Computer-Aided Process Decision-making R&D for...
Transcript of Computer-Aided Process Decision-making R&D for...
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Computer-Aided Process Decision-making R&D for Advanced Energy Systems
Stephen E. Zitney , Ph.D. Director, Collaboratory for Process & Dynamic Systems Research
Energy Systems Initiative (ESI)
Computer-Aided Process Decision-making (CAPD)
Carnegie Mellon University
Pittsburgh, PA
March 7, 2010
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U.S. Energy Challenges
• Meet increasing demand
• Provide secure, affordable, and clean energy
• Address energy-water nexus
U.S. data from EIA, Annual Energy Outlook 2008
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U.S. Energy Challenges DOE 2020 Goals
• Clean energy – Near-zero levels of NOx, SOx,
PM, and Hg – 90% CO2 capture and
99%+ storage permanence • Affordable energy
– <35% increase in COE for post- and oxy-combustion capture
– <10% increase in COE for pre-combustion capture (e.g., IGCC)
• Energy-water nexus – Reduce freshwater withdrawal
and consumption by 70% or greater
References: 1. Existing Plants—Emissions and Capture Program Goals, U.S. DOE/National Energy Technology Laboratory, Draft Final Report, February 2009 2. Impact of Cost Escalation on Power Systems R&D Goals—Re-baselining APS, CS & FC GPRA R&D Goals, July 2008
IGCC Power Plant
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National Energy Technology Laboratory Where Energy Challenges Converge and Energy Solutions Emerge
• U.S. Department of Energy (DOE) national lab • Advances economic and energy security by: – Increasing efficiency, reliability, and economics
of advanced energy systems – While protecting the environment and promoting
sustainability • Accomplishes DOE mission by: – Implementing a broad spectrum of energy and
environmental R&D programs • >1,800 projects with total award value over $9B
– Conducting cutting-edge on-site R&D • Office of Research & Development • Institute for Advanced Energy Solutions (IAES)
– NETL/University R&D partnership » CMU, Pitt, PSU, VT, and WVU » $12M/yr, 40 faculty, and 160 PhDs/post-docs » 10 R&D thrust areas, including “Collaboratory for
Process & Dynamic Systems Research”
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Collaboratory for Process & Dynamic Systems Research Goals and Objectives
• Accelerate R&D on advanced models, methods, and tools for process systems engineering
APECS Co-Simulation of IGCC-CCS Plant
IGCC Power Plant
Energy Plant Lifecycle
• Apply to existing plants and emerging advanced energy systems with carbon capture & storage (CCS)
• Develop innovative solutions across energy plant lifecycle innovation, design, operations, and management
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Collaboratory for Process & Dynamic Systems Research Energy Application Areas
• Combustion – Natural Gas Combined Cycle (NGCC) – Pulverized Coal (PC) Combustion – Oxygen Combustion – Chemical Looping Combustion (CLC)
• Gasification – Integrated Gasification Combined Cycle (IGCC) – Polygeneration
• Chemicals, Liquid Fuels, H2, SNG – Chemical Looping Gasification (CLG) – IGCC/Fuel Cell Hybrids (IGFC)
• Carbon Capture and Storage (CCS) – Pre- and post-combustion – Absorption (e.g., physical/chemical solvents) – Adsorption (e.g., PSA/TSA/VSA, solid sorbents) – Membrane Separation, Cryogenics, Hydrates
Combustion Power Plant
IGCC Power Plant with CCS
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Collaboratory for Process & Dynamic Systems Research R&D Areas
• Innovation – Process Synthesis – Heat Exchanger/Water Networks
• Design – Process/Equipment Co-Simulation – Virtual Plant Simulation – Plant-wide Optimization – Risk and Uncertainty Analysis
• Operations – Dynamic Modeling and Simulation – Sensors and Control – Operator/Immersive Training Systems
• Management – Planning and Scheduling – Supply Chain Management – Enterprise-Wide Optimization
Energy Plant Lifecycle
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Collaboratory for Process & Dynamic Systems Research Process Innovation
• R&D Areas – Process Synthesis – Heat Exchanger Network Synthesis / Pinch Analysis – Reactor / Separation Network Synthesis – Water Network Synthesis
• Technology – Mixed Integer NonLinear Programming (MINLP) – Disjunctive Programming
• Projects – Optimal Synthesis of IGCC Systems
• R. Kamath, Profs. Grossmann and Biegler (CMU) – Optimization Approach to Process Synthesis
with Application to Pulverized Coal Power Plants with CO2 Capture and Water Networks • Dr. Diwekar (VRI)
– Optimal Synthesis of Pressure Swing Adsorption Cycles for Pre- and Post-Combustion CO2 Capture
• A. Agarwal, S. Vetukuri, Prof. Biegler (CMU)
IGCC Superstructure
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Collaboratory for Process & Dynamic Systems Research R&D Areas
• Innovation – Process Synthesis – Heat Exchanger/Water Networks
• Design – Process/Equipment Co-Simulation – Virtual Plant Simulation – Plant-wide Optimization – Risk and Uncertainty Analysis
• Operations – Dynamic Modeling and Simulation – Sensors and Control – Operator/Immersive Training Systems
• Management – Planning and Scheduling – Supply Chain Management – Enterprise-Wide Optimization
Energy Plant Lifecycle
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Collaboratory for Process & Dynamic Systems Research Design
• R&D Areas – Process/Equipment Co-Simulation – Virtual Plant Simulation – Plant-wide Optimization – Risk and Uncertainty Analysis
• Technologies – Steady-State Process Simulation – Computational Fluid Dynamics (CFD) – Reduced Order Modeling (ROM) – Nonlinear Programming (NLP) – Stochastic Simulation
• Projects – APECS R&D, SW Dev.
