-se implementar um secador a montante da já existente unidade de pirólise presente na

unidade piloto bioliq, no Campus Nord – KIT. Este secador hipotético é alimentado com palha de trigo

com a intenção de ser decomposto, originando um bio-slurry Os teores em humidade do sólido

alimentado considerados foram seco-ao-ar (9,2 % m/m) e húmido (23,6 % m/m) com o objectivo de 1,2

% m/m.

A biomassa foi submetida a pirólise rápida num reactor de parafuso, no qual o transportador de

calor foram esferas de aço. Os rendimentos obtidos para os diferentes teores de humidade foram

retirados dos resultados e implementados no modelo implementado usando Aspen Plus 8.4, e cujos

resultados serviram de base a cálculos subsequentes.

Foi avaliado o uso ao gás que é actualmente eliminado por flare, e a rentabilidade financeira do

coque produzido. Foi calculada a exigência energética da fornalha e obtido um custo aproximado em

gás natural de 800 €/ano, contrabalançado pela receita do char, 145000 €/ano.

Foram dimensionados secadores, um sistema de pré-aquecimento da biomassa, um sistema de

bomba de calor para recuperação de entalpia, e sistemas de aquecimento de ar usando calor sensível

já existente ou electricidade foram desenvolvidos. A decisão final baseou-se no custo, e foi um secador

rotativo indirecto-convectivo. O custo do investimento é de 1,8 M€ +/- 30 % (incluindo impostos,

depreciações, juros, manutenção, salários da administração) com uma área 10 m2, 4,20 m de

comprimento e 0,76 m de diâmetro, e todo o equipamento associado.

Palavras-chave: Pirólise, secagem, simulação, dimensionamento de equipamento, palha


vii

Abstract

The present work discusses the implementation of a dryer upstream to the existent pyrolysis unit

in the bioliq plant, Campus Nord – KIT. The dryer would be fed with wheat straw with the intention of

conversion to bio-slurry. The moisture contents considered for the straw were an air-dry (9,2 % wt.,

called ‘as received’), and a moist (23,6 % wt.). The target moisture content is 1,2 % wt..

The biomass was submitted to ultra-fast pyrolysis in a double screw, using steel spheres as heat

carrier. The yields obtained for the different moisture contents were implemented on the model

assembled in Aspen Plus V8.4, whose results therefore are used as foundation for further calculations.

The possibility of the use of the pyrogas, currently disposed of at the flare, was also considered,

as well as the generation of revenue from produced char. The energetic demand of the furnace was

calculated, and the use of the pyrogas plus a cost of 800€/year in natural gas was achieved, value

countered by 145000 €/year in char revenue.

Besides the dryers, a solids pre-heating system, a heat pump system, and an air heating system

using sensible heat or electricity were designed. The final decision was based on the cost, and it was

the implementation of a jacketed rotary dryer. The total investment cost is of 1,8 M€ ± 30 % (including

taxes, depreciation, interest rates, maintenance, and executive salaries), for an area of 10 m2, 4,20 m

in length, and 0,76 m in, plus all associated equipment.

Keywords: Pyrolysis, drying, simulation, equipment design, straw


viii

Contents

Acknowledgments ....................................................................................................................................v

Resumo Analítico .................................................................................................................................... vi

Abstract................................................................................................................................................... vii

Contents ................................................................................................................................................ viii

Listing of Figures ......................................................................................................................................x

Listing of Tables ...................................................................................................................................... xi

Listing of Symbols ................................................................................................................................. xiii

0. Thesis Outline ...................................................................................................................................... 1

1. Introduction .......................................................................................................................................... 2

1.1 Motivation ...................................................................................................................................... 2

1.1.1 Fossil Fuel Consumption and CO2 Emissions ........................................................................ 2

1.1.2 Biorefinery .............................................................................................................................. 6

1.2 Straw.............................................................................................................................................. 8

1.3 bioliq and Python ........................................................................................................................... 9

1.3.1 The bioliq concept .................................................................................................................. 9

1.3.2 The bioliq pilot plant .............................................................................................................. 10

1.3.3 The Python-PDU .................................................................................................................. 11

1.4 Pyrolysis ...................................................................................................................................... 12

1.4.1 Introduction to Pyrolysis ....................................................................................................... 12

1.4.2 Bio-oil valorisation ................................................................................................................ 14

1.4.3 Reaction mechanisms and modelling ................................................................................... 14

2. Plant modelling .................................................................................................................................. 16

2.1 Conditioning and analysis methodology ...................................................................................... 16

2.1.1 Laboratorial analyses ........................................................................................................... 16

2.1.2 Feedstock conditioning ......................................................................................................... 17

2.2 Reactor yields .............................................................................................................................. 17

2.3 Property Estimation ..................................................................................................................... 21

2.4 ASPEN Model for the reaction and separation part .................................................................... 22

3. Heat carrier furnace ........................................................................................................................... 25

3.1 Furnace demands ........................................................................................................................ 25

3.2 Fuel supply .................................................................................................................................. 26

3.2.1 Baseline: Burned char + Natural gas ................................................................................... 27

3.2.2 Burned char + Pyrogas (+ Natural Gas) ............................................................................... 28

3.2.3 All Char + Natural Gas ......................................................................................................... 28

3.2.4 All Char + Pyrogas ............................................................................................................... 29

3.2.5 Only Natural Gas .................................................................................................................. 29

3.2.6 Pyrogas + Natural Gas ......................................................................................................... 30

3.2.7 Conclusion ............................................................................................................................ 30

3.3 Flue gas ....................................................................................................................................... 31

4. Drying ................................................................................................................................................ 34


ix

4.1 Thermodynamics ......................................................................................................................... 35

4.1.1 Vapour-gas mixtures ............................................................................................................ 35

4.1.2 Moisture content of solids ..................................................................................................... 37

4.2 Drying Kinetics ............................................................................................................................. 37

4.3 Classification of Dryers ................................................................................................................ 40

4.3.1 Mode of Operation ................................................................................................................ 40

4.3.2 Mode of Heat Transfer.......................................................................................................... 40

4.3.3 Solid Entrainment ................................................................................................................. 41

4.3.4 Other factors ......................................................................................................................... 43

4.4 Safety Aspects of Dryer Operation .............................................................................................. 43

4.4.1 Fire Hazard in Bulk Storage ................................................................................................. 44

4.4.2 Fire and Explosion Hazard in Dryers .................................................................................... 44

4.5 Literary Review ............................................................................................................................ 47

4.5.1 Simulation in Aspen Plus ...................................................................................................... 47

4.6 Heat Balance to the Solid Phase ................................................................................................. 49

4.7 General concepts of heat recovery ............................................................................................. 51

4.7.1 Heat recovery ....................................................................................................................... 52

4.7.2 Air transport .......................................................................................................................... 62

4.8 Design of Indirect Dryers ............................................................................................................. 63

4.8.1 Screw Dryers ........................................................................................................................ 64

4.8.2 Band Dryers .......................................................................................................................... 66

4.8.3 Rotary Drum Dryers .............................................................................................................. 67

4.8.4 Fluidized Bed Dryers ............................................................................................................ 69

4.8.5 Other equipment considered ................................................................................................ 71

4.9 Design of Direct Dryers ............................................................................................................... 72

4.9.1 Conveyor Dryers ................................................................................................................... 73

4.9.2 Rotary Cascading Dryers ..................................................................................................... 74

4.9.3 Other equipment considered ................................................................................................ 76

5 Conclusion .......................................................................................................................................... 77

5.1 Cost Analysis ............................................................................................................................... 77

5.2 Future Work ................................................................................................................................. 80

Bibliography ........................................................................................................................................... 81

Appendix ....................................................................................................................................................i

A1. Deviations of the models in regards to the objective. .....................................................................i

A2. The bioliq pyrolysis plant PFD ...................................................................................................... iii

A3. Flue gas calculations for the other cases...................................................................................... iv

A4. Aspen Model Heat Exchanger values ........................................................................................... vi

A5. Flue Gas Cooling ......................................................................................................................... vii

