Applications of the constrained Gibbs energy method in modelling thermal biomass conversion.

Similar documents
Three-dimensional modelling of steam-oxygen gasification in a circulating fluidized bed

Jet-NOx model Understanding nitrogen chemistry in biomassfired

Drying, devolatilization & char oxidation of solid fuel

Nitrogen oxide chemistry in combustion processes. Based on material originally by Prof. Mikko Hupa

ENERGY, EXERGY AND SUSTAINABILITY ANALYSIS OF RICE HUSK AIR GASIFICATION PROCESS

Department of Mechanical Engineering, University of Cagliari Piazza d Armi, Cagliari, Italia

THERMOCHEMICAL MODELING OF DIRECT CAUSTICIZATION OF BLACK LIQUOR USING SODIUM TRI-TITANATE

Modeling and Simulation of Downdraft Biomass Gasifier

MODELLING THE LOW-TAR BIG GASIFICATION CONCEPT

DETERMINATION OF AIR/FUEL AND STEAM/FUEL RATIO FOR COAL GASIFICATION PROCESS TO PRODUCE SYNTHESIS GAS

ADVANCES in NATURAL and APPLIED SCIENCES

Thermochemical Gasification of Agricultural Residues for Energetic Use

An Improved Reaction Mechanism for Combustion of Core (C 0 -C 4 ) Fuels

3D Modelling of Oxygen Fired CFB Combustors in Different Scales

Thermodynamic study of residual biomass gasification with air and steam

Customizing Syngas Specifications with E-Gas Technology Gasifier

A reduced chemical kinetics mechanism for NOx emission prediction in biomass combustion

ABE 482 Environmental Engineering in Biosystems. September 29 Lecture 11

Chapter 13. Thermal Conversion Technologies. Fundamentals of Thermal Processing

Biomass gasification gas cleaning by reforming Energy Lab 2.0 meets Neo-Carbon Energy Noora Kaisalo

Torrefaction, Pyrolysis, and Gasification- Thermal Processes for Resource Recovery and Biosolids Management

NON THERMAL PLASMA CONVERSION OF PYROGAS INTO SYNTHESIS GAS

Biomass Combustion Technology

Mikko Hupa Åbo Akademi Turku, Finland

Pyrolysis and Gasification

Hydrogen Rich Syngas Production via Underground Coal Gasification (UCG) from Turkish Lignite

Author: Andrea Milioni Chemical Engineer On Contract Cooperator University UCBM Rome (Italy)

Thermodynamic modelling of the BGLgasification. consideration of alkali metals

Fossil, Biomass, and Synthetic Fuels

A STEADY STATE MODEL FOR PREDICTING PERFORMANCE OF SMALL-SCALE UPDRAFT COAL GASIFIERS

Paper Mill Repowering with Gasification

H 2 Production from Biomass Feedstocks Utilising a Spout-Fluidised Bed Reactor

Modelling of Smelt Deposition in a Pressurized Entrained Flow Black Liquor Gasifier

Compact Gasification and Synthesis process for Transport Fuels

Process Analysis and Design: Objectives and Introduction

MECHANISMS OF PYROLYSIS. Jim Jones

TGA testing of biomass char gasification Antero Moilanen

Simulation of methanol synthesis from syngas obtained through biomass gasification using Aspen Plus

Chapter page 1

Carbon To X. Processes

Fluidised bed gasification of high-ash South African coals: An experimental and modelling study

Two-stage Gasification of Untreated and Torrefied Wood

Aspen Plus Process Model for Production of Gaseous Hydrogen via Steam Gasification of Bagasse

RECENT ADVANCES IN THE UNDERSTANDING OF PRESSURIZED BLACK LIQUOR GASIFICATION

The Novel Design of an IGCC System with Zero Carbon Emissions

Effect of Moisture Content on Composition Profiles of Producer Gas in Downdraft Biomass Gasifier


Basic Calculation Technique in Thermochemical Conversion of Biomass. Thomas Nordgreen

EVALUATION OF AN INTEGRATED BIOMASS GASIFICATION/FUEL CELL POWER PLANT

MSW Processing- Gasifier Section

Towards Energy Self-Sufficient Wastewater Treatment for Ireland. Karla Dussan and RFD Monaghan National University of Ireland Galway

