The Experts below are selected from a list of 2502 Experts worldwide ranked by ideXlab platform
Richard S Middleton - One of the best experts on this subject based on the ideXlab platform.
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simccs an open source tool for optimizing co2 capture transport and Storage Infrastructure
Environmental Modelling and Software, 2020Co-Authors: Richard S Middleton, Brendan A. Hoover, Kevin EllettAbstract:Abstract Commercial-scale carbon capture and Storage (CCS) technology will involve deploying Infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, Storage sites, and the dedicated CO2 distribution pipelines are selected in a robust and cost-effective manner. Introduced in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS Infrastructure networks. SimCCS2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO2 source, sink, and transportation data, SimCCS2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is then solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.
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e-Energy - Efficient Design of CO2 Capture and Storage Infrastructure
Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019Co-Authors: Caleb Whitman, Richard S Middleton, Brendan A. Hoover, Kevin EllettAbstract:CO2 capture and Storage (CCS) is a climate change mitigation strategy that aims to reduce the amount of CO2 vented into the atmosphere from industrial processes. Designing cost-effective CCS Infrastructure is critical to meet CO2 emission reduction targets and is a computationally challenging problem. We outline this challenge and present a novel algorithm to generate high quality CCS Infrastructure designs.
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a dynamic model for optimally phasing in co2 capture and Storage Infrastructure
Environmental Modelling and Software, 2012Co-Authors: Richard S Middleton, Gordon N Keating, Michael Kuby, Rajesh J PawarAbstract:CO"2 capture and Storage (CCS) is a climate-change mitigation strategy that requires an investment of many billions of dollars and tens of thousands of miles of dedicated CO"2 pipelines. To be effective, scientists, stakeholders, and policy makers will have to understand how as well as when to deploy large-scale CCS Infrastructure. This will require comprehensive modeling that takes into account detailed costs, engineering, and environmental concerns. We introduce a new and comprehensive model, SimCCS^T^I^M^E, that is capable of spatially and temporally optimizing CO"2 management-capture, transport, and Storage of large quantities of CO"2. The model minimizes CCS Infrastructure costs while simultaneously deciding where, how much, and when to capture, transport, and store CO"2. We demonstrate the SimCCS^T^I^M^E model using real data from the Texas panhandle. Results show that the model minimizes CCS costs, while meeting rising demand to capture and store CO"2, by gradually expanding the CCS network. The model identifies non-intuitive cost savings by overbuilding Infrastructure in early time periods, and then fully utilizing this Infrastructure in later years. Further, results show that there is significant benefit for planning a cooperative and integrated CCS system. Finally, we show how SimCCS^T^I^M^E offers significant advantages over myopic models that cannot integrate Infrastructure through time.
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effects of geologic reservoir uncertainty on co2 transport and Storage Infrastructure
International Journal of Greenhouse Gas Control, 2012Co-Authors: Richard S Middleton, Gordon N Keating, Hari S Viswanathan, Philip H Stauffer, Rajesh J PawarAbstract:CO2 capture and Storage (CCS) is a climate-change mitigation technology that can significantly reduce greenhouse gas emissions in the near future. To have a meaningful impact, CCS Infrastructure will have to be deployed on a massive scale; in the U.S. this will require capturing CO2 from hundreds of fossil fuel power plants and building a dedicated pipeline network to transport a volume of CO2 greater than domestic oil consumption. In this paper, we analyze the effect of geologic reservoir uncertainty on constructing CCS Infrastructure—geologic uncertainty can impact reservoir cost and capacity estimates by as much as an order of magnitude. This uncertainty propagates through the capture–transport–Storage system, influencing decisions including where and how much CO2 should be captured. We demonstrate the effect of geologic uncertainty using a proposed oil shale industry that could generate tens of millions of tonnes of CO2 each year. We show that uncertainty can make transport and Storage costs deviate by over 100% and that CCS Infrastructure, particularly the optimal pipeline network, can considerably diverge spatially. Finally, we draw conclusions on how geologic uncertainty may end up being a driving factor on how major industries decide to manage produced CO2.
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a comprehensive carbon capture and Storage Infrastructure model
Energy Procedia, 2009Co-Authors: Richard S Middleton, Jeffrey M. BielickiAbstract:Abstract In this paper we present a spatial optimization model that comprehensively models carbon capture and s torage (CCS) Infrastructure, from source -to -sink. The model optimally and simultaneously chooses at which sources and how much CO2 should be captured, at which reservoirs (or sinks) and how much CO2 should be injected and stored, where a pipeline network should be constructed and at what capacity, and how to distribute CO2 among the networked sources and reservoirs. A key contribution of the model is the ability to link sources and reservoirs using a realistic and capacitated pipeline network.