A6. Dryer design results .................................................................................................................... viii


x

Listing of Figures

Figure 1: For the cover. Source: Pixabay ii

Figure 2 Evolution of the world coal production, in millions of tonnes. Source: [1] 2 Figure 3: Total coal imports by major importers, millions of tonnes. Source: [1] 3

Figure 4 Total coal exports by major exporters, millions of tonnes. Source: [1] 3 Figure 5 World oil production by region. Source: [2] 3

Figure 6 World oil demand by region. Source: [2] 3 Figure 7 World coal consumption. Source: [1] 3

Figure 8 World CO2 emissions by fuel. Source: [1] 4 Figure 9 Greenhouse gas emissions, by source sector, EU-28. Source: [3] 4 Figure 10 Primary energy consumption mix in Germany in 2014. Source: [4] 5

Figure 11: Model of a bio-based model flowchart for biomass feedstock. Source: [5] 6 Figure 12: Lignocellulosic feedstock biorefinery scheme. Source: [5] 7

Figure 13 Overview of the bioliq concept. Adapted from: [14] 9 Figure 14 Overview of the pyrolysis plant. Source:[15] 10

Figure 15 Scheme of the Python-PDU system. Source: [15] 11 Figure 16 Graphic that compares the phase yields between the different moisture contents. 17

Figure 17: Phase discrimination for the liquid phases produced in the Python-PDU. 18 Figure 18 Graphic. Evolution of the glycol contents on the HTC system over time. From the June 10th trial on the

Python-PDU. 20

Figure 19 Print screen of the main ASPEN model. This is from the as received case. Temperatures in °C (numbers

in ovals) and flow rates in kg/h (below the temperatures). 23

Figure 20 Drying curves: moisture content in function of the time. Adapted from: [47] 38 Figure 21 Drying curves: rate of drying in function of the dry-base moisture content. The vertical curve is the initial

moisture content, taken as the critical value for the calculation of the drying time for 90 °C. 39

Figure 22: Graphic, variation of the beta efficiency and the heat consumption of the dryers with the variation of the

feed temperature. The situation reported is for the AR-to-Dry situation. 50

Figure 23: Schematic of a simple vapour compression heat pump. Source: [91] 53 Figure 24: Twin-screw dryer-conveyor. Adapted from source: [86] 64

Figure 25: Scheme of an horizontal agitated dryer. 65 Figure 26: Picture of a tunnel dryer. Source: [88] 66

Figure 27: Scheme of a steam-tube rotary dryer. Source: [40] 68 Figure 28: Well-mixed fluidized bed dryer. Source: [40]. 69

Figure 29: Typical single pass conveyor dryer. Source:[40] 73 Figure 30: Simplified diagram of a direct-fired co-current rotary dryer. Source:[40] 74

Figure 31: The bioliq pyrolysis plant PFD iii

file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991771file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991772file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991773file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991774file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991775file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991776file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991777file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991781file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991782file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991788file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991788file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991792file:///C:/Users/Fred/Google%20Drive/Piro/Documents%20IKFT/Tese.docx%23_Toc437991800


xi

Listing of Tables

Table 1: Chemical composition of wheat straw. [9] 8

Table 2: Proximate analysis of wheat straw. [10] 8

Table 3: Analytical methodology 16

Table 4: Stream yields to implement in the Aspen models, for the AR and Moist models. The fractions are of the

biomass feed, except when stated otherwise. The sum of the dry char, HTC, LTC and pyrogas yield 100 %. 19

Table 5: Stream yields to implement in the Aspen models, for both Dry models. The fractions are of the biomass

feed, except when stated otherwise. The sum of the dry char, HTC, LTC and pyrogas yield 100 %. 19

Table 5: Yields obtained and input in the Aspen RYield reactor unit block. 20

Table 6 Wheat straw. Values of proximate and ultimate analysis used by Aspen to calculate enthalpies. The sum

of the ash content and the UA equals to 100%. 21

Table 7 Char. Values of proximate and ultimate analysis used by Aspen to calculate enthalpies. The sum of the ash

content and the UA equals to 100%. 22

Table 8 Average values of the Python-PDU. 25

Table 9 Calculated values for the bioliq system. 26

Table 10: Useful char amounts and energy values, after discounting the gasifier requirements and the stored char.

27

Table 11: Useful pyrogas amounts and energy values. 27

Table 12: Energy requirements and natural gas cost for the baseline situation. 27

Table 13: Revenue obtained from selling the pyrochar. 28

Table 14: Energy requirements and natural gas cost for the pyrochar + pyrogas situation. 28

Table 15: Energy requirements and natural gas cost for the char and natural gas situation. 28

Table 16: Energy requirements and natural gas cost for the char and pyrogas situation. 29

Table 17: Revenue obtained from selling the pyrochar. 29

Table 18: Natural gas demand and cost when it’s the only energy supplier. 29

Table 19: Energy requirements and natural gas cost for the pyrogas and natural gas situation. 30

Table 20: Oxygen demand and water formation of the fuels. 31

Table 21: Psychrometric metrics of the summer and winter airs in Karlsruhe. 32

Table 22: Flue gas characteristics for the baseline (Burned Char + Natural Gas) situation. 33

Table 23: Flue gas characteristics for the chosen (Pyrogas + Natural Gas) situation. 33

Table 24: Antoine constants for water. Source: [46] 36

Table 25: Safety values for wheat straw dust. Source: [50], [51] 46

Table 26 Comparison of energy demands and efficiencies for a dryer for the solid feed temperatures considered.

50

Table 27: CEPCI indexes. 51

Table 28: Heat exchanger values and heat carrier demands for the dry-from-AR situation. 52

Table 29: Heat exchanger values and heat carrier demands for the dry-from-moist situation. 52

Table 30: Thermodynamic data for potential refrigerants. 54

Table 31: Costs and material requirements associated with the heat pump carrier fluid. 55

Table 32: Compressor values and costs for a heat pump system. 56

Table 33: Values and costs for the evaporator. 57

Table 34: Energy potential of the chosen situation, storage of the totality of the char. 57

Table 35: Values obtained in Aspen Plus for the pre-heating of the biomass. Due to the way Aspen calculates the

heat capacity, the energy transferred is basically independent of the initial moisture content. 59

Table 36: Preheating of the biomass exchanger dimensions and costs. 60

Table 37: Heat and energy requirements for the furnace air preheating. 60

Table 38: Values of the heat transfer coefficients used to calculate the global one. Source: [40] 63

Table 39: Cost summary of the dryers without the accessory equipment. 78

Table 40: Total costs for the drying systems, including auxiliary equipment. 79

Table 41: Objective and Model obtained values for the dry char for the different models. Values in kg/h. i

Table 42: Objective and Model obtained values for the pyrogas for the different models. i

Table 43: Objective and Model obtained values for the organic condensate for the different models. ii

Table 44: Objective and Model obtained values for the aqueous condensate for the different models. ii

Table 46: Flue gas characteristics for the All Char situation. iv

Table 47: Flue gas characteristics for the All Char moist situations. iv


xii

Table 45 Flue gas characteristics for the Burning Char + Pyrogas (+ Natural Gas) situation. v

Table 48: Flue gas characteristics for the purely Natural Gas situation. v

Table 49: Heat exchanger values and heat carrier demands for the as received situation. vi

Table 50: Heat exchanger values and heat carrier demands for the moist situation. vi

Table 51: Energy characteristics of the flue gas for a summer air and AR-to-dry situation. vii

Table 52: Energy characteristics of the flue gas for a winter air and AR-to-dry situation. vii

Table 53: Energy characteristics of the flue gas for a summer air and Moist-to-dry situation. vii

Table 54: Energy characteristics of the flue gas for a winter air and Moist-to-dry situation. vii

Table 55: Design values and costs for the dimensioned screw dryers. The dimensions are present for the individual

units, the costs are for the total amount. viii

Table 56: Design values and costs for the dimensioned paddle dryers. The dimensions are present for the individual

units, the costs are for the total amount. ix

Table 57: Design values and costs for the dimensioned solid band dryers. ix

Table 58: Design values and costs for the dimensioned tunnel dryers. x

Table 59: Design values and costs for the dimensioned steam tube rotary dryers. xi

Table 60: Design values and costs for the dimensioned jacketed rotary dryers. xii

