The Next Generation of Activated Carbon Adsorbents for the Pre- Combustion Capture of Carbon Dioxide. Power Plant Modelling Workshop at University of Warwick Dr. Joe Wood,Prof. Jihong Wang, Simon Caldwell, Yue Wang
Dr Joe Wood - Introduction Project overview Modelling objectives Simon Caldwell - Modelling of carbon capture at IGCC Power Plants Dispersion Model Adsorption Model Yue Wang - Modelling of power plant performance Heat recovery steam generator Gas turbine and heat recovery module
General acceptance that CO 2 emissions are affecting the climate UK emissions targets for power stations is a reduction from 500 to 50 gco 2 /kwhr by 2030 (1) Up to 18 GW of investment of CCS power stations is possible in the 2020s By 2030, 26% of global emissions from China, with 98% of power generation emissions from coal (2) $2.7 trillion investment in power by 2030 (3) 50/50 split favouring pre-combustion to postcombustion capture (3) 1. Turner, A. et al. The Fourth Carbon Budget - Reducing emissions through the 2020s. London : Committee on Climate Change, 2010. 2. Grubb, M. Generating Electricity in a Carbon Constrained World. London : Elsevier, 2010. 3. Liang, X et al. 2011, Applied Energy, Vol. 88, pp. 1873-1885
Diagram based on Tampa Electric IGCC Process Flow Diagram, National Energy Technology Laboratory, USA http://www.netl.doe.gov/index.html
Could provide a CO 2 emission free process of the future Reaction to form Syngas Convert CO in to CO 2 in water gas shift Separation of CO 2 and hydrogen Diagram based on Scottish Carbon Capture and Storage Centre http://www.geos.ed.ac.uk/sccs/capture/precombustion.html
University of Birmingham (Simon Caldwell) Simulation of pre-combustion carbon capture Developing a model of the adsorption step Producing cyclic model including all PSA steps Developing model to incorporate complete carbon capture process Incorporates adsorption isotherms, mass transfer models, fixed bed model Unsteady state heat and mass balances Parameter estimation from experimental data
Project Overview T, P T, P Syngas from WGS Reactor Composition Dry Molar Flowrate CCS Process Composition Molar Flowrate Fuel gas to gas turbine Molecular Weight Molecular Weight Composition: Hydrogen, Carbon dioxide, Carbon Monoxide, Nitrogen, Methane, Hydrogen Sulphide, Water
Typical PSA Process Water Gas Shift Product (60% H 2, 40% CO 2 ) High Purity CO 2 Adsorption Purge Blowdown Pressurisation High Purity H 2
University of Warwick Modelling and simulation study of IGCC power generation process Integration of power plant and CCS models Investigations of Dynamic response Impact on power transmission and distribution network Effect of CCS upon plant efficiency Effect of different fuel types Quantified analysis of the process with plant optimization
Dr Joe Wood - Introduction Project overview Modelling objectives Simon Caldwell - Modelling of carbon capture at IGCC Power Plants Dispersion Model Adsorption Model Yue Wang - Modelling of an IGCC power plant Heat recovery steam generator Gas turbine and heat recovery module
Model being developed for the removal of CO 2 from a H 2 /CO 2 gas mixture by adsorption High CO 2 content compared to post-combustion processes High pressure favours physisorption Hierarchical model developed in gproms Based on Axial Dispersed Plug Flow Model Current model looks at an Adsorption system for the separation of Carbon Dioxide and Nitrogen Literature review of CO 2 /N 2 Adsorption Models on Zeolite 13X
Equations Component Mass Balance Use of overall Mass balance: Adsorption rate equation (Linear Driving Force): Equilibrium Isotherm (Langmuir):
Temperature, Pressure and Transport Properties Thermal Operating Modes Isothermal Adiabatic Non-isothermal Momentum Balance No pressure drop Ergun s Equation Darcy s Equation Mass Balance Coefficients: Mass transfer coefficient Dispersion coefficient Diffusivity Heat Balance Coefficients: Heat transfer coefficient
Fixed bed for removal of CO 2 from a N 2 flow Capable of controlling pressure, input flowrates and temperature Limited to 200 C and 25 barg Maximum CO 2 content of 25% restricted by the CO 2 analyser Main output is CO 2 mole fraction
A simplified model was established where no adsorption takes place Allows ability to validate model to be tested Tests the response of the entire experimental system Assumes system to be isothermal with no pressure drop Empirical models looking at response of the system without the bed were established Experiments run with bed filled with glass beads Model Parameters identical to experiment (i.e. bed size, flowrates etc.)