SYNERGI MELLEM BIOGAS- OPGRADERING OG SOEC

CHEMICAL-LOOPING COMBUSTION (CLC) Status of development. Anders Lyngfelt, Chalmers University of Technology, Göteborg

CHAPTER 3 BENEFITS OF BETTER BURNING

Efficient Conversion of Solid Biomass into Gaseous Fuel

Development and optimization of a two-stage gasifier for heat and power production

Gasification of Biomass. Hannes Kitzler, Vienna University of Technology

Slim POX Design for Gasification 4th International Freiberg Conference on IGCC & XtL Technologies 3-5. May 2010

MODELING OF BIOMASS GASIFICATION Venko Petkov, Emil Mihailov, Nadezhda Kazakova

Thermal Conversion of Animal Manure to Biofuel. Outline. Biorefinery approaches

MILENA gasification technology for high efficient SNG production from biomass

Reforming options for H 2 and SNG manufacture via steam gasification

The Enerjetik RJ2 Gasifier. Do we finally have the right gasifying system for the Ceramic Industry?

ATTRITION OF LIGNITE CHAR DURING FLUIDIZED BED GASIFICATION: EXPERIMENTAL AND MODELING STUDIES. Paola Ammendola and Fabrizio Scala

Conversion of Biomass Particles

LARGE-SCALE PRODUCTION OF FISCHER-TROPSCH DIESEL FROM BIOMASS

Fuel Analysis and Burning Characteristics

PROCESS SIMULATION OF A ENTRAINED FLUIDIZED BED BIOMASS GASIFICATION USING ASPEN PLUS

A novel approach for the development of global kinetic models for biomass gasification

Integrated Membrane Reactor for Pre-Combustion CO 2 Capture

Integration study for alternative methanation technologies for the production of synthetic natural gas from gasified biomass

MULTI-WASTE TREATMENT AND VALORISATION BY THERMOCHEMICAL PROCESSES. Francisco Corona Encinas M Sc.

Thermal-chemical treatment of solid waste mixtures

Improved solutions for solid waste to energy conversion

THE ROLE OF CFB IN CO- COMBUSTION

Innovations in Thermal Conversion. Bill Toffey, MABA Stan Chilson, GHD-CET Biosolids Session, WaterJAM September 10, 2012

Incineration (energy recovery through complete oxidation) Mass Burn Refuse Derived Fuel Pyrolysis Gasification

Modelling of syngas production from municipal solid waste (MSW) for methanol synthesis

Biomass Gasification IEA Task 33 Country Report - Finland Piteå, Sweden

MODELING & SIMULATION OF BIOMASS GASIFIER: EFFECT OF OXYGEN ENRICHMENT AND STEAM TO AIR RATIO

Solid Carbon Conversion (Biomass & MSW) via CO 2

Lectio Praecursoria. Lappeenranta University of Technology. From the SelectedWorks of Kari Myöhänen

Supercritical Water Coal Conversion with Aquifer-Based Sequestration of CO 2

Kinetic Modeling of the Pyrolysis of Biomass

AGH w Krakowie, al. Mickiewicza 30, Kraków Instytut Chemicznej Przeróbki Wegla, ul. Zamkowa 1, Zabrze

Hydrothermal Biomass Conversion

Options to reach Syngas Quality Requirements by Catalytic Reforming of Tars and Methane from FBgasification

The Death of Coal 1957

PROCESS DEVELOPMENT AND SIMULATION FOR PRODUCTION OF FISCHER-TROPSCH LIQUIDS AND POWER VIA BIOMASS GASIFICATION

Equilibrium model of the gasification process of agro-industrial wastes for energy production Marcelo Echegaray, Rosa Rodríguez, María Rosa Castro

Simulation of Low-Btu Syngas Combustion in Trapped Vortex Combustor

Optimal design of coal gasifiers in combination with sour shift

Production of synthesis gas from liquid or gaseous hydrocarbons, and the synthesis gas per se, are covered by group C01B 3/00.