Table 61: Design values and costs for the dimensioned indirect convective fluidized bed dryers. xiii

Table 62: Design values and costs for the dimensioned flow-through conveyor dryers. xiv

Table 63: Design values and costs for the dimensioned cross-flow current dryers. xiv

Table 64: Design values and costs for the dimensioned rotary cascading counter-current dryers. xv

Table 65: Design values and costs for the dimensioned rotary cascading co-current dryers. xvi


xiii

Listing of Symbols

%RM: relative moisture content of a solid

A: area (m2)

Airfurn: air to be fed for the furnace (kg/h)

AR: as received, the straw as it is kept in storage in the bioliq, air dry. The humidity is considered not to chance throughout the year, based on values obtained through TG.

aw: activity of water

BPN: boiling point at normal pressure (°C)

Co: convection number

COP: coefficient of performance

cp, cv: heat capacity at constant pressure/volume (J/kgK, kJ/kgK)

D: diameter of the equipment (m)

DA: dry air

db.: dry base, for chemical and proximate analysis

di: internal tube diameter (m)

DME: Dimethyl Ether

Dry: as received straw previously dried in a tray dryer at 120 °C overnight

DS: dry solid

E: evaporation rate (kgV/h)

Econs: energy consumption (kJ/kgV)

EG: Ethylene glycol

F: mass flow (kg/h)

F0: initial mass flow (kg/h)

FOB: free-on-board cost

Fr: Froude number

G: gas mass flow dry base (kg/h), gas flux (kg/m2s)

GC: Gas chromatography

Gs gas mass flow (kg/h)

GWP: global warming potential

H, HB: solid hold-up (m)

h, hTP, hL: convective heat transfer coefficient, phase transfer, liquid phase (W/m2K)

Ha: absolute humidity of air (kgV/kgDA)

hf: resistance to heat transfer between the drying bed and the conductive wall

HFC: hydrofluorocarbon

hh: resistance to heat transfer between the heating medium and the conductive wall (W/m2K)

HHV: higher heating value (MJ/kg)

hm: resistance to heat transfer in the drying bed (W/m2K)

HTC/OC: the first condensate obtained, high boiling point, mostly organic

hv: resistance to heat transfer on the drying surface (W/m2K)

hw: resistance to heat transfer across the conductive wall (W/m2K)

k: adiabatic exponent; thermal conductivity (W/mK)

K: parameter of Page’s equation (eq. 4.14)

L: length of the equipment (m)

LHV: lower heating value (MJ/kg)

LTC/AC: the second condensate, mostly aqueous

M: molecular weight (g/mol); moisture content of a sample at time t (% wt.)

Me: equilibrium moisture content of a sample (% wt.)

Mf: final mass of solid sample (g, kg)


xiv

Mg: mass of the glass for weighing samples (g)

M0: initial mass of solid sample (g, kg) ; initial moisture content of a sample (% wt.)

Moist: as received straw previously moistened with deionized water

MS: mass spectrometry

mw, mg, mv: mass of water/gas/vapour (kg)

NG: natural gas

Nmix: mixing number

P: pressure of the system (bar, mmHg)

PC: critical pressure (bar)

PDU: the Process Development Unit

Pg, Pw: partial pressure of water/gas (bar, mmHg)

Pr: Prandtl number

Psat: saturation pressure at a certain temperature (mmHg)

PV: vapour pressure (bar, mmHg)

Q: energy flow (kW)

QH, QC: heat at the hot/cold sources on a Carnot cycle (kW)

RM, ψ: relative humidity of air

S: solid mass flow dry-base (kg/h)

T: temperature (°C)

TC: critical temperature (°C)

tc: time of constant-rate drying period (s, min)

tdi: time of falling-rate drying period i (s, min)

TG: Thermogravimetry

TH, TC: temperature at the hold/cold sources on a Carnot cycle (°C)

Tk: temperature of hot surface on an indirect dryer (°C)

TS: temperature of solid (°C)

U: global heat transfer coefficient (W/m2K)

u: linear velocity (m/s)

V: volume of the equipment (m3)

W%: moisture fraction of solid

Wcomb: water produced in the combustion (kg/kgfuel)

Ws: machine work on a fluid (kW)

X: absolute moisture of solid (kgW/kgDS)

X0: initial absolute moisture of solid (kgW/kgDS)

X0: initial humidity of the solid (kgW/kgDS)

Xf: final absolute moisture of solid (kgW/kgDS)

β: ratio between the amount of heat provided to the dryer and the actual used to vaporize water

ΔHvap: enthalpy of vaporization (kJ/kg)

ΔS: entropy difference (kJ/kgK)

ΔT: temperature difference (°C)

ΔTlm: logarithmic temperature difference (°C)

η, ηis, ηmech: efficiency, isentropic and mechanical

μ: dynamic viscosity (cP)

ρ: density (kg/m3)

τ, ttrial, tR, tdrying: residence time of solid in the pyrolysis trials in the Python PDU, on a generic equipment, on the dryer (s, min)

Ψ: Shah correlation

0. Thesis Outline

This work is divided into two sections. The first section is an introduction, made up of the first

chapter. The second section is composed of the 3 following chapters, and are focused on the three parts

of this work: the Aspen Plus model of the bioliq plant, the choice of fuel for the heat carrier heating up

and the dryer system design.

Starting with the Introduction. This chapter focuses on a presentation of the biomass used, the

bioliq and Python units, and some information on the pyrolysis reaction and its modelling, numerical or

in Aspen Plus.

It’s followed by the chapter 2: Plant modelling. This chapter focuses on the translation of the

results obtained in the Python PDU to the Aspen models. In this chapter all the Python results are

presented and their translation to the reactor yields applied on the models, and also the results obtained

from the models.

The third chapter, Heat carrier furnace, is focused on the choice of the fuels fed to the furnace

in which the heat carrier of the pyrolysis reactor is regenerated. As the pyrochar has a good economic

potential, and the fact that the pyrogas is, on the current design, being disposed of in a flare system, but

has some combustible potential, it was considered as a fuel. In this chapter the furnace fuel and air

demands are calculated for the different Aspen models, as well as the characterising of the flue gas

produced.

After that, the chapter four focuses on Drying. The dryer thermodynamics and kinetics are

discussed and presented, as well as an overview about dryer classification and safety aspects of dryer

operation. The calculations are presented for the heat balance of the solid phase, which sets the heat

demands of the dryers, and a discussion of the auxiliary equipment for the dryers, mainly heat sources

and available sensible heat utilization. The main equipment design is presented divided into two

sections, dependent on the main way of heat transfer. In the end of this chapter the costs are reunited

and weighed, and the most economic option is chosen.


2

1. Introduction

The work here reported concerns investigating the feasibility of a drying step upstream of the

pyrolysis reactor. This dryer would receive biomass (wheat straw), either as received (air dry) or moist

(artificially moistened). The objective of the plant is to produce a bio-slurry (a mixture of the organic

condensate and char), therefore a quality and yield assessment of the components is required.

The first goal is to compare the heat consumption and product yields of the pyrolysis and

subsequent product separation, of biomass at different moisture contents (dry, AR, moist). This was

done at the Python-PDU at Technikum-IKFT, a small scale unit meant to replicate the reality of the bioliq

plant, but with running times of 3 h instead of several days, and around 25 kg instead of 500 kg.

The second goal is to model the aforementioned system in Aspen Plus, based on the bioliq mass

flow, implementing values adapted from the Python results and the bioliq operational parameters.

The third goal is to model and select a dryer to implement, taking in consideration economical

and technical criteria. To complete it, integration of the available heat and fuel is done, as well as dryer,

exchanger and air system basic dimensioning.

1.1 Motivation

1.1.1 Fossil Fuel Consumption and CO2 Emissions

Fuels are the substances that, when heated, suffer an exothermic oxidation reaction in the

presence of oxygen from air. They are present in all earthly states, solids, liquids or gases, and can be

divided into two great groups: fossil fuels and biomass.

Fossil fuels are the product of the transformation of biomass over time under intense pressures.

