dynamic simulation and controls for oxy - fired ... - ieaghg

5th Oxyfuel Combustion Research Network Meeting, Wuhan, China

October 29, 2015

Dynamic Simulation and Controls for Oxy-Fired Boiler and Steam Power Plant with

CO2 Capture System

Alstom Power

Xinsheng Lou, Armand Levasseur, Francois Granier, Olaf Stallmann, Carl Neuschaefer, Robert Schrecengost

© ALSTOM 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authority, is strictly prohibited.

5th IEAGHG International Oxyfuel Combustion Research Network, Wuhan, China, X. Lou Oct. 29, 2015 – P 2

Agenda

• Oxy Plant Dynamic Modeling−Roadmap and Motivation−Integrated Oxy CCS Plant Scope−Oxy Boiler, Turbine Island, GPU, ASU

• Controls and Operations Simulations−Air/Oxy Mode Transitions Operational Analysis−Grid Code Compliance Analysis−GPU Flexibility and Trip Analysis−Load Changes and M.I. Analysis

• Advanced Controls and Optimization

• Conclusions



Oxy Plant Dynamic ModelingRoadmap and Motivation

• Oxy Plant Product Development Roadmap- Modeling and Tool Development



Oxy Plant Dynamic ModelingWhy Oxy Combustion

• Near Zero Emissions• High CO2 Capture Rates (>90%)• Cost Competitive (v.s. other CCS, Wind, Solar, etc.)• Fuel and Operating Flexibility • Ready for Scale Up - Fit for New and Retrofit Applications

Proven

Reliable

Flexible

Alstom offers all major Oxy-Fuel Power Plant components [Boiler, AQCS, GPU] and integrated turnkey power plants and power blocks



Oxy Plant Dynamic ModelingIntegrated Oxy CCS Plant Scope

• Oxy-fired Boiler Model: - Combustion/Furnace model , Firing system - Auxiliary equipment (fans, dampers, APH or GGH, etc.)- Heat absorption surfaces

• Air Quality Control System Model: - ESP, WFGD and FGC models still to be developed

• GPU Model:

- Main Compressors and heat exchangers

• Turbine Island Model:- HP/IP/LP turbines and condensers- Feedwater pre-heater train & Feedwater tank- Feedwater pumps, control valves, etc.

• ASU Model: - Main compressors, turbines and heat exchangers

• Plant Regulatory Controls

Disclaimer: Generic Oxy Fuel Model (no specific project)



Oxy Plant Dynamic ModelingOxy Boiler Island Scope

• Fuel Model- Can be used to model a variety of fuels including

hard coal, biomass, heavy/light oil, etc.• Combustion Model

- Stoichiometry based combustion using R-Stoic model

- Staged combustion• Firing System

- MBZ includes Air/Oxidant/O2 flows of each coal elevation

- Lumped CCOFA, LSOFA and HSOFA windboxes• Heat Absorption Surfaces and Boiler Water

Circulation System- Economizer, Waterwall, Separator, SH panels, SH

platens, SH finish, RH horizontal, RH pendicular, RH finish, SH/RH desuperheaters, etc.

- Boiler water relief line, Flash tank, Boiler water circulation pump, etc.

• O2 from ASU Injection and FGR System- Primary/Secondary/Supplemental O2 flows- Primary/Secondary flue gas recirculation flows

• Auxiliary Equipments- Pulverizer, Fans, Pumps, GGH, Valves/Dampers,

SCR, etc.• Simplified AQCS Models

- ESP, FGD and FGC

• Oxy boiler island controls- Combustion controls- Steam temperature controls- Firing Mode transitions, etc.