GoBiGas a First-of-a-kind-plant

Autothermal Reforming of Hydrocarbon Fuels

Biomass Conversion in Supercritical Water

Effect of Pressure and Heating Rates on Biomass Pyrolysis and Gasification

Lecture 4. Ammonia: Production and Storage - Part 1

D DAVID PUBLISHING. Numerical Simulation of Char Particle Gasification. 1. Introduction

CFD based modelling of a large-scale power plant for co-combustion of biomass gas and pulverised coal. Case: Kymijärvi power plant in Lahti, Finland.

Transcription:

VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD Applications of the constrained Gibbs energy method in modelling thermal biomass conversion GTT-Technologies' 7th Annual Users' Meeting, Herzogenrath, Germany, July -3, 205 Petteri Kangas and Pertti Koukkari VTT Technical Research Centre of Finland

In 203: CFE for in the kraft recovery boiler modelling presented in GTT Annual Users meeting 2

Methodology

Methodology Constrained Free Energy (CFE) method CFE is an extension to Gibbs free energy method where additional immaterial constraints are incorporated to chemical system Chemical system can be constrained by extent of reaction, electrochemical potential, surface area or volume The distinct benefit of this method lies in the calculation of constrained chemical reactions, enthalpic effects and state properties simultaneously and interdependently ChemSheet is applied as modelling tool, as it allows extending chemical system with virtual constraints Kangas, P 205, Dissertation, Åbo Akademi University 4

5 Chemical system is constrained by defining immaterial constraints based on the extent of reactions Non-stoichiometric chemical system is solved by minimising the Gibbs energy with Lagrange method of undetermined multipliers Additional immaterial components and constituents are implemented into system for applying chemical kinetics Methodology Constrained Free Energy (CFE) method Y L X K L K L K K Y L L L,,,,,,,, 0 0 0 0 K k L l K k l k kl l k k b n n G L 0 L l kl l k n k k n n L 0 l k K k kl l b n L l n x C x (T) f x x dt r t x x 0 xr xf x r r r b a b j k r ) / ( exp RT E B AT k (constant value) (temperature dependent model) (global and elementary kinetic reactions)

NO emissions

Modelling NO emissions with CFE Aim: Evaluate how reaction kinetic models could be implemented into CFE methodology Model thermal and fuel NO emissions CFE method Constrained thermodynamic equilibrium with major kinetic reactions implemented [2,3] ChemSheet [5] applied as modelling tool Reference and validation Pure kinetic model of combustion and NO formation ÅA mechanism 37 kinetic reactions applied ChemKin applied as modelling tool 7

(i) NO emissions - Dry air Extended stoichiometric matrix for CFE Table - Extended stoichiometric matrix; Total 60 gaseous species and 2 immaterial constraints; r : N 2 + O NO + N; r 2 : N + O 2 NO + O Phase Constituent O N N* NO* Gas O O 2 2 N N 2 2 NO NO 2 2 Constraints r : N 2 + O NO + N r 2 : N + O 2 NO + O - 8

(i) NO emissions - Dry air Synthetic air: 2 v-% of O 2 and 79 v-% of N 2 No moisture Heating air (no combustion here) Temperature range: 200-2200 C Pressure bar Zeldovich mechanism applied 2 reaction limiting NO formation r : N 2 + O NO + N r 2 : N + O 2 NO + O Local equilibrium considered otherwise (eg amount of radical O) => CFE model agrees with kinetic model when dry air is considered Figure 6 NO formation in dry air 9

(ii) NO emissions - Combustion of CO Extending stoichiometric matrix Table 3 Extended stoichiometric matrix; Total 60 gaseous species and 3 immaterial constraints; r : N 2 + O NO + N; r 2 : CO + O 2 CO 2 + O; r 3 : CO + O + M CO 2 + M Phase Constituent O C N Ar NO* O* CO* Gas CO CO 2 2 O N 2 N 2 2 NO Ar Constraints r : N 2 + O NO + N r 2 : CO + O 2 CO 2 + O - r 3 : CO + O + M CO 2 + M - - 0