For this reason, they are not renewable for the sake of human consumption. These are petroleum and

its derivations, coal and natural gas. Biomass is the name given to organic matter, especially plant

matter that can be converted to or used as fuel and is therefore regarded as a potential energy source;

this consists mainly on wood, forestry wastes, agricultural wastes and municipal and industrial wastes.

Coal reserves are large, when compared

to the remaining fossil fuels. Assuming the

current consumption rate stays constant, this

fuel can satisfy the energetic needs of the world

for the next 200 years. However, more

important than the absolute value of the

reserves, it’s its geopolitical distribution,

extraction and transportation economics. The

production of coal has been led by China since

1985. [1]

Figure 2 Evolution of the world coal production, in millions of tonnes. Source: [1]


3

The main coal importer is also the main

producer, due to lower costs of import than of

production, to feed its internal demand. The

consumption has risen steadily during the first

decade of the XX century, due to high petroleum

prices, although it’s dropping on the OCDE

countries.

Regarding the oil demand, it has raised

steadily on every territory except the OECD

members as a collective. [2] The increase of the

production of shale oil in the US has led to a drop

in the OPEC countries.

Figure 7 World coal consumption. Source: [1]

Figure 4 Total coal exports by major exporters, millions of tonnes. Source: [1]

Figure 3: Total coal imports by major importers, millions of tonnes. Source: [1]

Figure 5 World oil production by region. Source: [2] Figure 6 World oil demand by region. Source: [2]


4

Global CO2 emissions from fuel combustion

reached 31,7 Gt, with coal being the largest source of

anthropogenic, with 43,8 %. Oil had been the greatest

contributor until 2003, but the steep rise of the price led

to an increase of the use of coal. It remains the greatest

contributor on the OECD emissions. [1]

Figure 9 Greenhouse gas emissions, by source sector, EU-28. Source: [3]

Major EU initiatives to reduce greenhouse gas emissions include the development and

implementation of the EU Emissions trading system, that aims to build an international carbon trading

market, the monitoring of the implementation of the emission reduction targets in sectors other than the

EU Effort Sharing Decision, the implementation of legislation to increase the share of energy produced

by renewable sources and the global European energy efficiency to 20 % by 2020, by improving the

efficiency of buildings and household appliances and promoting reduced CO2 emissions for new vehicle

models. [3]

Greenhouse emissions on the EU-28 stood at 4,7 Gt of CO2 equivalents in 2012, a 19,2 % drop

from 1990 levels, almost reaching the 20 % objective set by the Europe 2020 growth strategy. For 2050,

the EU leaders have already endorsed a greater objective to reduce European greenhouse gas

emissions by 80 %, as part of a concerted effort by developed countries to reduce their emissions by a

similar degree. Other initiatives include the replacement or incorporation of biofuels in the passenger

transportation fuels. [3]

When analysing the German situation, its primary energy consumption is heavily dependent on

fossil fuels, especially oil, which makes the country dependant on foreign trade to fuel its energetic

Figure 8 World CO2 emissions by fuel. Source: [1]


5

demand. To answer this, the German State has implemented a program called the Energiewende

(energy transition) to transition itself to a low carbon world.

Figure 10 Primary energy consumption mix in Germany in 2014. Source: [4]

The 11,1 % share of renewable energy is dominated by an investment in the use of biomass,

biofuels and co-incineration of wastes, as less than 1 % of the organic waste in Germany is sent to a

landfill.

In that sense, the implementation of methods of replacing the dependency on foreign petroleum

derivates, by replacing them with similar products produced through biomass valorisation is

commendable and important, not only for the energy security of the country but for the health of the

global environment.


6

1.1.2 Biorefinery

The preservation and management of the different resources are fundamental political tasks that

foster the need for sustainable development in the XXI century. Sustainable economic growth requires

safe and sustainable resources for industrial production. Fossil fuels are not regarded as sustainable,

due to pollution and long-term availability issues. Due to the potentially increasing prices of these, the

feasibility of their utilization is declining, leading to the necessity of establishment of solutions that reduce

the fast consumption of these resources, as they are not renewable. [5]

The issue of sustainable fuel production has been in focus during the last years, due to the

potential conflict between food and energy crops land occupation and the increased emissions of

greenhouse gases from changes in land use. Nowadays, there’s a great necessity of research regarding

the production of food, fuel and chemical commodities in a sustainable way, minimizing the risk of land-

use changes and deforestation. [6]

A forward looking approach is the conversion of large parts of the global economy into a

sustainable bio-based economy. Nature is a permanently renewing production chain for chemicals, and

the great part of the bio-based industrial products are results of direct physical or chemical treatment

and processing of biomass. These include cellulose, starch, edible oils, protein, lignin, terpenes and

furfural. Nowadays, many important products and feedstock chemicals are produced via biochemical

materials, but only 6 billion tons (as of 2008) of the over 1011 tons of biomass yearly produced are

currently used, and only around 3 % is used in non-food applications. [5]

The term biomass encompasses any organic matter available on a renewable or recurring basis,

including dedicated energy crops and tree, agricultural food and feed crop residues, aquatic vegetation,

wood, and wastes.

Figure 11: Model of a bio-based model flowchart for biomass feedstock. Source: [5]


7

Lignocellulose feedstocks have a

great potential for biorefining, as the

material situation is good, as there is a

great availability, and conversion

products have a good position on

traditional petrochemical market. These

materials consist on three primary

chemical fractions: hemicellulose, a

polymer of pentoses, cellulose, a

polymer of hexoses (mainly glucose),

and lignin, a polymer of phenols. [5]

The structural elements of a

common refinery can be applied on a biorefinery of lignocellulose feedstock, and the raw materials are

inexpensive. However, there are set backs in the separation of the three fractions, and an efficient use

of the lignin in the chemical industry. [5]

The cellulose fraction can be hydrolized to produce glucose, which can be further processed.

Glucose is a direct precursor for the production of HMF (5-hydroxymethylfurfural), precursor of nylon 6,

as well as lubricants and solvents. The fermentation of glucose can yield ethanol, acetic or lactic acid,

acetone or butanol, among other products. [5]

The hemicellulose fraction, is processed to yield plant gum, used to make adhesives and food

additives, including thickeners, stabilizers and emulsifiers. It can also be hydrolysed, to yield xylose,

from which xylitol, a sweetener, and furfural, can be produced. [5]

The lignin scaffold contains a great amount of mono-aromatic hydrocarbons that, if isolated in an

economically efficient way, would add great revenue to the process. However, no natural enzymes are

able to split the naturally formed lignin into basic monomers. Nonetheless, it has a potential market as

a natural binder, or as a sulphur-free solid fuel. [5]

Joelsson et al. [6] describes a biorefinery system for forest residues, also lignocellulosic, and its

energetic and resource efficiency. In the devised system, the biomass is pre-treated with SO2 or steam

and dried, then fermented in a yeast culture to produce ethanol, which is distilled. The distillation residue

is decanted and the solid part split. A fraction is dried and converted to pellets, while the other is

incinerated for energy production. The liquid is submitted to anaerobic digestion for biogas production,

and its residue it’s treated and fed to the incinerator.

This example can be applied to the use of any kind of biological residue, like straw, to increase

the usefulness of said product. In the situation in study, however, the straw is decomposed

thermochemically, not biochemically, and the non-gaseous product is gasified to produce DME and

gasoline. [7]

Figure 12: Lignocellulosic feedstock biorefinery scheme. Source: [5]


8

1.2 Straw

Straw is the crop residue that consists on the dry stems and leaves left after the harvest of mostly

cereal crops. These materials are available in large quantities, usually over 50% of the harvestable

vegetation of the crop. Straws are coarse, highly fibrous roughage and are not fit for human

consumption. They have always, however, played an important role in agriculture and rural societies,

since they have many uses within the farm economy. [8]

Straw, in the strict sense, also called white straw, consists on the (air) dry stems and leaves of

small cereals (wheat, barley, oat…). In temperate countries, such as Germany, the term usually refers

to wheat straw, while in tropical places it may refer to rice straw. The name is also used as a synonym

for stover, meaning the stalks and leaves of large cereals (maize, sorghum, pearl millet), or sunflower

stalks; or as a common name for the haulms and vines of legume crops (pea, beans, lentils…), oil crops

(rapeseed, soy, groundnut…), root crops (potatoes) or textile crops (flax, linen…). [8]

Straws’, together with stoves and chaff’s, multiple uses must be taken into account when

considering their use as feedstock for the chemical or fuel industry. Their main use is as livestock feed,

but they also viable as construction, crafts and clothing material, and can be used to produce paper.

