Modeling and Cost Evaluation of CO2 Capture Processes

Transcription

1 Modeling and Cost Evaluation of CO2 Capture Processes Rate-Based Distillation and Integration Economics Industry Webinar Josh Stanislowski & Tony Snyder, Energy & Environmental Research Center Sanjeev Mullick & Rob Hockley, AspenTech 02 May Aspen Technology, Inc. All rights reserved

2 Disclaimer Aspen Technology may provide information regarding possible future product developments including new products, product features, product interfaces, integration, design, architecture, etc. that may be represented as product roadmaps. Any such information is for discussion purposes only and does not constitute a commitment by Aspen Technology to do or deliver anything in these product roadmaps or otherwise. Any such commitment must be explicitly set forth in a written contract between the customer and Aspen Technology, executed by an authorized officer of each company Aspen Technology, Inc. All rights reserved 2

3 Guest Presenters EERC Josh Stanislowski Research Manager EERC Josh s principal areas of interest and expertise include fossil fuel conversion with emphasis on CO 2 capture, gasification systems analysis pollution control and process modeling. He has extensive experience with systems engineering process controls project management and AspenTech software. Tony Snyder Research Engineer EERC Tony s principal areas of interest and expertise include alternative fuels development conceptual modeling and economic analysis of novel processes and process optimization through experimental design and statistical data analysis Aspen Technology, Inc. All rights reserved 3

4 Improve Performance and Reduce Capital Costs Using Rate-Based Distillation to Model CO 2 Capture Systems AspenTech Webinar: Modeling and Cost Evaluation of Carbon Capture Processes May 2, 2012 Josh Stanislowski and Tony Snyder 2012 University of North Dakota Energy & Environmental Research Center.

5 Agenda Topics See how the EERC was able to: Model the entire CO 2 capture process with Aspen Plus and Rate-Based Distillation from coal combustion to amine scrubbing with solvent recycle. Use pilot-scale performance data to apply models to advanced solvents. Evaluate the performance of baseline and novel solvents. Determine the CO 2 baseline capture rates from coalderived flue gas using monoethanolamine (MEA). Estimate CO 2 capture costs using Aspen Process Economic Analyzer (APEA). 5

6 Presentation Outline Project overview Development of Aspen models Base combustion models Integrated combustion models CO 2 capture models Absorber stripper column design Integrated models Heat-stable salt (HSS) formation models Full-scale capture models Economic analysis Conclusions 6

7 Advancing the state of CO 2 capture by evaluating and developing those technologies that are nearest to commercial viability for utility applications. Multiple-phase program. Includes funding from private sector sponsors (27), the North Dakota Industrial Commission, and the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL). Identify technology challenges and develop strategies for cost-effective and efficient implementation at the power utility scale.

8 8 State of Wyoming Clean Coal Technology Fund

9 Summary of CO 2 Capture Technologies 9

10 Combustion Test Facility (CTF) 550,000 Btu/hr Upfired Air- or O 2 -fired Multifuel capability Coal, biomass, gas, liquid fuel, sludge, and municipal solid waste Features - Air preheater and heat exchangers - Adjustable-swirl burner - Deposition section - Numerous ports - Selective catalytic reduction (SCR) reactor - Baghouse - Electrostatic precipitator (ESP) - Sulfur scrubber Testing of fuels and additives - Fouling and slagging - Corrosion - Hg - NO x - SO x - CO 2 capture - Particulates - Heat flux - Infrared (IR) flame characterization 10

11 CO 2 Capture System 10-inch-diameter columns designed to be flexible. Capable of evaluating different solvents with column height adjustment. Packed column with the ability to easily change packing type. Very highly instrumented to allow for high control and greater measurement

12 12 EERC... The International Center for Applied Energy Technology

13 Postcombustion Testing MEA (30 wt%) Hitachi H3-1 Methyldiethanolamine (MDEA) piperazine Huntsman solvent additive Baker Hughes additives 13

14 Aspen Modeling Approach Aspen Plus v7.2 is utilized for developing mass and energy balance and process flow. Combustion models CO 2 capture models (Aspen Rate-Based Distillation) APEA is used for sizing equipment and developing costs. Capital cost Operating cost Considers entire plant costs Aspen Plus mass and energy are able to be directly exported into APEA for equipment sizing and costing, allowing rapid comparisons of process alternatives. 14