(ii) NO emissions - Combustion of CO; Dry air Combustion of carbon monoxide Excess air: λ = 2 Dry air: 2 v-% of O 2 and 79 v-% of N 2 Two additional constraints for CO + O: r 2 : CO + O 2 CO 2 + O r 3 : CO + O + M CO 2 + M Simplified Zeldovich mechanism for N: r : N 2 + O NO + N NO formation during combustion (CFE) agrees with reference model (pure kinetics) when dry air is considered Figure 3 NO formation; CO combustion; 500 C; Dry air; Figure 4 NO formation; CO combustion; 500 C; Dry air;

(iii) NO emissions - Combustion of CO; Wet air Rapid combustion if moisture present Super-equilibrium of O-, H-, and OH-radicals formed Additional elementary reactions needed (O-, H- and OH- radicals) Additional constraints implemented to calculation and stoichiometric matrix is extended again Table 4 Elementary reactions for CO, wet air Constituent Reaction CO CO+OH CO 2 +H CO+O+M CO 2 +M H CO+OH CO 2 +H O+OH H+O 2 OH CO+OH CO 2 +H O+OH H+O 2 OH+OH O+O O O+OH H+O 2 CO+O+M CO 2 +M OH+OH O+O 2

(iii) NO emissions - Combustion of CO; wet air Extending stoichiometric matrix Table 5 Extended stoichiometric matrix; Total 60 gaseous species and 5 immaterial constraints; Phase Constituent O H C N Ar CO* NO* O* H* OH* Gas CO CO 2 2 2 O 2 O H O NO Ar Constraints r : ΣΔr CO r 2 : ΣΔr NO r 3 : ΣΔr O r 4 : ΣΔr H r 5 : ΣΔr OH 3

(iii) NO emissions - Combustion of CO; Quasi steady-state assumption Two competing reactions (O-radical) r 2 : CO+O 2 CO 2 +O r 3 : CO+O+M CO 2 +M Oscillation, when Δr 2 Δr 3 n O Quasi steady-state Figure 6 NO formation; Euler-method One possible solution is quasi steady-state assumption d[o]/dt=0=> k 3 [CO][O][M]=k 2 [CO][O 2 ] [O]=k 2 /k 3 *[O 2 ]/[M] Improves stability Fails close to O(eq) Figure 8 NO formation; Steady-state assumption 4

(iv) NO emissions - Combustion of CH 4 Larger amount of reactions are involved for CH 4 combustion and related Several hydrocarbons involved for NO X formation Need for extending stoichiometric matric further Several competing reactions could cause numerical problems during simulation; stiff chemical system Global kinetic model applied instead of models based on the elementary kinetic reactions Table 6 Applied global kinetic model Reaction R N+NO N 2 +O R2 CH 4 +½O 2 CO+2 R3 CH 4 + O CO+3 R4 +½O 2 O R5 O +½O 2 R6 CO+ O CO 2 + R7 NH 3 +O 2 NO+ O+½ R8 NH 3 +NO N 2 + O+½ 5

(iv) NO emissions - Combustion of CH 4 Table 6 Extended stoichiometric matrix; Total 60 gaseous species and 5 immaterial constraints; Phase Constituent O H C N Ar CH 4 * CO* NH 3 * NO* * Gas CO CO 2 2 2 O 2 O CH 4 4 NH 3 3 NO Ar Constraints r : ΣΔr CH4 r 2 : ΣΔr CO r 3 : ΣΔr NH3 r 4 : ΣΔr NO r 5 : ΣΔr H2 6

(iv) NO emissions - Combustion of CH 4 Separate models for: oxidation of methane oxidation of carbon monoxide oxidation of ammonia CFE method is applicable for modelling fuel NO emissions if global kinetic models are used => However timing is slightly off as model does not consider radical build-up 7

Gasification

Gasification - Background During biomass gasification light hydrocarbons (eg : CH 4,, H 4,, C 3 H 8, C 6 ), ammonia, tars and char are formed among syngas This affects on the composition of major species in syngas (CO, CO 2,, O) Assuming thermodynamic equilibrium the superequilibrium of hydrocarbons, ammonia, tar and char is not taken into account Phenomena based and semi-empirical models have been developed for describing the superequilibrium Phenomena based models become tedious with several parameters Current semi-empirical models provide only ad-hoc solution Aim: evaluate the use of experimental models with CFE and to study different model structures Figure Example of gasification process [] Figure 2 Example of multi-step semi-empirical model 9