They are coarse, high-fibre, low-protein and low-digestibility roughages and play an important role as

feeders when processed, or emergency feeds during periods of drought. [8]

In agriculture, straws used to be an integral part of large-scale farming as feed and litter for

manure production, which was replaced by inorganic fertilizers and mechanization. In the advent of the

industrial revolution, straw lost much of its value, and was often burnt in the field, a practice that

continued until the implementation of environmental legislation and treatments to make the straw

digestible. At the small-scale and subsistence levels, the importance of straws grew due to the reduction

of free grazing areas. In both cases, straws continue to be a major agricultural product and provide

biomass (when ploughed), fodder and bedding, the latter returning to the soil as fertilizer. [8]

Table 1: Chemical composition of wheat straw. [9]

Component Yield (% wt. db.)

Cellulose 29-51

Hemicellulose 26-32

Lignin 16-21

Ash 4.5-9

Silica 3-7

Table 2: Proximate analysis of wheat straw. [10]

Component Yield (% wt. db.)

Fixed Carbon 17,71

Volatile Matter 75,27

Ash 7,02


9

Straws are available wherever cereal or legume grain production occurs. Assuming that cereal

straw production is slightly higher than the corresponding grain production, it can be estimated that at

least 8150 million tonnes of straw have been produced worldwide in 2014. [11]

Regarding Germany, whose population was over 82 million in 2014, with over 48 million ha of

harvested area, and around 1,5 % of the population employed in agriculture, the use of agricultural

residues as energy sources can be very important. In 2014, the total production of food in Germany was

worth around 36000 million US$. The production of cereals in 2014 was around 52 million metric tons,

a low estimate for the amount of straw produced. The net trade balance yielded German producers over

3500 M$ in 2014. [11] This means the energetic potential of biomass is quite high.

1.3 bioliq and Python

1.3.1 The bioliq concept

The bioliq project concerns the conversion of low-grade lignocellulosic biomass, such as wood or

agricultural residues to synthetic fuels or other organic chemicals.

In the original solid form, the biomass packs a low energy and volumetric density (LHV of 17,7

MJ/kg[12], bulk density of 61,36 kg/m3 (adapted from: [13]), and so the economic viability of its

transportation is limited to short distances. The first stage of bioliq is to create a web of multiple

decentralized pyrolysis plants that convert solid biomass, from a radius of circa 30 km, around the plant

into a bio-syncrude (bio-slurry) (LHV of around 20 MJ/kg[14], density close to water), with a much greater

energy and volumetric density, which allows for a more economical transportation over long distances.

The second stage is the implementation of a large scale gasification and synthesis plant that receives

the bio-syncrude and converts it into gasoline, DME (dimethyl ether) and other products.

Figure 13 Overview of the bioliq concept. Adapted from: [14]


10

1.3.2 The bioliq pilot plant

Figure 14 Overview of the pyrolysis plant. Source:[15]

The bioliq pilot plant is situated in the Campus Nord, one of the campuses of KIT, in Eggenstein-

Leopoldshafen. This plant is used to trial both stages of the concept mentioned previously, and

therefore, is composed of a pyrolysis stage and a gasification stage. The focus of this work is the

pyrolysis stage, and its PFD can be found on the appendix A2 at the end of this report.

In first hand, the solid handling consists on the biomass treatment, storage and buffer silo; the

biomass is originally stored in a shed, and it’s milled to 5 mm; and it’s fed to a silo. The biomass feed

rate is controlled by a series of screws and lifts and it’s fed to a twin-screw reactor in which the heat is

provided by the heat carrier, fed a little earlier.

The heat carrier is heated in a riser through the combustion of a fraction of the dry char, and

furnace gas; the riser works as a fluidized bed and the fluidization is aided by the injection of vapour.

The furnace works with natural gas. The flue gases pass through a cyclone, and are cooled using

sprayed water and by heating up the intake air for the furnace, and are blown with the pyrolysis gas and

burned in a flare.

The aerosol is deprived of its dry char in a cyclone, and the dry char is cooled and stored. The

cyclone gas is fed to a quenching cycle, in which it sprayed with a cooled down organic condensate; the

product is fed to a condenser, where there is another condensate spray, and an electrostatic precipitator,

to make sure the gas is clean of solids and liquids, the condensate is cooled and partially stored.

Lastly, the gas is fed to a condenser, with a quenching spray system, where the pyrogas is

removed from the top and the aqueous condensate is cooled and partially stored. The glycol and water

to fill the quench-condenser systems are added prior to the beginning of the trial.

Both quenching systems had previously been filled with glycol and water, for the organic

condensate loop and the aqueous condensate loop, respectively, equivalent to 30000 kg/h for the

bottom of the gas-liquid separator. Each trial lasts a few days, with a fresh biomass feed of 500 kg/h


11

(meaning a need for around 20-30 kg throughout the whole campaign), and the steady-state is only

achieved when the glycol content in the first condensation loop goes below a certain threshold (3-5 %),

as it’s been replaced by the organic condensate.

While the dry char is cooled and stored, the organic condensate is kept at a temperature similar

to its product exit value to keep the viscosity low enough to be easily pumped. The aqueous condensate

is separated at a low temperature, and therefore doesn’t require cooling.

1.3.3 The Python-PDU

The Python-PDU is situated on the Technikum of IKFT (Institute of Catalysis Research and

Technology - Institut für Katalyseforschung und –technologie), and tries to replicate the bioliq plant in

laboratory pilot scale. This is very useful to gather fast information regarding different biomass moisture

contents, feed rates, aggregation forms, without the expenditure associated to a full-fledged industrial

plant.

Figure 15 Scheme of the Python-PDU system. Source: [15]

The system is composed of 6 parts, as observed in the Figure 15. From the point of view of the

biomass moving through the system, it begins by being fed into a biomass buffer silo, which feeds to a

screw that controls the feed rate.

The reactor is a dual-screw system that is fed with a heat carrier, small steel balls, that supplies

the heat and are heated electrically and are re-lifted by a bucket elevator. The aerosol formed by the

pyrolysis is fed to a system of two cyclones in series that recover the dry char, the char that falls with

the heat exchanger to the bucket elevator is ignored.

The vapours, free of dry char, enter the first quenching loop, in which the gas is showered with a

cool condensate, and separate in the condensation chamber; the electrostatic precipitator makes sure


12

all the gases are free of condensates. Afterwards, the gas is fed to a heat exchanger that acts as a

second quencher-condenser, as the condensable gases are liquefied by contact with the cooled

condensate. The condenser loops are pre-filled with 12 kg of glycol and with 7 kg of water, for the

organic and the aqueous one, respectively.

Each trial lasts around 3 hours. At its end, both quenching systems are emptied and small

amounts are taken for analysis. The yield of each condensate is calculated by discounting the initial load

of the system.

The plant is fully controlled by an automatized system in a computer, except the electrostatic

precipitator which has its own manual control system. The gases pass through a GC analysis before

being blown out. The biomass is manually inserted in a buffer silo.

1.4 Pyrolysis

1.4.1 Introduction to Pyrolysis

Pyrolysis (from the Greek πυρ, meaning fire, and λύσις, a loosening) is a thermochemical process

of energetic conversion, akin to combustion, gasification or liquefaction, with the main difference residing

on the fact that pyrolysis occurs in an inert atmosphere, through the application of a temperature rise to

decompose the macromolecules into those of lower molecular weight. The pyrolytic process is not a

recent technique [16], as it has been applied to raw wood for charcoal production and for iron extraction

before the industrial age and the advent of coal mining. Kerosene was first obtained through pyrolysis

of coal and was widely used in illumination lamps. Nowadays, pyrolysis is a hot topic for the production

of liquid fuels and industrial precursors.

