termoeconomic gasification

THERMO-ECONOMIC ANALYSIS FOR THE OPTIMAL CONCEPTUAL DESIGN

OF BIOMASS GASIFICATION ENERGY CONVERSION SYSTEMS

ASTRID YULIANA RAMIREZADRIANA PALENCIA SALGAR

INTRODUCTION

GAS CONTAMINANTS AND GAS CLEANING

ELECTRICITY PRODUCTION

THERMO-ECONOMIC OPTIMISATION

INTRODUCTION GAS CONTAMINANTS AND GAS CLEANING

ELECTRICITY PRODUCTION THERMO-ECONOMIC OPTIMISATION

IMPROVING BIOMASS GASIFIERS TECHNOLOGIES

IGCCIntegrated gasification

combined cycle

Steam injected gas turbine

Solid oxide fuel cells

O2+N2

Steam

Wood - Tar (Quantity)

- Main gas species- Hydrocarbons- Soot

- H2, CO, CO2 , and N2

- Trace species

+

O2

GASIFICATION CONDITIONS

Tar formation

Electricity generation



DESIGN PROBLEM

Identifying

Gasification conditions Gas cleaningTechnologies

Energy conversion Technologies

To minimize the contaminant formation

To obtain a high net conversion efficiency

Tar deposits are an economical bottleneck to gasification(Equipment shutdowns)

Review of gas cleaning technologies Gasification process

Optimization



TAROrganic contaminants with a molecular weigh larger than benzene (78kg/kmol)

Category Primary Secondary Tertiary Range (°C) 400-600 600-800 800-1000

Species Acids, phenols, ketones, guaialcols,

furans, fulfurals.

Phenols, heterocyclic heters,

monoaromatic hydrocarbons

Polyaromatic hidrocarbons

Classification of biomass tar according to formation temperature

Shorter reaction times Gas phase reactions that becomes progressively aromatics



TAR CONTROL

Fixed bed co-current gasifiers and circulating fluidized beds produce less tar than fixed bed counter courrent gasifiers

PHISICAL TAR REMOVAL PROCESS

CHEMICAL TAR CONVERSION PROCESS

Thermal conversion processes involve rainsing the gas temperatarute above

1000°C (PAH , SOOT )

Catalytic conversion can be operated a lower T elimination the heating

(SOOT )and material requeriments.

Metal based Mineral based Uneconomic due toH2S desactivation

• Scrubbers

• Wet electrostatics precipitators

• Packed bed filtering

• Bag filters

TECHNOLOGY



OTHER GAS CONTAMINANTS

Nitrogen and sulphur gases• Precursor to acid rain and photochemical smog • The low temperature and oxygen deficient favor NH3 which

act as NOx precursor. • Thermal NOx can be form simply from the addion of N2 or O2 (5-

15)%.

NOx control can be dome through fume recirculation and post combustion, and also trough the catalytic or thermal conversion of NH3 and NOx to N2 y H2O.



PARTICULATE (FLY ASH AND DUST PARTICLES)

Particulates are organic and inorganic fine dust particles entrained out of the gasifier by products and cause corrosion and clogging.

Pariculates can be removed by phisical process like:

Cyclones wet scrubbers

Allow recycling large particulates and bed

material to the gasifier. It is ineffective at

removing particles of sub-microns.

It can be operate close to gasifier temperature.

Bag filters or dry electrostatic filters

Removes fine particles.

Due to the importance or ther alkali content, certain components of biomass ashes are dense, sticky and reactive. Alkalis combine with chlorine to form

Alkali chlorides. AC induce corrosion.



Due to feedstock collecion and transportation costs, electricity production from biomass is typically limited to less than 100MW.

Parameter 1 2 3 4 5

Feedstock Wood Bio (misc) Wood Wood Coal

Oxidant Steam Air Air Air Oxygen

Power ouput (MW)

2 6 8 32 800

Efficiency (%)

25 33 29 40 43

Gasifier Atmospheric Pressurised Atmospheric Atmospheric Pressurised

Gas cleaning

Cold Hot Cold Cold Cold

CYCLE ICE GT-CC GT-CC GT-CC GT-CC



Cycles of energy production with biomass gasification as a part of the process

BOILERS AND RANKIE CYCLES

TOPPING CYCLES

Gas turbines Internal combustion engines (More

efficient that gas turbines)

Gasification combined cycle (CC) with heat recuperation by steam generation appears advantageous for electricity production.

Increse the efficient of the biomass process (15-25%)

Internal combustion engine combined cycle can realistically be considered for biomass based power generation.



The gasification model was developed with air gasification data for a pilot circultation fluidised bed reactor operated at atmospheric pressure

1. Light gas species, total tar and char concentration were verified by mass balance reconciliation

2. The distribution of a subset of tar species was determined from the quantity and elemental composition of the total tars by non-stoichiometric equilibrium calculations

3. A complete stoichiometry was written for the reaction system, and fitted to the calculated product distribution by letting reaction equilibrium temperatures vary from the measured gasification temperature. A multivariate regression relates these parameters (representative of producer gas, tar and char distribution variations) to operating conditions and fuel compositions.

MODELLING



The thermodynamic properties of biomass were obtained from atomic group contributions. Char was assumed to be solid graphite (C). The light gas species considered were {O2, H2O, H2, CO2, CO, CH4, N2, NH3} and C2H4 representing all remaining light hydrocarbon gases.