Gasification - Cases with different sets of constraints EQ: Thermodynamic equilibrium is used as base case No additional constraints are defined Super-EQ: super-equilibrium where carbon conversion, tar and ammonia formation are defined is studied In addition the amount of carbon in volatile hydrocarbons (CH 4,, H 4,, C 3 H 8 and C 6 ) is fixed Super-EQ2 where previous case is extended by introducing additional constraint for the amount of hydrogen in volatile hydrocarbons Super-EQ3 replaces the hydrogen constraint by introducing a constraint for CH 4 Super-EQ4 defines the amount of carbon bound to unsaturated hydrocarbons hydrocarbons ( and H 4 ) and benzene (C 6 ) Super-EQ5 introduces a fully constrained system where the amount of every hydrocarbon constituent is defined by empirical models However the water-gas shift reaction is not constrained, but local equilibrium is assumed 20

Gasification Extended stoichiometric matrix Components: C-O-H-N-S Phases: gas (4 constituents), biomass (4), water, char and ash Extending matrix with CFE method: 2 virtual components 2 virtual constituents Extended model is used to predict the super-equilibrium of char, tar, ammonia, and light hydrocarbons in syngas Different combinations of immaterial constraints are evaluated from thermodynamic equilibrium to fully constrained system Figure 6 Extending chemical system with additional immaterial constraints 2

Gasification - EQ - stoichiometric matrix Table Extended stoichiometric matrix C-O-H-N-Si system Phases Constituents Cases C O H N Si 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 Gas phase CO 0,,2,3,4,5 0,,2,3,4,5 2 CO 2 0,,2,3,4,5 2 N 2 0,,2,3,4,5 2 O 0,,2,3,4,5 2 CH 4 0,,2,3,4,5 4 0,,2,3,4,5 2 2 H 4 0,,2,3,4,5 2 4 0,,2,3,4,5 2 6 C 3 H 8 0,,2,3,4,5 3 8 C 6 0,,2,3,4,5 6 6 C 0 H 8 0,,2,3,4,5 0 8 NH 3 0,,2,3,4,5 3 O 2 0,,2,3,4,5 2 Biomass C 0,,2,3,4,5 O 0,,2,3,4,5 H 0,,2,3,4,5 N 0,,2,3,4,5 Water O 0,,2,3,4,5 2 Char C 0,,2,3,4,5 Ash SiO 2 0,,2,3,4,5 2 No additional virtual constraints 22

Gasification Super-EQ - Extended stoichiometric matrix Table 2 Extended stoichiometric matrix C-O-H-N-Si system Phases Constituents Cases C O H N Si Char* HC_C* Tar* Amm* 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5,2,3,4,5,2,3,4,2,3,4,5 0,,2,3,4,5 Gas phase CO 0,,2,3,4,5 0,,2,3,4,5 2 CO 2 0,,2,3,4,5 2 N 2 0,,2,3,4,5 2 O 0,,2,3,4,5 2 CH 4 0,,2,3,4,5 4 0,,2,3,4,5 2 2 2 H 4 0,,2,3,4,5 2 4 2 0,,2,3,4,5 2 6 2 C 3 H 8 0,,2,3,4,5 3 8 3 C 6 0,,2,3,4,5 6 6 6 C 0 H 8 0,,2,3,4,5 0 8 0 NH 3 0,,2,3,4,5 3 O 2 0,,2,3,4,5 2 Biomass C 0,,2,3,4,5 O 0,,2,3,4,5 H 0,,2,3,4,5 N 0,,2,3,4,5 Water O 0,,2,3,4,5 2 Char C 0,,2,3,4,5 Ash SiO 2 0,,2,3,4,5 2 Constraints R_Char,2,3,4,5 R_HC_C,2,3,4 R_Tar,2,3,4,5 R_Amm,2,3,4,5 Constraints for char, tar, ammonia, and carbon in hydrocarbons 23