• ANSYS, ALSTOM, AspenTech, CMU
– APECS Applications • ALSTOM: PC, NGCC, Oxy-Fuel, CLC/G • Others: REI, OSU, WVU
– Reduced Order Modeling • Neural Networks, PCA, Kriging
– CMU, ANSYS • Multizonal Gasification ROMs
– Reaction Design – Virtual Power Plant Simulation
• APECS/VE-Suite Integration (VE-PSI) – Ames Laboratory
• US/UK Collaboration on Virtual Simulation – ALSTOM, PSE, ANSYS, Doosan, RWE
– Optimization of PC and IGCC Systems with CO2 Capture and Water Networks – NETL, CMU, WVU, IIT
– Stochastic/Multi-Objective Optimization
• Vishwamitra Research Institute (VRI) APECS/ EKMTM
VE-PSI
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Collaboratory for Process & Dynamic Systems Research R&D Areas
• Innovation – Process Synthesis – Heat Exchanger/Water Networks
• Design – Process/Equipment Co-Simulation – Virtual Plant Simulation – Plant-wide Optimization – Risk and Uncertainty Analysis
• Operations – Dynamic Modeling and Simulation – Sensors and Control – Operator/Immersive Training Systems
• Management – Planning and Scheduling – Supply Chain Management – Enterprise-Wide Optimization
Energy Plant Lifecycle
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Collaboratory for Process & Dynamic Systems Research Operations
• R&D Areas – Process Operability – Sensors and Control – Operator/Immersive Training
Systems • Technologies
– Dynamic Process Simulation – Virtual Plant Simulation – Model Predictive Control – Dynamic Optimization
• Projects – Plant-wide IGCC Dynamic
Simulation and Control+
• West Virginia University (WVU) – Dynamic Simulator Research &
Training Center+ • NETL, WVU, IOM, FCS,
Enginomix, EPRI, Ames Lab
• Projects – Nonlinear Model
Predictive Control (NMPC) of Air Separation Units (ASUs)+ • R. Huang, Prof. Biegler (CMU)
– Plant-wide IGCC Model Predictive Control (MPC)++
• Rensselaer Polytechnic Institute – MPC for GE Gasifier and Radiant
Syngas Cooler+++
• GE Global Research – Dynamic Simulation and Advanced
Controls for Hybrid Combustion-Gasification Chemical Looping+++ • ALSTOM Power, Univ. of Illinois
+ Funded by NETL IAES; ++ Funded by NETL’s University Coal Research (UCR) Program +++ Funded by NETL Advanced Research Program
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NETL Dynamic Simulator Research & Training Center
• R&D, education, and training for design, operation, and control of advanced energy systems
• Real-time dynamic simulators w/ operator training systems (OTS)
• Immersive training systems (ITS) • IGCC plant with CO2 capture
– OTS: Oct 2010; ITS: Jan 2011 • NETL collaborators
– WVU, FCS, Enginomix, EPRI – AEP, BP, Doosan, GRE, Southern, … – Invensys Operations Mgmt
• DynsimTM, InTouchTM, EYESimTM • Located at NETL & WVU/NRCCE • R&D: APC, Sensors, ROMs, VE, …
Zitney, S.E. and D. Wilbers, “NETL Advances Clean Coal Power Technology Utilizing Virtual Reality Training System,” Presented at 2010 Power Plant Simulation Conference, February 21-26, San Diego, CA (2010). Zitney, S.E. et al., “NETL to Establish Dynamic Simulation Research and Training Center to Promote IGCC Technology with CO2 Capture,” Proc. of the COAL-GEN 2009 Conference, August 19-21, Charlotte, NC (2009).
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Collaboratory for Process & Dynamic Systems Research R&D Areas
• Innovation – Process Synthesis – Heat Exchanger/Water Networks
• Design – Process/Equipment Co-Simulation – Virtual Plant Simulation – Plant-wide Optimization – Risk and Uncertainty Analysis
• Operations – Dynamic Modeling and Simulation – Sensors and Control – Operator/Immersive Training Systems
• Management – Planning and Scheduling – Supply Chain Management – Enterprise-Wide Optimization
Energy Plant Lifecycle
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Collaboratory for Process & Dynamic Systems Research Management
• R&D Areas – Planning and Scheduling – Supply Chain Management – Enterprise-Wide Optimization (EWO)
• Technology – Linear Programming (LP) – Multi-Period Mixed Integer
Linear Programming (MILP) – Stochastic Programming
• Potential Projects – Optimal model-based planning and scheduling for polygeneration plants – National supply chain model for optimal planning of the production and
distribution of liquid fuels with uncertainties in demands and supplies, as well as supply disruptions
– Integrated energy-water-CO2 model for planning, management, and optimization purposes
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• Accelerates R&D on advanced models, methods, and tools for process systems engineering
• Addresses challenges and develops innovative solutions across the energy plant lifecycle – APECS with EKM and VE-PSI – IGCC dynamic simulator and ITS
• Applies technology solutions to existing plants and emerging advanced energy systems
• Offers unique opportunities for collaborative R&D, technology transfer, and commercialization Energy Plant Lifecycle
Collaboratory for Process & Dynamic Systems Research Summary
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Thank You
Questions?
• For additional information, please contact: – Stephen E. Zitney, NETL
• EML: [email protected] • TEL: 304-285-1379