The application of this method yields three main products: a gas phase, called the pyrogas, a

liquid phase, known as the bio-oil, and a solid phase, called the char. The pyrogas is mostly made up

of non-condensable gases like CO, CO2, hydrogen, methane, and other light paraffins. [16] The bio-oil,

with a combined mass-based LHV similar to the biomass [17], and a water content of around 20 % wt.

[16], is made up of two phases, a light phase, made up of water and light polar substances, like acetic

acid, methanol, aldehydes and others, and a heavier phase, made up of water, phenols, furanes, sugars

and waxes, that also contains a fraction of char. This latter phase is thermally unstable, as it will

decompose easily over time and should be readily used of stored at ambient temperature or lower. [17]

The char phase is mostly formed by carbon, but retains the majority of the metals present in the biomass

[16], and has a high LHV. [18] When mixing both liquid phases and the char phase in different

proportions, a bio-slurry (a pumpable mud made of char suspended in the liquid phase) of different

energetic content is achieved and can be burned or further refined. Apart from carbon, hydrogen and

oxygen, the biomass has a small content of nitrogen, sulphur and metals. These values weren’t

considered for the simulation of the pyrolysis and subsequent separation steps.

The char can be further processed in pellets or briquettes for an augment of its density [17]. It’s

useful as solid fuel but also for soil remediation and for the production of activated charcoal. [19]


13

The yields of the pyrolytic process are influenced by the components of the biomass, which

decompose in different ways. [16] The process produces, in a first approximation, a char and a gas

phase, of which the primary are the condensable gases, and the non-condensable (secondary). The

condensates can contribute further react and produce PAH (polycyclic aromatic hydrocarbons, also

called tars) that increase the density of the heavier liquid phase, or further decompose in secondary

gases.

The decomposition of the cellulose in the biomass usually yield primary gases, while the

hemicellulose origins secondary gas, due to being more thermally unstable. [16] Due to the slower

decomposition of lignin, this contributes the most to the production of char, but also produces a fraction

of phenolic compounds that enrich the bio-oil. [18] Other biomass characteristics, like particle size and

shape, have a great influence on the reactions and yields. [16] A smaller feed particle size would offer

lower resistance to the movement of gases inside of it, diminishing the occurrence of secondary

reactions. These are favoured if the gases stay in contact with the solid bed, working as a catalyst for

cracking reactions, which lead to the formation of more char, and gas (increasing the yield in olefins)

and reduce the bio-oil yield.

The classification of the pyrolysis processes is usually done in regards to the heating rate or the

residence time of the gaseous phase. For great residence times and small heating rates, the process is

named slow pyrolysis, otherwise the name is fast pyrolysis. [16] These parameters, as well as the

reaction temperature, greatly affect the yields of the different phases.

Torrefaction (roasting) is a special subsect of pyrolysis that applies temperatures of 250-350 °C

to the biomass, lower than the remaining pyrolytic processes, and has a great yield in charcoal, using

high gas residence times (usually days), and often using air to remove some volatiles. [20]

Slow pyrolysis is also focused on the production of char, but the production of gas is also valued.

The greater difference towards carbonization is the applied temperature. Convection slow pyrolysis can

reach temperatures of around 600 °C and gas residence times of minutes, whilst carbonization doesn’t

usually rise higher than 400 °C, with a residence time of hours, or even days. High residence times and

low temperatures lead to a great proportion of char due to high prevalence of cracking reactions. [16]

By removing the gases as they are formed, keeping the residence time low, and condensing them

elsewhere, it falls in the range of fast pyrolysis. These methods are designed to yield mostly liquid

product, but also gases, limiting the residence times to mere seconds and applying very high heating

rates. Temperatures applied are usually in the range of 425-600 °C for the production of oils and over

1000 °C for the attainment a great gas phase. Flash pyrolysis is designed for a yield of over 75 % in

liquid, with residence times between 30 and 1500 ms. Ultra-fast pyrolysis is even faster, and it’s

achieved by the mixing of the biomass with an inert hot solid to obtain very fast heat transfer rates and

even smaller residence times than the flash operation. Most of the times, the pyrolysis processes

happen in continuous model, either in fixed, mobile or fluidized bed, ultra-fast, rotating cone, ablative

and vacuum. [16]


14

The method applied in the bioliq, and therefore in the Python-PDU, is an ultra-fast pyrolysis, that

uses sand or steel spheres as heat carriers, respectively.

Often prior being fed to the pyrolysis reactor, the biomass is pre-dryer to keep the moisture

content inferior to 10 % (wt.), in order for the bio-oil to have a lower water content, as it diminishes its

energetic content [18]. As the pyrolysis process only occurs after complete devolatilization of the solid,

the greater the amount of water in the biomass, the greatest the consumption of energy to ensure its

vaporization. [21] The objective of this work is mainly to justify and design this step.

1.4.2 Bio-oil valorisation

The pyrolytic bio-oil is not viable for use right away, due to low thermal stability, pH restrictions,

presence of solids and possible deposition of heavy organics, among others. Therefore, it becomes

necessary to upgrade the oils, especially those rich in oxygenated compounds, and cracking of large

molecules. [22] As the bio-syncrude generated in the plant in study is pumped directly to the gasifier,

these valorisation methods were not applied.

This treatment intents to reduce the O/C ratio and increase the H/C ratio, increasing the energetic

density of the product. Post pyrolytic upgrading implies the evaporation of the bio-oil in order to split the

phases and to reuse the catalyst, which partially degrades the present substances. [22] This is achieved

by hydrogenation, using sulphide or metal oxide on alumina or silica catalysts, and cracking reactions,

using zeolites, like H-ZSM5 with a low Si/Al ratio and high acidity, or H-Y and H-mordenite. A

disadvantage of the employment of cracking reactions is the formation of cokes in the catalyst pores,

deactivating it, and increasing costs. [22]

It can also be achieved by applying solid catalyst particles on the solid bed during the catalysis

process, leading to decomposition, cracking and deoxygenation on the same process [23], but it can be

hard to control industrially due to the wide range of reactions happened simultaneously, as pyrolysis by

itself is already a catalysed process, owed to the presence of several of metals and silica that favour

cracking, leading to gas and char formation. [22] There is, therefore, a need for very active and selective

catalysts that are resisted to deactivation, cheap and reusable.

1.4.3 Reaction mechanisms and modelling

A series of mechanisms has been slated to describe the decomposition of the biomass as of the

pyrolysis process, in which a great number of reactions occur in parallel with different activation energies

and kinetic paths [21], with some considering the biomass as a whole and others focusing on the

degradation of the lignocellulosic substances individually. [16] Non-isothermal thermogravimetry can be

used to simulate in small scale the pyrolysis process, considering multi-component decomposition

reactions. [16] These mechanisms split the biomass into its main components, which decompose in

parallel reactions, however the model can underperform the reality due to different sample morphology,

as thermogravimetric analysis use pulverized samples and pyrolysis can be fed with pellets or shreds.

[24]


15

Koufopanos et al. [25] discusses the modelling of pyrolysis in a single particle. It approximates

the pyrolysis to three reactions, the decomposition of the biomass into a solid and a gas phase, and the

reaction between these two to generate the final products. It obtains the values of the kinetic constants

and the heat/mass transfer parameters by measuring the isothermal mass change of wood sawdust and

wood cylinders.

Visconti et al. [26] models the pyrolysis reactor in Aspen Plus as a series of two reactors. In the

first, a yield reactor block, splits the biomass into reference compounds, using a FORTRAN subroutine

that calculates the yields. These reference compounds are then fed to an equilibrium reactor that works

by minimizing the Gibbs free energy of the product with phase splitting and does not require reaction

stoichiometry. However, this is only made for the production of primary gases and char, to test the

production of these gases, particularly NOx and SO2 at different temperatures, and assumes that the

residence time of the reactional mixture is long enough for the system to reach equilibrium.

Xianjun et al. present a similar situation for the pyrolysis of rice straw [27], but using a FORTRAN

block to split the biomass to the cellulose, hemicellulose, lignin and ash contents and yield block to

produce the two phases.