Gasification Super-EQ2 - Extended stoichiometric matrix Table 3 Extended stoichiometric matrix C-O-H-N-Si system Phases Constituents Cases C O H N Si Char* HC_C* HC_H* Tar* Amm* 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5,2,3,4,5,2,3,4 2,2,3,4,5 0,,2,3,4,5 Gas phase CO 0,,2,3,4,5 0,,2,3,4,5 2 CO 2 0,,2,3,4,5 2 N 2 0,,2,3,4,5 2 O 0,,2,3,4,5 2 CH 4 0,,2,3,4,5 4 4 0,,2,3,4,5 2 2 2 2 H 4 0,,2,3,4,5 2 4 2 4 0,,2,3,4,5 2 6 2 6 C 3 H 8 0,,2,3,4,5 3 8 3 8 C 6 0,,2,3,4,5 6 6 6 6 C 0 H 8 0,,2,3,4,5 0 8 0 NH 3 0,,2,3,4,5 3 O 2 0,,2,3,4,5 2 Biomass C 0,,2,3,4,5 O 0,,2,3,4,5 H 0,,2,3,4,5 N 0,,2,3,4,5 Water O 0,,2,3,4,5 2 Char C 0,,2,3,4,5 Ash SiO 2 0,,2,3,4,5 2 Constraints R_Char,2,3,4,5 R_HC_C,2,3,4 R_HC_ R_Tar,2,3,4,5 R_Amm,2,3,4,5 Constraints for char, tar, ammonia, carbon in hydrocarbons and hydrogen in hydrocarbons 24

Gasification Super-EQ3 - Extended stoichiometric matrix Table 4 Extended stoichiometric matrix C-O-H-N-Si system Phases Constituents Cases C O H N Si Char* HC_C* Tar* Amm* CH 4 * 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5,2,3,4,5,2,3,4,2,3,4,5 0,,2,3,4,5 3,5 Gas phase CO 0,,2,3,4,5 0,,2,3,4,5 2 CO 2 0,,2,3,4,5 2 N 2 0,,2,3,4,5 2 O 0,,2,3,4,5 2 CH 4 0,,2,3,4,5 4 0,,2,3,4,5 2 2 2 H 4 0,,2,3,4,5 2 4 2 0,,2,3,4,5 2 6 2 C 3 H 8 0,,2,3,4,5 3 8 3 C 6 0,,2,3,4,5 6 6 6 C 0 H 8 0,,2,3,4,5 0 8 0 NH 3 0,,2,3,4,5 3 O 2 0,,2,3,4,5 2 Biomass C 0,,2,3,4,5 O 0,,2,3,4,5 H 0,,2,3,4,5 N 0,,2,3,4,5 Water O 0,,2,3,4,5 2 Char C 0,,2,3,4,5 Ash SiO 2 0,,2,3,4,5 2 Constraints R_Char,2,3,4,5 R_HC_C,2,3,4 R_Tar,2,3,4,5 R_Amm,2,3,4,5 R_CH 4 3,5 Constraints for char, tar, ammonia, carbon in hydrocarbons and CH 4 25

Gasification Super-EQ4 - Extended stoichiometric matrix Table 5 Extended stoichiometric matrix C-O-H-N-Si system Phases Constituents Cases C O H N Si Char* HC_C* Tar* Amm* UN_C* 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5,2,3,4,5,2,3,4,2,3,4,5 0,,2,3,4,5 4 Gas phase CO 0,,2,3,4,5 0,,2,3,4,5 2 CO 2 0,,2,3,4,5 2 N 2 0,,2,3,4,5 2 O 0,,2,3,4,5 2 CH 4 0,,2,3,4,5 4 0,,2,3,4,5 2 2 2 2 H 4 0,,2,3,4,5 2 4 2 2 0,,2,3,4,5 2 6 2 C 3 H 8 0,,2,3,4,5 3 8 3 C 6 0,,2,3,4,5 6 6 6 6 C 0 H 8 0,,2,3,4,5 0 8 0 NH 3 0,,2,3,4,5 3 O 2 0,,2,3,4,5 2 Biomass C 0,,2,3,4,5 O 0,,2,3,4,5 H 0,,2,3,4,5 N 0,,2,3,4,5 Water O 0,,2,3,4,5 2 Char C 0,,2,3,4,5 Ash SiO 2 0,,2,3,4,5 2 Constraints R_Char,2,3,4,5 R_HC_C,2,3,4 R_Tar,2,3,4,5 R_Amm,2,3,4,5 R_UN_C 4 Constraints for char, tar, ammonia, carbon in hydrocarbons and carbon in unsaturated hydrocarbons + aromatics 26