15 Aspen Process Economic Analyzer (APEA) One-to-Many Mapping 2012 Aspen Technology, Inc. All rights reserved 15

16 Base Combustion Model Base Model of the CTF (air-fired) HEATEX BAHOUSE SO2SCRUB B1 DECOMP AF-CTF HOTGAS COOLGAS FILT-GAS SCRUBGAS 1 COAL HEAT1 SOLIDS SULFUR Q HEAT2 PRIM-AIR PHEAT1 CHN PRIMHEAT MIXER COAL-AIR 2NDHEAT Notes: Used Peng Robinson equation of state. Compared our results with real data to determine heat loss in the combustor. PHEAT2 2ND-AIR Caveats: Built-in coal heat-of-formation correlations are based on bituminous coal only. User input allowed, but bituminous coal correlations are still used in heat-of-formation calculations. Sulfur analysis appears to have a large impact on heat-of-formation calculation, may not be valid for fuels with less than 1% sulfur. 16

17 Absorber Stripper Column Design Two phases: Design support for columns Detailed model development based on the results of the pilot-scale test runs 17

18 Integrated Absorber and Stripper Models An advanced integrated absorber stripper system with the following features: Interconnected absorber and stripper columns Heat exchangers to maintain required temperatures while minimizing energy loss Complete recycle of the lean amine stream Automatic determination and optimization of the makeup stream FLUEGAS2 MAKE UP ABSORBE R LEANMEA COOLER CO2OUT FLUEGAS LEANMEA 3 HEATEX STRIPPER RICHMEA RICHMEA2 LEANMEA 2 18

19 Integrated Combustion Capture Model Coupled the combustion model with all back-end flue gas-cleaning units, including the CO 2 capture unit. Convergence becomes much more difficult because of the complexity of the model equations. 19

20 HSS Formation Models Goals Predict heat-stable amine salt (HSAS) formation in the system. Obtain better understanding of the impact of flue gas impurities on CO 2 capture technologies. Challenges Missing data: Equilibrium constants and kinetic parameters of desired reactions. Heats and free energies of formation of new compounds. Physical property data, e.g., heat capacity, ion mobility, diffusivity, critical parameters, etc. Convergence difficulties: Solids formation. Sensitivity to stream and column variables. Ultimately, modeling the formation of HSAS in Aspen Plus was deemed not feasible at this time. Degradation rates from pilot-scale data were used to aid in economic analysis. 20

21 21

22 Sulfate Concentration, ppm Click Sulfate to edit Concentration Master title style MEA H3-1 Huntsman Additive MDEA-Piperazine Day 0

23 Model Calibration/Validation Parameter Model Pilot Plant Data CO 2 Capture 69.5% ~70% Reboiler Duty 150,000 Btu/hr 140,000 Btu/hr MEA Flow into Absorber 6 gpm 3 6 gpm Diluted MEA Makeup Rate 0.6 gph None Sensitivity studies showed that to get 90% CO 2 capture, the reboiler duty had to be increased. Increasing the MEA flow rate had only a small impact on capture level. The reboiler duty was increased on the pilot-scale unit, and 90% capture was achieved. Additional model vs. pilot plant performance comparisons are ongoing. 23

24 Scale-Up of Pilot Model Created an Aspen Plus process model to represent pilotscale CO 2 capture process. Scaled-up model for 500-MW coal-fired power plant. Aspen Plus model originally represented 50-lb coal/hr pilot-scale system. Coal feed rate increased to 6000 tons/day to represent 500-MWe power plant. Rate-based Aspen Plus modeling software calculated size of absorber and stripper towers for 90% CO 2 capture. Estimated capital and operating costs with APEA. 24

25 500-MW Aspen Plus Model for CO 2 Capture 90% of CO 2 is removed from flue gas in absorber tower by MEA solvent. MEA losses from degradation are estimated from pilot-scale data. Wash zone minimizes MEA evaporation losses in absorber tower. 25

26 Aspen Plus Model CO 2 Compression and Liquefaction CO 2 is compressed to 190 psi. Water is removed in CO 2 dryer. CO 2 is liquefied in condenser by cooling to 26 C. Pressure pumped to 2000 psi for pipeline transport. 26

27 APEA Methodology 27 Aspen Plus model imported into APEA Coal combustion and flue gas cleaning not included in economic model because the focus was on estimating the CO2 capture costs (standard power configuration). Specific types of equipment were assigned to each process unit. Equipment sizing was based on flow rates and realworld practical availability. Cost estimates are for construction in the United States. APEA determined that three CO 2 capture trains were required for 500-MW plant because of equipmentsizing constraints.