MODELLING

The stoichiometry was generated from the following master equation:

𝐶𝑛𝐻𝑚𝑂𝑝𝑁𝑞+(𝑛−𝑝 )𝐶𝑂2↔ (2𝑛−𝑝 )𝐶𝑂+(𝑚2 − 32𝑞)𝐻2+𝑞𝑁𝐻3

Four model tar compounds were kept for flowsheet calculations: fulfural, phenol, naphtalene and pyridine.

OBJECTIVE FUNCTIONS



𝜂=𝑤𝑒− ∑𝑤 𝑖

+¿

Δ𝑘𝑤𝑜𝑜𝑑° �̇�𝑤𝑜𝑜𝑑

¿

𝑤𝑒− Electricity generated

𝑤𝑖+¿¿

Power consumption of each process equipment

Dry ash free (daf) mass flow rate�̇�𝑤𝑜𝑜𝑑

Δ𝑘𝑤𝑜𝑜𝑑° Specific chemical exergy of wood calculated

with the method of Szargut and Styrylska

The model considers that no fuel other than wood could be imported to the process, nor waste heat exported from the process. The properties of wood are specified in the model.

The second objective is the total grass roots costs, i.e., the total investment cost for a new production site:

𝐶𝐺𝑅=(1+𝛼1 )∑𝐶𝐵𝑀−𝑎𝑐+𝛼2∑𝐶𝐵𝑀−𝑏𝑐

𝐶𝐺𝑅 Total grass roots costs CGR

𝐶𝐵𝑀−𝑎𝑐Equipment costs considering actual operating conditions and construction materials

𝐶𝐵𝑀−𝑏𝑐 Bare module equipment costs at base case conditions

OBJECTIVE FUNCTIONS



= 18%

=35%

OPTIMIZATION CASES STUDIES



Six alternatives have been included in the optimisation superstructure

whithAir, steam, oxygen gasifier

Each scenario combines

gas cleaning process combined with a ICE-CC (internal combustion engine)

hot gas cleaning process combined with a GT-CC (gas turbine)




Modelling steam and oxygen gasification scenarios

CONSIDERATIONS

Assuming that both gasifiers could be adapted to operate either in atmospheric or pressurised conditions

These assumptionsbecame of interest for assessing the sensitivity of the equilibriummodeL




OTHER CONSIDERATIONS

temperature and pressure losses in the different equipments




FOR OXYGEN GASIFICATION

an ASU using ceramic ion transfer membranes(ITM)

•(800-900°C)

•Mechanical power consumption=150kWh/ton O2

Other technologies

•Criogenyc separation

Most economical option




ICE FLOWSHEET MODELLING EQUATIONS

•The stoichiometric combustion fuel to air ratio was assumed to be 1.6

•nmec: mechanical efficiency•ncool:engine cooling water requirements•nflue: flue gas temperature were relatedto the electrical power generation by empirical efficiencycalculations

Related to the electrical power generation by empirical efficiency calculations




DECISION VARIABLES

10 decision variables

•Operating conditions•Steam cycle operational variables•Wood moisture content after drying (mc)•ER: equivalence ratio for air or oxygen gasification•SBR: steam to biomass ratio, for steam gasification




COST FUNCTION SCALING VARIABLES

EQUIPMENT COSTS

Decision variables Composition and fuel properties of wood

affect

RESULTS AND ANALYSIS



IMPACT OF DECISIÓN VARIABLES ON OPTIMIZATION RESULTS

After 15,000 evaluations, steam gasification had the most favourable trade-off, and that of air gasification mostly dominated that of oxygen gasification.





• investment costs tend to be minimised with GT-CC• ER and SBR are not strongly correlated variables because they practically always

take constant values. • In respect to the different oxidants and in terms of optimal specific capital costs,

steam gasification still appears as the best option (with specific costs of 2130 €/kWe for GT-CC, and 2717 €/kWe for ICE-CC) followed by air (GT-CC: 2465 €/kWe; ICE-CC: 3110 €/kWe) and oxygen gasification (GT-CC: 2805 €/kWe; ICE-CC: 3324 €/kWe).





•The ICE is costlier than the gas turbine, is also more efficient. •Oxygen plant, gasifier, and gas cleaning equipment costs vary essentially in function of the volumetric flow of gases.

•As a consequence, oxygen gasification, although penalised by the incremental cost of the ASU, is advantaged by the lower cost of the gasifier and gas cleaning equipment, which become higher for air gasification due to nitrogen gas and also for steam gasification due to the higher oxidant to biomass ratio

.





•The cost of wood dryers and heat exchangers is small compared with other equipments





•(9b) is included only when material stream compositionsare changed by chemical reactions•The most important exergy losses are due to chemical reactions (gasification, combustion)

CONCLUSION



•Plant capacity of 20 MWth,wood was obtained and analysedto identify process operating conditions that minimise tar formation.•Under the current modelling assumptions, optimisation results indicate that the energy conversion efficiency is maximised using ICE-CC at operating conditions that also favour low tar concentrations.

•As for choosing among different oxidantssteam gasification would appear to have the best specificcapital costs (the optimal specific cost of GT-CC is 2.1€/We, while that of ICE-CC is 2.7 €/We), followed by air gasification (GT-CC: 2.5 €/We; ICE-CC: 3.1 €/We), and finally oxygen gasification (GT-CC: 2.8 €/We; ICE-CC: 3.3 €/We).

termoeconomic gasification

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