Gasification Super-EQ5 - Extended stoichiometric matrix Table 6 Extended stoichiometric matrix C-O-H-N-Si system Phases Constituents Cases C O H N Si Char* Tar* Amm* CH 4 * * H 4 * * C 3 H 8 * C 6 * 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5,2,3,4,5,2,3,4,5 0,,2,3,4,5 3,5 5 5 5 5 5 Gas phase CO 0,,2,3,4,5 0,,2,3,4,5 2 CO 2 0,,2,3,4,5 2 N 2 0,,2,3,4,5 2 O 0,,2,3,4,5 2 CH 4 0,,2,3,4,5 4 0,,2,3,4,5 2 2 H 4 0,,2,3,4,5 2 4 0,,2,3,4,5 2 6 C 3 H 8 0,,2,3,4,5 3 8 C 6 0,,2,3,4,5 6 6 C 0 H 8 0,,2,3,4,5 0 8 0 NH 3 0,,2,3,4,5 3 O 2 0,,2,3,4,5 2 Biomass C 0,,2,3,4,5 O 0,,2,3,4,5 H 0,,2,3,4,5 N 0,,2,3,4,5 Water O 0,,2,3,4,5 2 Char C 0,,2,3,4,5 Ash SiO 2 0,,2,3,4,5 2 Constraints R_Char,2,3,4,5 R_Tar,2,3,4,5 R_Amm,2,3,4,5 R_CH 4 3,5 R_ 5 R_ H 4 5 R_ 5 R_C 3 H 8 5 R_C 6 5 Constraints for char, tar, ammonia, CH 4,, H 4,, C 3 H 8 and C 6 27

Gasification Full extended stoichiometric matrix Table 7 Extended stoichiometric matrix C-O-H-N-Si system Phases Constituents Cases C O H N Si Char* HC_C* HC_H* Tar* Amm* CH 4 * * H 4 * * C 3 H 8 * C 6 * UN_C* 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5 0,,2,3,4,5,2,3,4,5,2,3,4 2,2,3,4,5 0,,2,3,4,5 3,5 5 5 5 5 5 4 Gas phase CO 0,,2,3,4,5 H 0,,2,3,4,5 2 2 CO 0,,2,3,4,5 2 2 N 0,,2,3,4,5 2 2 O 0,,2,3,4,5 2 CH 0,,2,3,4,5 4 4 4 H 0,,2,3,4,5 2 2 2 2 2 2 H 0,,2,3,4,5 4 2 4 2 4 2 H 0,,2,3,4,5 6 2 6 2 6 C 3 H 0,,2,3,4,5 8 3 8 3 8 C 6 H 0,,2,3,4,5 6 6 6 6 6 6 C 0 H 0,,2,3,4,5 8 0 8 0 NH 0,,2,3,4,5 3 3 O 0,,2,3,4,5 2 2 Biomass C 0,,2,3,4,5 O 0,,2,3,4,5 H 0,,2,3,4,5 N 0,,2,3,4,5 Water O 0,,2,3,4,5 2 Char C 0,,2,3,4,5 Ash SiO 0,,2,3,4,5 2 2 Constraints R_Char,2,3,4,5 R_HC_C,2,3,4 R_HC_ R_Tar,2,3,4,5 R_Amm,2,3,4,5 R_CH 3,5 4 R_ H 5 2 R_ H 5 4 R_ H 5 6 R_C 3 H 5 8 R_8 6 H 5 6 R_UN_C 4