28 Modeling Advanced Solvents Difficult-to-model advanced solvents in Aspen Plus: Composition unknown (proprietary). Some advanced solvent components are not part of the Aspen Plus standard database. Physical properties Equilibrium constants Reaction kinetics Utilized pilot plant data to determine difference between MEA and the advanced solvents. Used indices to perform economic analysis for the advanced solvents. 28

29 CO 2 Capture, % CO 2 Capture vs. Liquid-to-Gas Ratio MEA H3-1 MDEA/PZ Liquid to Gas Ratio, gallons/1000 actual ft 3

30 CO 2 Capture, % CO 2 Capture vs. Regeneration Energy MEA CO 2 Capture (4 psig) H3-1 CO 2 Capture (4 psig) MDEA/PZ CO 2 Capture (6 psig) Stripper 4-6 psig Btu/lb Btu/lb Btu/lb Regeneration Energy, Btu/lb CO 2

31 Capital Cost US$ Capital Cost Comparison $300,000,000 $250,000,000 $200,000,000 $150,000,000 $100,000,000 Other Boiler ASU CO 2 Liquefaction Stripper Tower Heat Exchangers Absorber Tower $50,000,000 $- MEA (old plant) H3-1 (old plant) MEA (new plant) H3-1 (new plant) Oxy-Fired Scenario 31

32 Energy Penalty Based on a 500-MW Plant 32

33 Overall Cost Summary Millions of US$ MEA (old plant) H3-1 (old plant) MEA (new plant) H3-1 (new plant) Total Capital Cost Operating Cost Utilities Cost Annual Cost (total) CO 2 Capture Cost, $ per ton CO 2 Avoidance Cost, $ per ton Rate Increase, $/kwh Base Electricity Cost of $0.08 per kilowatt-hour 33

34 US$ / ton CO 2 Avoided Cost of CO 2 Avoided $ $90.00 $80.00 Lost Revenue Operating Costs - Other Capital Recovery Operating Costs - Utility $70.00 $60.00 $50.00 $40.00 $30.00 $20.00 $10.00 $0.00 MEA (Old Plant) H3-1 (Old Plant) MDEA/PZ (Old Plant) MEA (New Plant) Scenario H3-1 (New Plant) MDEA PZ (New Plant) Oxy-Fired 34

35 Modeling Conclusions The EERC has developed reasonable models for coal combustion processes and CO 2 capture using Aspen Plus software. Rate-based distillation models are better than equilibrium models in simulating the CO 2 capture process. Currently not modeling HSS formation. APEA incorporated Aspen Plus model to estimate capital and operating expenses. 35

36 Economic Analysis Conclusions Utilities (steam/electricity) and equipment capital are the largest contributors to cost. An estimated 7% reduction in capital cost results from the use of the advanced solvent. The advanced solvent provides a savings potential of $6 per ton of CO 2 over MEA when electricity cost is $0.08/kWh. Over the course of 1 year, the advanced solvent has a savings potential of US$23 million versus MEA. The base COE has a large impact on the cost of CO 2 capture. Energy penalty is significantly reduced with H3-1 solvent. 36

37 PCO 2 C: Phase II Pilot-scale testing of CO 2 capture technologies Over ten test campaigns evaluating eight different technologies Several technologies will be further evaluated, and new novel approaches will be tested. Solvents: Huntsman, Hitachi, CanSolv (Shell), and Advanced Systems (NSG Contactor) Solid sorbents (NETL) Oxy-fired combustion (completed) Other solvent-based technologies: ION Engineering Slurry-based approach (C-Quest) Significant modeling effort to determine most efficient approaches to CO 2 capture system integration with power systems. 37

38 Steam Extraction Retrofitting Analyses have shown that the extraction of low-pressure steam from the steam cycle is an efficient technology to cover the energy demand for solvent regeneration in the stripper. The different configurations make it necessary to work on different approaches to how the challenges of steam extraction can be met. Study took the base case (withdraw steam in the intermediate lowpressure crossover) and compared to Cases a, c, and d shown at left. Lucquiaud, M.; Gibbins, J. Steam Cycle Options for the Retrofit of Coal and Gas Power Plants with Post-Combustion Capture. Energy Procedia 2011, 4,