A different approach is to determine the yield of the products as a function of the feedstock

characteristics, as in Onarheim et al. [28] The ash is used as a catalyst, increasing the amount of gas

and char and lowering the liquid phase yield. This model uses a yield reactor to represent the pyrolysis

reactor, “preferred over equilibrium or kinetic reactors because the kinetics and reaction mechanisms

for fast pyrolysis of wood are poorly understood and would be accompanied by a certain degree of

unreliability.” The vapour quenching process is modelled with a RadFrac unit block, a rigorous column

model that is able to simulate most types of multi-stage vapour-liquid fractionation operations, also

fulfilling the requirements of simulating a two-phase system, including a strongly non-ideal liquid phase.

It also simulates a char burner to provide heat to both the reactor and the pre-treatment phase using a

stoichiometric reactor. This model is focused on the yield of bio-oil in function of temperature and

feedstock variations.

Ward et al. [29] mentions the unfeasibility of any other reactor other than a yield model to model

processes that involve solid, liquid and gas phase components. However, it employs a Gibbs reactor to

model the reactors occurring and the resulting temperatures.


16

2. Plant modelling

2.1 Conditioning and analysis methodology

2.1.1 Laboratorial analyses

The analyses from which the values used on the modelling of the system and design of the dryers

and auxiliary equipment were done in a laboratory situated in the installations of IKFT.

Table 3: Analytical methodology

Biomass Char

Organic Condensate

Aqueous Condensate

Moisture content

DIN EN 14774-3: (prEN ISO 18134) Drying at 105 °C;

(±0.2 %)

DIN EN 14774-3: Drying at 105 °C;

(±0.1 %)

Volumetric Karl-Fischer-Titration

(MetOH with Hydranal-

Composit-V)

(±1.5 %)

Volumetric Karl-Fischer-Titration

(MetOH with Hydranal-

Composit-V)

Higher Heating Value

DIN EN 14918:

Bomb calorimeter

(±100 J g-1)

DIN 51900-2/3:

Bomb calorimeter

(±200 J g-1)

DIN EN 14918:

Bomb calorimeter

(±50 J g-1)

-

Ash Content

DIN EN 14775

(prEN ISO 18122):

60 min @ 250 °C,

120 min @ 550 °C

(atmospheric conditions)

(±0.2 %)

DIN EN 14775

(prEN ISO 18122):

60 min @ 250 °C,

120 min @ 550 °C

(atmospheric conditions)

(±0.5 %)

- -

Carbon, hydrogen,

and nitrogen contents

DIN EN 15104:

Elemental analysis


17

2.1.2 Feedstock conditioning

The Python-PDU doesn’t include a dryer unit since its objective in the light of this work would be

to compare the yields of the different phases for the different moisture contents. In that sense, the air

dry (as received) straw had to be “manually” conditioned to achieve the right moisture content. These

can be found in Table 7.

The input amount of conditioned was around 25000 g in dry base. The moisture content was

measured by taking small samples of the straw, after conditioning if applicable, and compare its weight

before and after drying. The moisture content was obtained by 𝑊%(𝑤𝑡. ) = 100 −𝑀0−𝑀𝑔

𝑀𝑓−𝑀𝑔, in which M0 is

the initial mass of the sample glass plus the original biomass, Mg is the mass of the sample glass and

Mf is the mass of the sample glass plus the biomass after drying. The standard deviation of the as

received situation is 0,20 % (wt.).

The drying of the straw was done in tray batch convection dryers, at 120 °C, overnight, with a

calculated standard deviation of 0,40 %(wt.).

The moistening of the straw was achieved by spraying deionized water on piles of straw, then

gathering it on sealed barrels, and letting it stay overnight, repeating the process if the target moisture

content (at least 20 %(wt.)) wasn’t achieved. The calculated standard deviation of the moisture content

is 0,04 % (wt.).

2.2 Reactor yields

From the results obtained in the Python-PDU, the best results from each part were averaged and

are presented in the histograms below (Figure 16). In the Python, as in the bioliq, the bio-oil is split into

two phases due to the high amount of ash in the feedstock that facilitates the production of water,

therefore generating an aqueous phase.

Figure 16 Graphic that compares the phase yields between the different moisture contents.

On a first approximation, when comparing the yields of the different phases (Figure 16), and

ignoring the mass loss, the use of drier biomass yields more dry char and pyrogas, but less liquid phase,

-2,8% -2,2% -4,4%

21,33% 20,36% 16,87%

43,27% 43,65% 51,87%

7,14% 11,22%10,33%

28,27% 24,77%20,93%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Dry AR Moist

Gas

AC

OC

Char


18

probably due to cracking reactions, as expected from the prior statements in the chapter 1.4.1. However,

it’s important to discriminate the constitution of the bio-oil.

Figure 17: Phase discrimination for the liquid phases produced in the Python-PDU.

The goal of the process is to produce a bio-slurry. This bio-slurry, fed to the gasifier downstream

of the pyrolysis plant, is constituted of the both condensates and some extra bio-char (25% of the LTC

in mass flow).

In that sense, when comparing the yields between the different moisture content it can be stated

that the production of condensates increased with the moisture content of the feed, but as the organic

content on the condensates (most apparent on the OC) stays roughly the same, the water content

increases, and that lowers its calorific value (10,92 MJ/kg for the moist, 17,16 MJ/kg for the as received

and 18,39 MJ/kg for the dry, all dry-ash-free averages for the organic condensate); this fact makes the

dry option the most useful for any downstream use, either gasification, fuel or valorisation. The pyrolysis

gas and char yields are also bigger for the dry biomass, which means a greater fuel value for potential

self-sustainability or to be sold, particularly the char, as the pyrolysis gas contains a great fraction of

inert (N2, CO2, some water).

The implementation of the results in the Aspen model was based on the fractions obtained in the

last bioliq campaign (as of May 2015), these were conceded by the IKFT team and are presented in

Table 4 on the As Received columns. To calculate the values for the other situations, the proportions

between the Python yields of the Dry and the Moist biomass, and the AR biomass were applied to the

fractions stated above.

The main difference between the dry models and the other two is the feed rate. On both the as

received and moist models, the feed is kept at 500 kg/h. There are two dry models for the reaction and

the separation part, as there is some mass flow lost as moisture in the drying step. The entering flow

rate can be calculated using 𝐹 = 𝐹0(𝑋0 − 𝑋𝑠), where F0 is the base flow rate (500 kg/h), X0 is the starting

33,91% 34,84% 36,89%

4,10% 2,29%2,50%

5,26% 6,53%

12,47%0,50% 0,69%

0,53%

6,64%10,52%

9,80%

0%

10%

20%

30%

40%

50%

60%

70%

Dry AR Moist

Water-AC Organics-AC Water-OC Char-OC Organics-OC


19

moisture content (0,099 kg moisture/kg dry solid for the straw as received, 0,308 kg moisture/kg dry

solid for the moist straw) and XS is the target (equilibrium) moisture content (0,012 kg moisture/kg dry

solid). The values obtained are 456,73 kg/h for the straw as received being fed to the pyrolysis reactor,

and 352,02 kg/h for the moist situation.

Table 4: Stream yields to implement in the Aspen models, for the AR and Moist models. The fractions are of the biomass feed, except when stated otherwise. The sum of the dry char, HTC, LTC and pyrogas yield 100 %.

As Received Moist

Fractions Flow Rates (kg/h) Fractions Flow Rates (kg/h)

Biomass 500,00 500

Inert Gas 51,571 51,571

Total Char 125,20 110,84

HTC Char 8,0% HTC 15,20 8,7% HTC 19,71

Dry Char 22,0% 110,00 18,2% 91,13

HTC 38,0% 190,00 45,2% 225,76

Oil HTC 174,80 206,05

Water HTC 29,98 57,05

Ethylene Glycol HTC 3,0% 5,70 2,8% 6,38

LTC 24,0% 120,00 22,1% 110,53

Water LTC 96,21 85,48

Ethylene Glycol LTC 0,45 0,41

Org LTC 23,79 25,05

Pyrogas 16,0% 131,57 14,5% 124,15

1: The inert gas is nitrogen, with an injection rate averaged between 40-50 Nm3/h.

Table 5: Stream yields to implement in the Aspen models, for both Dry models. The fractions are of the biomass feed, except when stated otherwise. The sum of the dry char, HTC, LTC and pyrogas yield 100 %.