Gasification Applied constraints Temperature dependent constraints: carbon in char carbon in hydrocarbons hydrogen in hydrocarbons carbon in unsaturated and aromatics carbon in CH 4,, H 4,, C 3 H 8 Constant values: carbon in tar nitrogen in ammonia Table 8 Applied constraints for SuperEQ SuperEQ5 cases Experimental model is taken from literature Constraint Unit Expression Case C in char [mol/kg carbon in dry biomass ] 7664+002906*T,2,3,4,5 C in tar [mol/kg dry biomass ] 30,2,3,4,5 N in ammonia [mol/kg dry biomass ] 0042,2,3,4,5 C in hydrocarbons [mol/kg dry biomass ] 7642-0009545*T,2,3 H in hydrocarbons [mol/kg dry biomass ] 50376-002732*T 2 C in unsaturated and aromatic [mol/kg dry biomass ] 7723-000408*T 4 CH 4 [mol/kg dry biomass ] 7074-0003*T 3,5 [mol/kg dry biomass ] 006454-000004*T 5 H 4 [mol/kg dry biomass ] 2987-0002*T 5 [mol/kg dry biomass ] 96-000*T 5 C 3 H 8 [mol/kg dry biomass ] 05092-000055*T 5 C 6 [mol/kg dry biomass ] 027 5 carbon in C 6 Models based on empirical data 29

Gasification Validation Five different gasification setups modelled (A-E) Six different model construction evaluated (Cases EQ, Super- EQ-Super-EQ5) Table 9 Validation data Nitrogen removed Data from [] A B C D E C in dry biomass [w-%] 507 507 507 53 5 H in dry biomass [w-%] 62 62 62 6 6 N in dry biomass [w-%] 0 0 0 05 0 O in dry biomass [w-%] 428 428 428 395 423 Ash in dry biomass [w-%] 02 02 02 26 04 Fuel moisture [%] 69 69 69 04 74 Gasifier temp [C] 823 838 886 830 868 Pressure [MPa] 0250 0250 0250 0250 0250 Oxygen-to-fuel ratio [kg/kg dry fuel] 03 037 042 037 046 Steam-to-fuel ratio [kg/kg dry fuel] 05 054 054 054 075 CO [v-%] 044 032 033 022 003 CO 2 [v-%] 02 0220 0222 0222 0207 [v-%] 067 054 056 067 049 CH 4 [v-%] 0056 0055 0056 0056 0046 O [v-%] 0400 048 04 04 0483 30

Gasification Validation: Measured vs modelled syngas components (CO, O, CO 2, and CH 4 ) Ref: Kangas, P, et al, 204 Fuel 29, 86 94 doi:006/jfuel20403034 3

Gasification - Validation of CFE model with other gasifiers Ref: Kangas, P, et al, 204 Fuel 29, 86 94 doi:006/jfuel20403034 32

In Delft: Biomass gasification in supercritical water I 2-phase model II single SC fluid phase 0 w-% wood, 34 Mpa, 409 C 29 min 06 M-glucose, 28 Mpa, 600 C 50 sec Yakaboylu,O et al, Fuel Processing Technology, 38, (205), 74-85 33

Conclusions

Conclusions this study CFE is successfully applied for modelling biomass gasification and NO emissions Experimental model, global kinetic models and reactions based elementary kinetic reactions can be implemented as constraints in CFE calculation Requires less parameters than a mechanistic kinetic approach Best result are achieved when moderate amount of reactions are limiting the system Kangas, P 205, Dissertation, Åbo Akademi University 35

Conclusions - Other uses of kinetic constraints In chemical and metallurgical reactors for improved control of autogenic energy efficiency (up to 40 % savings in energy and/or CO 2 release) In rotary drums and other furnaces for replacement of fossil fuels with biofuel In pulp and papermaking processes for control of chemical dosage and process ph In developing new chemistry concepts for in-situ reactions 36

Conclusions CFE provides a rigorous method to include work-related and dynamic factors to min(g) Serves for quantitative calculation of both partial equilibria and para-equilibrium systems in chemistry and materials science Can be used for approximate local equilibria in complex reaction systems With accurate reaction kinetics, will provide data of reaction rate controlled local chemical equilibrium systems Has gained increasing interest with its wide applicability in both materials and process research* Overviews published in: wwwvttfi/inf/pdf/technology/204/t60pdf wwwvttfi/inf/pdf/science/205/s92pdf *https://wwwmendeleycom/groups/249358/constrained-free-energy-cfe-method/ 37