Oxy Plant Dynamic ModelingASU Scope

• Cryogenic Air Separation Unit

• HP and LP Distillation Columns for Gaseous Oxygen production

• Oxygen Liquefaction Using N2 for refrigeration



Oxy Plant Dynamic ModelingSteam Turbine Island

• 1 HP, 1 IP and 2 LP

• 2 Condensers

• 2 x 50% condensate pumps

• 3 x 33% feedwater pumps

• 3 x 33% booster pumps



Oxy Process ModelingGPU Scope

• EOR Based Gas Processing Unit— Rigorous Thermo-physical properties prediction methods— Modeling of the Direct Contact Cooler (DCC)— Improved purity of CO2 product (~1.0x10-5 O2/mole of CO2)— CO2 Recirculation Added for Anti-Surge Control— Control loops well tuned



Simulations of Dynamic OperationsAir/Oxy Model Transitions

• Air/Oxy Mode Transition at 40%MCR

Air and FGR Flows during Air/Oxy Transition at 40% MCR



Simulations of Dynamic OperationsGrid Code Compliance Analysis

For a frequency drop of 0.5Hz, the minimum requirements:

−Primary response: 10%MCR increase in 10s with help of MCV pressure reserve and condensate stop

−Secondary response: maintain 10%MCR increase for 30min with the help of boiler load boost

• Grid Code Compliance Requirement




• Grid Code Compliance Analysis Results




• Power Responses- The primary response simulation results show that the power (gross MWe load)

produced by the generator can increase by 44MWe or 10%MCR in 10 seconds and that this level of power production (gross MWe load) can be maintained for 30 minutes to satisfy the secondary response.

- The full response capability of the plant is restored in about 20 minutes, ready to undergo another power (gross MWe load) jump as the condenser level returns back to normal set point conditions.

- The furnace pressure deviation is within a small range, indicating that the boiler is not negatively impacted by the event.

• GPU Responses- The GPU compressor powers increases as the boiler catches up and as more flue

gases have to be processed. - The GPU response shows that the CO2 purity remains steady and the product

quality is not affected by the grid code event.- The CO2 recovery is reduced initially, dropping to about 75% within the first 5

minutes but returning to about 90% in less than 20 minutes.



Simulations of Dynamic OperationsGPU Flexibility and Trip Analysis

• Flexibility Analysis −Both Models Used: full GPU Stand-Alone Model vs. Boiler+Simplified GPU −The simulation shows that a minimum of 90% CO2 product recovery is achieved. −Off-gas, CO2 product recirculation and the process control system assure that

product purity is within the acceptable limits (O2 contaminant of less than 10ppm).−The GPU is capable of supporting 5%BMCR/min load ramping operations

CO2Capture

Time [secs]

CO

2_R

ecov

ery

PA_A

irCO

2 kg

/sPr

oduc

tCO

2 k

g/s

Feed

CO

2 kg

/s

0.0 2000.0 4000.0 6000.0 8000.0

20.0

40.0

60.0

80.0

100.

0

0.0

50.0

100.

015

0.0

200.

0



Simulations of Dynamic OperationsGPU Flexibility and Trip Analysis

• Trip Analysis −Both Models Used: Full GPU Stand-Alone Model vs. Boiler+Simplified GPU −The hot flue gas flow from boiler and the primary air flow recycled from the DCC

to the boiler are not affected by the compressor trip.−The full GPU model can be used to analyze FG compressor trip when a minimum

feed into the cold-box is used to sustain the trip simulation transients.



Simulations of Dynamic OperationsLoad Change and MI Analysis

• Oxy Boiler Load Ramping−Full Load Cycles−Mechanical Integrity Analysis

• SH Header and Separator Header

MCR - Low Load - MCR



Simulations of Dynamic OperationsLoad Change and MI Analysis

• Oxy Boiler Load Cycling and MI Analysis −Transient simulation analysis were conducted using the Alstom Dynamics model−Pressures vs. time incorporated into the model−Heat transfer coefficients. Vs. temperatures incorporated into the model for both

header and tubes in MI analysis−Material property ( modulus of elasticity, density, coefficients of thermal

expansion, conductivity, etc..) vs. temp is incorporated into the model) −Fatigue life was estimated, which generally decreases as ramping rate increases



Simulations of Dynamic OperationsAdvanced Controls and Optimization

• What Is Advanced Controls−Computer based algorithm, strategy and

system that deviates from conventional PID based controls

• Model Predictive Controls (MPC)• Model Reference Adaptive Controls (MRAC)• Fuzzy Controls (FC)• Real-Time Optimization (RTO)