39 Modified Steam Cycle for Steam Extraction 39

40 Option A The throttle valve is exchanged to expand the extracted steam. 40

41 Option C Modify Option A by additional back-pressure turbine added between the crossover outlet after steam extraction and low-pressure turbine inlet. 41

42 Option D Modify Option C by exchanging both backpressure turbines with throttle valves. 42

43 [1] Based on HHV Results Parameter Base Case Option A Option C Option D Gross Electric Output, MW Net Electric Output, MW Gross Plant Heat Rate, Btu/kWh (kj/kwh) ( ) ( ) ( ) ( ) Net Plant Heat Rate, Btu/kWh (kj/kwh) ( ) ( ) ( ) ( ) Steam Flow Rate for Regeneration, tons/hr (tonnes/hr) (723.96) (779.73) (779.73) (723.96) Net Plant Efficiency, %

44 Conclusions Aspen Plus is an effective tool for evaluating the energy penalty associated with steam extraction for CO 2 stripping. The benefits and challenges associated with each option are determined in a modeling environment. Additional modeling will utilize APEA to determine which scenario provides the best economic benefit. 44

45 Contact Information Energy & Environmental Research Center University of North Dakota 15 North 23rd Street, Stop 9018 Grand Forks, North Dakota World Wide Web: Telephone No. (701) Fax No. (701) Josh Stanislowski, Research Manager (701) Tony Snyder, Research Engineer (701)

46 Want to see similar results? Consider a training class from AspenTech Aspen Technology, Inc. All rights reserved 46

47 Aspen Plus: Process Modeling Training Aspen Plus: Process Modeling (EAP101) May 7, 2012 Denver, CO May 14, 2012 Calgary, AB, Canada May 21, 2012 Reading, UK May 21, 2012 Virtual-Latin America Gain the practical skills and knowledge to begin modeling new and existing processes Build and troubleshoot flowsheet simulations Reduce process design time by testing various plant configurations Determine optimal process conditions to improve current processes Help de-bottleneck constraining parts of a process 2012 Aspen Technology, Inc. All rights reserved 47

48 CO2 Removal Training CO2 Removal Processes Using Aspen Plus (EAP2510) May 9, 2012 Virtual- Americas May 28, 2012 Reading, UK July 30, 2012 Reading, UK August 13, 2012 Houston, TX Determine and properly setup the necessary component physical properties and reactions needed to model CO2 removal processes using Aspen Plus. Learn the steps involved in modeling CO2 removal processes. Model absorbers and regenerators systems using chemical and physical solvents. Setup, run and interpret results for a rate-based model of a CO2 Absorber. Use detailed rate-based modeling to understand and improve separation performance Aspen Technology, Inc. All rights reserved 48

49 Aspen Rate Based Distillation Training Aspen Rate Based Distillation (EAP251) July 5, 2012 Reading, UK July 19, 2012 Houston, TX November 11, 2012 Reading, UK November 5, 2012 Pune, India Learn how to use the Aspen Rate-Based Distillation to predict tray efficiency or HETP and evaluate column set up. Learn how to use Rate-Based Distillation model to match real column data. Create accurate simulations of reactive and non-reactive column separations Aspen Technology, Inc. All rights reserved 49

50 Aspen Process Economic Analyzer (APEA) Training Aspen Process Economic Analyzer (EEE102) June 11, 2012 Houston, TX July 24, 2012 Tokyo, Japan August 6, 2012 Houston, TX August 6, 2012 Reading, UK Maximize your company s return on investment (ROI) and reduce the risk involved in making decisions. Define your project more accurately by integrating operating cost, capital cost, and schedule. Reduce estimation variability by adopting a consistent methodology. Increase costing accuracy by generating detailed reports for analysis, traceable to line items not lump sums of money Aspen Technology, Inc. All rights reserved 50

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56 Contact Information Sanjeev Mullick, Industry Marketing Director, AspenTech Rob Hockley, Senior Business Consultant, AspenTech For any Aspen Plus product family communication: For more information on Aspen Plus and related products: Aspen Technology, Inc. All rights reserved 56

57 Contact Information Energy & Environmental Research Center University of North Dakota 15 North 23rd Street, Stop 9018 Grand Forks, North Dakota World Wide Web: Telephone No. (701) Fax No. (701) Josh Stanislowski, Research Manager (701) Tony Snyder, Research Engineer (701)