AR-to-Dry AR-to-Moist

Fractions Flow Rates (kg/h) Flow Rates (kg/h)

Biomass 456,73 352,02

Inert Gas 51,571 51,571

Total Char 115,22 88,80

HTC Char 14,3% HTC 9,98 7,69

Dry Char 23,0% 105,24 81,11

HTC 37,7% 172,04 132,59

Oil HTC 162,05 124,90

Water HTC 21,75 16,76

Ethylene Glycol HTC 5,33 4,11

LTC 15,3% 69,74 53,75

Water LTC 30,13 23,22

Ethylene Glycol LTC 0,26 0,20

Org LTC 39,61 30,53

Pyrogas 24,0% 161,28 136,13

1: The inert gas is nitrogen, with an injection rate averaged between 40-50 Nm3/h.


20

The values for the as received case were based on the bioliq yields and the Python-PDU values

for each fraction. As reported on the Figure 2.4, the glycol levels lower quite fast for during a single

Python trial; in the bioliq power plant, each trial lasts some days and steady-state is achieved when the

EG content is around 3%, hence that choice of value. For the LTC, the water and EG values were

averaged from analysis from the last campaign, around 0,4% of the total LTC.

Figure 18 Graphic. Evolution of the glycol contents on the HTC system over time. From the June 10th trial on the Python-PDU.

The gas yields were obtained on site through GC, while the HTC and LTC were only submitted

to calorimetry, elemental analysis and EG/Moisture content determination. In light of that, the individual

component yields were adapted from MS values from a previous bioliq campaign.

Table 6: Yields obtained and input in the Aspen RYield reactor unit block.

Species AR Moist Dry

Hydrogen 0,04% 0,03% 0,05%

Oxygen 0,26% 0,39% 0,28%

Carbon Monoxide 3,98% 3,69% 6,18%

Methane 0,48% 0,42% 0,81%

Carbon Dioxide 9,40% 8,73% 14,48%

Ethylene 0,05% 0,04% 0,08%

Ethane 0,13% 0,11% 0,23%

Propane 0,16% 0,13% 0,26%

N-Butane 0,33% 0,28% 0,40%

N-Propane 0,78% 0,62% 1,00%

Water 26,04% 29,08% 12,23%

Char 25,13% 22,23% 25,47%

Acetic Acid 7,30% 7,53% 9,23%

Propionic Acid 1,55% 1,59% 1,78%

Ethylene glycol 1,23% 1,36% 1,24%

Acetaldehyde 0,97% 1,00% 1,04%

Acetol 10,11% 10,39% 11,80%

Furfural 1,82% 1,87% 2,17%

Phenol 1,55% 1,59% 1,70%

Guaiacol 2,53% 2,60% 2,77%

Methanol 0,32% 0,34% 0,59%

Syringol 2,16% 2,21% 2,31%

Levoglucosan 3,67% 3,76% 3,93%

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8

Eth

ylen

e G

lyco

l (%

)

Time (no unit)


21

2.3 Property Estimation

The modelling of the bioliq pilot plant was done in Aspen Plus 8.4. The thermodynamic method

used was unmodified UNIFAC, as it made the best liquid phase activity predictions.

The species considered on the model were nitrogen, hydrogen, carbon monoxide and dioxide,

methane, ethane, ethylene, propane, n-butane, n-pentane, oxygen, water, acetic and propionic acids,

ethylene glycol, acetaldehyde, hydroxyacetone (acetol), furfural, phenol, guaiacol, methanol, syringol

and levoglucosan. Straw and char were defined as non-conventional solids.

For the latter two, this version of Aspen Plus has very little information, so certain properties were

estimated: for syringol and levoglucosan, the Parachor (required by the McLeod-Sugden method to

estimate surface tension) was estimated using the Parachor method; only for levoglucosan: the heat of

vaporization was estimated using the Clausius-Clayperon equation, both the critical volume and

pressure were estimated using the Joback method, the critical compressibility factor was estimated

using the definition (𝑍𝑐 =𝑃𝑐𝑉𝑐

𝑅𝑇𝑐), the heat of vaporization at the normal boiling point was estimated with

the Riedel method, the acentric factor was estimated with the Lee-Kesler method and the standard heat

of formation was estimated with the Benson equation.

Both straw and wheat straw char heat capacities were averaged from the results in [30] as

1426,195 J/kg.K and 1173,341 J/kg.K , respectively. Straw and char enthalpy values were calculated

using the General Coal Enthalpy Model, using default calculation parameters, and the value of 1728,254

J/kg.K was obtained for the straw (deviation of 47% from the literature results) and, for the char,

1623,268544 J/kg.K (deviation of 14% from the literature results). Density calculations were ignored,

since there’s no need for that value in the model.

For the calculation of the values just mentioned, the user is required to provide the model both

proximal and ultimate analysis of the solids. The values used are presented on Table 7 and Table 8.

Table 7 Wheat straw. Values of proximate and ultimate analysis used by Aspen to calculate enthalpies. The sum of the ash content and the UA equals to 100%.

As Received Moist Dry

Moisture 9,25% 23,56% 1,21%

Ash 6,03% 5,33% 6,54%

Fixed Carbon1 25,66% 25,85% 25,52%

Volatile Carbon1 68,32% 68,83% 67,95%

UA-C 47,34% 47,70% 47,09%

UA-H 5,89% 5,94% 5,86%

UA-O 40,74% 41,04% 40,52%

1: Values adapted from [31]


22

Table 8 Char. Values of proximate and ultimate analysis used by Aspen to calculate enthalpies. The sum of the ash content and the UA equals to 100%.

As Received Moist Dry

Moisture 25,99% 27,09% 25,93%

Ash 4,86% 4,86% 5,38%

Fixed Carbon1 53,52% 52,72% 53,56%

Volatile Carbon1 20,49% 20,19% 20,51%

UA-C 62,66% 61,76% 63,56%

UA-H 2,90% 2,38% 2,37%

UA-O 8,45% 8,77% 8,14%

1: Values adapted from [32], [33].

2.4 ASPEN Model for the reaction and separation part

This model assumes steady-state has been reached. The stream names are taken from the bioliq

PFD (see appendix A2). The flow rates and temperatures, from the last bioliq campaign (as of May

2015), were assured in the model, but the individual component fractions and the operational pressure

deviated from the reality (see appendix A1). This has to do with limitations of the individual unit blocks

chosen to represent the equipment, and to limitations with the thermodynamic model. To simulate the

loops, although tear streams could have been used, it was decided to split the streams and initialize the

value of the re-entering stream. The initialization was done with the values that should be obtained.

The implementation of an Aspen PLUS model for any kind of industrial situation, allows for

sensitivity analyses and try-out of different situations without having to spend material and time with

extensive laboratorial or pilot tests. Due to the deviations observed, it shouldn’t be taken, as it currently

is, as an accurate representation of the reality, but it’s a good way of calculating heat and properties of

individual streams, and a good foundation for further improvement.

PYROREAC: RYield reactor unit block. Acts as a black box system, fed with an inert (INERTGAS,

nitrogen, 45 Nm3/h), and with the fresh straw (S23, conditioned). Other values given were the

temperature and the absolute pressure of the system, from the PDU results.

The simulation of a pyrolysis reaction is a very complex process, as it involves a very big number

of reactions and chemical species. Early in the works, a series of a yield reactor that divided the straw

in its elemental constituents and a Gibbs energy minimization reactor were considered, but the results

obtained weren’t very good. It was decided to calculate the yields of the system and simulate the reactor

as a black box

CYCLONE: Solids separator unit block. Separates the dry char (S28) from the aerosol (S40), and yields

a “clean gas” stream (S41). Values given were the flash temperature and pressure, from the PDU, as

well as the fraction of vapour to gas exit (taken as 100%, no gases leaving with the char), and the

fraction of solids to solids exit (varies between cases).

X-32301: Simple heat exchanger unit block. Simulates the fast loss of heat of the char from the cyclone

to the W-32301 temperature (200 °C).


23

Figure 19 Print screen of the main ASPEN model. This is from the as received case. Temperatures