13 research outputs found
Using Dynamic Simulation to Evaluate Attemperator Operation in a Natural Gas Combined Cycle With Duct Burners in the Heat Recovery Steam Generator
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Multiobjective Optimization Power Generation Systems Involving Chemical Looping Combustion
Integrated Gasification Combined Cycle (IGCC) system using coal gasification is an important approach for future energy options. This work focuses on understading the system operation and optimizing it in the presence of uncertain operating conditions using ASPEN Plus and CAPE-OPEN compliant stochastic simulation and multiobjective optimization capabilities developed by Vishwamitra Research Institute. The feasible operating surface for the IGCC system is generated and deterministic multiobjective optimization is performed. Since the feasible operating space is highly non-convex, heuristics based techniques that do not require gradient information are used to generate the Pareto surface. Accurate CFD models are simultaneously developed for the gasifier and chemical looping combustion system to characterize and quantify the process uncertainty in the ASPEN model
Development of a Dynamic Model and Control System for Load-Following Studies of Supercritical Pulverized Coal Power Plants
Traditional energy production plants are increasingly forced to cycle their load and operate under low-load conditions in response to growth in intermittent renewable generation. A plant-wide dynamic model of a supercritical pulverized coal (SCPC) power plant has been developed in the Aspen Plus Dynamics® (APD) software environment and the impact of advanced control strategies on the transient responses of the key variables to load-following operation and disturbances can be studied. Models of various key unit operations, such as the steam turbine, are developed in Aspen Custom Modeler® (ACM) and integrated in the APD environment. A coordinated control system (CCS) is developed above the regulatory control layer. Three control configurations are evaluated for the control of the main steam; the reheat steam temperature is also controlled. For studying servo control performance of the CCS, the load is decreased from 100% to 40% at a ramp rate of 3% load per min. The impact of a disturbance due to a change in the coal feed composition is also studied. The CCS is found to yield satisfactory performance for both servo control and disturbance rejection
Reduced Order Model Based on Principal Component Analysis for Process Simulation and Optimization â€
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Virtual Simulation of Vision 21 Energy Plants
The Vision 21 Energy plants will be designed by combining several individual power, chemical, and fuel-conversion technologies. These independently developed technologies or technology modules can be interchanged and combined to form the complete Vision 21 plant that achieves the needed level of efficiency and environmental performance at affordable costs. The knowledge about each technology module must be captured in computer models so that the models can be linked together to simulate the entire Vision 21 power plant in a Virtual Simulation environment. Eventually the Virtual Simulation will find application in conceptual design, final design, plant operation and control, and operator training. In this project we take the first step towards developing such a Vision 21 Simulator. There are two main knowledge domains of a plant--the process domain (what is in the pipes), and the physical domain (the pipes and equipment that make up the plant). Over the past few decades, commercial software tools have been developed for each of these functions. However, there are three main problems that inhibit the design and operation of power plants: (1) Many of these tools, largely developed for chemicals and refining, have not been widely adopted in the power industry. (2) Tools are not integrated across functions. For example, the knowledge represented by computational fluid dynamics (CFD) models of equipment is not used in process-level simulations. (3) No tool exists for readily integrating the design and behavioral knowledge about components. These problems must be overcome to develop the Vision 21 Simulator. In this project our major objective is to achieve a seamless integration of equipment-level and process-level models and apply the integrated software to power plant simulations. Specifically we are developing user-friendly tools for linking process models (Aspen Plus) with detailed equipment models (FLUENT CFD and other proprietary models). Such integration will ensure that consistent and complete knowledge about the process is used for design and optimization. The technical objectives of the current project are the following: Develop a software integration tool called the V21-Controller to mediate the information exchange between FLUENT, other detailed equipment models, and Aspen Plus. Define and publish software interfaces so that software and equipment vendors may integrate their computer models into the software developed in this project. Demonstrate the application of the integrated software with two power plant simulations, one for a conventional steam plant and another for an advanced power cycle. The project was started in October 2000. Highlights of the accomplishments during the first year of the project are the following: Formed a multi-disciplinary project team consisting of chemical and mechanical engineers; computer scientists; CFD, process simulation, and plant design software developers; and power plant designers. Developed a prototype of CFD and process model integration: a stirred tank reactor model based on FLUENT was inserted into a flow sheet model based on Aspen Plus. The prototype was used to show the effect of shaft speed (a parameter in the CFD model) on the product yield and purity (results of process simulation). This demonstrated the optimization of an equipment item in the context of the entire plant rather than in isolation. Conducted a user survey and wrote the User Requirements, Software Requirements and Software Design documents for the V21-Controller. Adopted CAPE-OPEN standard interfaces for communications between equipment and process models. Developed a preliminary version of the V21-Controller based on CAPE-OPEN interfaces. Selected one unit of an existing conventional steam plant (Richmond Power & Light) as the first demonstration case and developed an Aspen Plus model of the steam-side of the unit. A model for the gas-side of the unit, based on ALSTOM's proprietary model INDVU, was integrated with the Aspen Plus model. An industrial Advisory Board was formed to guide the software development effort and one Advisory Board meeting was conducted. Because we are integrating widely used commercial software (Aspen Plus and FLUENT) we expect that the results of the project will find immediate commercial applications at the conclusion of the project. The future activities planned are the following: Complete and test the V21-Controller and complete the integration between process-level and equipment-level models. Conduct power plant Demonstration Case 1 simulations with the integrated software suite. Select power plant Demonstration Case 2 and conduct simulations. Prepare a mock up of a 3-D plant walk through to assess the integration of process and physical domain software in a future phase of the project
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Innovative computational tools and models for the design, optimization and control of carbon capture processes
The development and scale up of cost effective carbon capture processes is of paramount importance to enable the widespread deployment of these technologies to significantly reduce greenhouse gas emissions. The U.S. Department of Energy initiated the Carbon Capture Simulation Initiative (CCSI) in 2011 with the goal of developing a computational toolset that would enable industry to more effectively identify, design, scale up, operate, and optimize promising concepts (Miller et al., 2014). The CCSI Toolset consists of both multi-scale models as well as new computational tools. This paper focuses specifically on the PSE-related computational tools and models that provide new capabilities for integrating multi-scale models with advanced optimization, uncertainty quantification (UQ), and surrogate modeling techniques
Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)
The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format