CO 2 Mole Fraction 0.1 0.08 0.06 0.04 0.02 Flowrate (ml/min) 8.5 Pressure (barg) 25 CO 2 Mole Fraction 0.1 Estimated Dispersion Coefficient (m 2 s -1 ) Literature Dispersion Coefficient (m 2 s -1 ) 2.75 x 10-6 10-6 Experimental Output Model Output 0 0 200 400 600 800 1000 1200 Time (s)
More complex model developed for simulation of the adsorption step Model Assumptions 1. Fluid flow is governed by axially dispersed plug flow model 2. Equilibrium relations are given by the Langmuir Isotherm 3. MT rates are represented by LDF equations 4. Thermal effects are negligible 5. Pressure drop represented by Ergun Equation Parameters Estimated Dispersion coefficient, Langmuir Isotherm parameters All other parameters match experiment conditions
CO2 Mole Fraction 0.12 0.1 0.08 0.06 0.04 0.02 0 0 1000 2000 3000 4000 5000 6000 7000 8000 Time (s) Experimental Output Model Output Flowrate (ml/min) 8.5 Pressure (barg) 25 CO 2 Mole Fraction 0.1 Bed length (cm) 7.7 Experimental Adsorption Capacity (mmol/g) 3.3
Parameters Estimated: Langmuir Isotherm Parameters: Dispersion Coefficient Literature results vary widely for Isotherm parameters and often do not give Dispersion Coefficient values Start point for parameter estimation severely affects estimated value Parameter Range Closest Fit Dispersion Coefficient (m 2 s -1 ) 8.2x10-7 1.1x10-4 8.2x10-7 A (N 2 ) (mol kg -1 Pa -1 ) 4.4x10-7 3.1x10-5 4.4x10-7 B (N 2 ) Pa -1 ) 5.5x10-7 1.4x10-5 5.5x10-7 A (CO 2 ) (mol kg -1 Pa -1 ) 1.9x10-5 6.5x10-4 1.9x10-5 B (CO 2 ) (Pa -1 ) 5.4x10-6 5.0x10-4 5.4x10-6 CO 2 Adsorption Capacity (mol kg -1 ) 1.29 3.61 3.61
Validation of estimated parameters by testing them against a shorter bed Experiment repeated with 5g adsorbent instead of 18g, the remainder filled with glass beads All other conditions kept the same Glass Beads Zeolite 13X Dispersion model used for glass bead part and adsorption model for 5g adsorbent part CO 2 /N 2 Mixture
CO2 Mole Fraction 0.12 0.1 0.08 0.06 0.04 0.02 Flowrate (ml/min) 8.5 Pressure (barg) 25 CO 2 Mole Fraction 0.1 Bed Length (cm) 2.4 Experimental Adsorption Capacity (mmol/g) 2.8 Experimental Output Model Output 0 0 500 1000 1500 2000 2500 3000 3500 4000 Time (s)
Parameter Full Bed Best Estimate Short Bed Best Estimate Dispersion Coefficient (m 2 s -1 ) 8.2x10-7 8.2x10-7 A (N 2 ) (mol kg -1 Pa -1 ) 4.4x10-7 4.4x10-7 B (N 2 ) Pa -1 ) 5.5x10-7 5.5x10-7 A (CO 2 ) (mol kg -1 Pa -1 ) 1.9x10-5 4.5x10-5 B (CO 2 ) (Pa -1 ) 5.4x10-6 2.5x10-5 CO 2 Adsorption Capacity (mol kg -1 ) 3.61 1.81 Dispersion coefficients and Nitrogen Langmuir constants kept constant as they approached their bounds Other models fit adsorption capacity closer but with significantly different parameters
Hierarchy model developed based on axial dispersed plug flow model Simplistic dispersion only model validated More complex adsorption model able to mimic experimental work 5 parameters estimated to give very close approximations to experiments
Adsorption Model Improve parameter estimation Implement energy balance Pre-Combustion Model Switch system to using Activated Carbon adsorbent Move towards conditions found in pre-combustion capture (i.e. Hydrogen) Produce cyclic PSA model Power Plant Model Complete carbon capture unit model Combine model together with power plant model
Dr Joe Wood - Introduction Project overview Modelling objectives Simon Caldwell - Modelling of carbon capture at IGCC Power Plants Dispersion Model Adsorption Model Yue Wang - Modelling of an IGCC power plant Heat recovery steam generator Gas turbine and heat recovery module
Figure1. Simplified IGCC power plant procedure Key modules for IGCC process: a.gem with auxiliary systems:coal feed, ASU, Gasifier, WGS; b.combined cycle system: Gas turbine, Heat recovery boiler, steam turbine.