• Potential Benefits from Advanced Controls−Steam temperature variations suppression−Heat rate Improvement−NOx Emission reduction− Improve CO2 capture rate−Maintain CO2,O2 concentrations in CO2 product−MW Flexibility vs ASU operations −Optimization of Startup, Shutdown, Mode

Transitions




• Model Predictive Control (MPC)




• Real-Time Optimization (RTO)- The objective of RTO is to optimize plant operations

Based on an economic performance measured under changing production schedules, prices, emission credits availability and trading mechanisms, etc.

http://www.google.com/url?url=http://environmentalheadlines.com/ct/2010/09/07/company-in-windsor-to-receive-9m-to-develop-carbon-capture-technology/&rct=j&frm=1&q=&esrc=s&sa=U&ved=0CCQQwW4wB2oVChMI5KWd6ciuyAIVC3M-Ch3aPgHE&usg=AFQjCNFy72HI0mz7RsfXDQsz4tgoep6w8Q

http://www.google.com/url?url=http://environmentalheadlines.com/ct/2010/09/07/company-in-windsor-to-receive-9m-to-develop-carbon-capture-technology/&rct=j&frm=1&q=&esrc=s&sa=U&ved=0CCQQwW4wB2oVChMI5KWd6ciuyAIVC3M-Ch3aPgHE&usg=AFQjCNFy72HI0mz7RsfXDQsz4tgoep6w8Q




• RTO for Oxy CCS- To achieve the maximum profit of the oxy CCS plant by pushing the

operating condition at steady state towards the economic optimum points. - Identifying the optimization opportunities related to both electric power,

environmental controls and CO2 economics- ASU and GPU represent a major part of plant aux power consumption

Maximize: (Total Profit = Total Income – Total Cost)

Minimize: Total cost = cost of {operations + emissions} –value of {additional capacity + byproducts}

Cost of operations = Cost of {fuel + ammonia/urea + lime/limestone + imported power (under production)};

Cost of emissions = Cost of {CO2 emissions + NOx emissions + SOx emissions};

Value of byproducts = Value of {saleable ash+ gypsum (WFGD w/forced oxidation)}



Conclusions

1. Technical approach to modeling and controls of industrial scale oxy fired boiler and CCS proved feasible and effective

2. Process dynamic model developed and validated with reference design data for 350+MWe oxy boiler and CCS plant

3. The regulatory controls designs were implemented and evaluated with the oxy boiler and CCS plant dynamic simulator

4. Transient analysis was conducted using the oxy boiler dynamic model, GPU model, and the integrated plant model in FEED

5. Integrated advanced controls were developed and evaluated for the industrial scale reference design unit with oxy firing and carbon capture and sequestration. Potential incremental operating performance and economic benefits are to be achieved with advanced process controls (APC)



Acknowledgements and Disclaimer

Acknowledgement

Some of work presented was supported by the US Department of Energy through the National Energy Technology Laboratories under Agreement DE NT-0005290. The guidance and direction of NETL Project Managers Steve Mascaro and Tim Fout is acknowledged and appreciated.

Disclaimer

Parts of this presentation were prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

Information disclosed herein is furnished to the recipient solely for the use thereof as has been agreed upon with ALSTOM and all rights to such information are reserved by ALSTOM. The recipient of the information disclosed herein agrees, as a condition of its receipt of such information, that ALSTOM shall have no liability for any direct or indirect damages including special, punitive, incidental, or consequential damages caused by, or arising from, the recipient’s use or non-use of the information.



Acknowledgements

• DOE – National Energy Technology Lab (NETL)

• Alstom – Thermal Power / Steam - Boiler R&D, Boiler Projects

• Alstom – Thermal Power / Steam – EES CO2 – Oxy R&D Program

• Alstom – Thermal Power / Steam – White Rose Oxy Project

• Alstom – Process dynamic modeling and control - Mahesh Mistry, Olu Akinjiola, Shizhong Yang, Chuan Wang, Abhinaya Joshi,

Gisbert Kaefer, Lionel Lambert, Tracy Midgley

• Alstom – Mechanical Integrity (MI) analysis- Haiyang Qian, Guosheng Ye, Haider Al-Mamoury

www.alstom.com

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