Coal slurry feed system Pulverize coal to 5mm particles and mixed with water to feed coal slurry to the gasifier. Coal mill model has been developed from our previous work.
ASU unit in IGCC power plant Supplies oxygen to gasification island/ sulphur removal processes Optimal integration with gas turbine efficiency
ASU unit in IGCC power plant Figure3 simplified ASU unit
The GEM (Gasification Enabled Module )unit Use coal slurry oxygen and air to produce syngas; CO shift promotes the CO2 content in syngas and prepare for the PSA removal; Supply HP &LP steam to HRSG.
Main model based on gas and solid phase mass balance and energy conservation; Chemical reaction submodel inculdes devolatilization and drying, homogeneous reactions and heterogeneous reactions; Heat transfer submodel; Slag layer submodel. CO+H O CO +H -41MJ /kmol 2 2 2 Water gas shift reaction provide high partial pressure of CO2 preferred in PSA system Improved hydrogen extraction; Direct contact gas / liquid exchange Increased power output through improved where water flows against a gas gasification waste heat recovery. stream passing upwards; Considerably aid waste heat recover and lower costs, and is especially advantageous in a shifted scheme All of the cooling train heat exchang are liquid liquid making them much smaller and cheaper Figure 4 the GEM unit
Gas turbine components: Brayton cycle
Gas turbine mathematical model: The Compressor (Isentropic) block increases the pressure of an incoming flow to a given outlet pressure. It determines the thermodynamic state of the outgoing flow along with the compressor's required mechanical power consumption at a given isentropic efficiency. The realized output mass flow rate A characteristic time is used to delay the mass flow.
Gas turbine mathematical model: Mixes two fluids with or without phase change. The Mixer block calculates temperature, composition and pressure after an adiabatic mixing of two fluids. The output enthalpy is the sum of the input enthalpies. The pressure of the resulting flow Pressure loss K is the pressure loss factor
Gas turbine mathematical model: The Reactor block computes the outgoing flow bus (FB) after one reaction, a heat exchange with the environment and a pressure loss. Heat exchange with the surrounding environment is taken into account. In general, the outgoing flow is not in chemical equilibrium as the Reactor performs a chemical reaction depending on a rate of reaction.
Gas turbine mathematical model: The Turbine (Isentropic) block decreases the pressure of an incoming flow to a given outlet pressure. It determines the thermodynamic state of the outgoing flow along with the produced mechanical power at a given isentropic efficiency. Subscripts, s and ac states for isentropic and actual change of state. oi h h h 3 4 ' h 3 4 Turbine is adiabatic and used with gaseous flows
This heat exchanger support counter flow The Heat Exchanger block calculates the change of state of two media caused by indirect heat exchange. It is assumed, that this heat transfer rate is constant over the area of the heat exchanger or it represents a mean of the heat exchange rate. To approximate the dynamic thermal behavior of the block, the heat exchanger is assumed to have a thermal mass The heat exchange with environment is divided in four parts: both thermal masses (for flow 1 and flow 2) exchange heat with environment, both output flows exchange heat with environment. Each of the two flows entering the heat exchanger exchanges heat with its own thermal mass, The two thermal masses are not interacting, but they have a term representing the heat exchange with environment.
to complete the whole system modelling implementation of the model to software environment; integrate the model with CCS process model.