Jeffrey M. Bielicki - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive carbon capture and Storage Infrastructure model
Energy Procedia, 2009Co-Authors: Richard S Middleton, Jeffrey M. BielickiAbstract:Abstract In this paper we present a spatial optimization model that comprehensively models carbon capture and s torage (CCS) Infrastructure, from source -to -sink. The model optimally and simultaneously chooses at which sources and how much CO2 should be captured, at which reservoirs (or sinks) and how much CO2 should be injected and stored, where a pipeline network should be constructed and at what capacity, and how to distribute CO2 among the networked sources and reservoirs. A key contribution of the model is the ability to link sources and reservoirs using a realistic and capacitated pipeline network.
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A comprehensive carbon capture and Storage Infrastructure model
Energy Procedia, 2009Co-Authors: Richard S Middleton, Jeffrey M. BielickiAbstract:In this paper we present a spatial optimization model that comprehensively models carbon capture and s torage (CCS) Infrastructure, from source -to -sink. The model optimally and simultaneously chooses at which sources and how much CO2should be captured, at which reservoirs (or sinks) and how much CO2should be injected and stored, where a pipeline network should be constructed and at what capacity, and how to distribute CO2among the networked sources and reservoirs. A key contribution of the model is the ability to link sources and reservoirs using a realistic and capacitated pipeline network. © 2009 Elsevier Ltd. All rights reserved.
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returns to scale in carbon capture and Storage Infrastructure and deployment
2008Co-Authors: Jeffrey M. BielickiAbstract:The degree to which carbon capture and Storage (CCS) is deployed will be partly determined by the returns to scale of the technological system that captures, transports, and stores carbon dioxide (CO2). This technological system spatially connects the organization of CO2 point sources with the organization of geologic CO2 Storage reservoirs. These point sources and Storage reservoirs are heterogeneous in the amount of CO2 that they produce or store and in the costs of capturing or storing CO2, and the associated cost structures interact to determine the returns to scale for the entire coupled system. The SimCCS cost-minimizing geospatial deployment model is used to deploy CCS for a variety of combinations of CO2 sources and injection reservoirs and determine the returns to scale for CCS deployment and unravel the determinants thereof. SimCCS minimizes the total costs of the entire capture, transport, and Storage system by simultaneously determining how much CO2 is captured from each source, how much CO2 is stored in each Storage reservoir, and assigning CO2 flows through pipeline networks that include trunk distribution lines that are routed to minimize the influence of the social and physical topography. The returns to scale for the entire CCS system involves the interaction of the cost structures for each link in the CCS chain capture at the source, transport through the network, and Storage at the reservoir ∗This paper is was also presented at the 7 Annual Conference on Carbon Capture and Sequestration, May 5-8, 2008 and an earlier version will be available in the conference proceedings. †This paper has benefitted from conversations with John Holdren, Juha Kiviluoma, Richard Middleton, and Richard Zeckhauser ‡Portions of this work have been funded by: BP Alternative Energy, BP Climate Mitigation Initiative, The Energy Foundation, Shell Exploration and Development Company, Zero Emissions Research Technology (ZERT) funded through Los Alamos National Laboratory, and the Joseph G. Crump Fellowship. §Project on Energy Technology Innovation Policy, Belfer Center for Science and International Affairs, Harvard Kennedy School, 79 John F. Kennedy Street, Cambridge MA, 02138
Cees Th.a.m. De Laat - One of the best experts on this subject based on the ideXlab platform.
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A Trusted Data Storage Infrastructure for Grid-Based Medical Applications
International Journal of Grid and High Performance Computing, 2009Co-Authors: Guido J. Van 't Noordende, Silvia D. Olabarriaga, Matthijs R. Koot, Cees Th.a.m. De LaatAbstract:Most existing Grid technology has been designed with performance and scalability in mind. When using Grid Infrastructure for medical applications, privacy and security considerations become paramount. Privacy aspects require a re-thinking of the design and implementation of common Grid middleware components. This article presents a novel security framework for handling privacy sensitive information on the Grid, and describes the privacy and security considerations which impacted its design.
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A Trusted Data Storage Infrastructure for Grid-Based Medical Applications
2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGRID), 2008Co-Authors: Guido J. Van 't Noordende, Silvia D. Olabarriaga, Matthijs R. Koot, Cees Th.a.m. De LaatAbstract:Most existing Grid technology has been foremost designed with performance and scalability in mind. When using Grid Infrastructure for medical applications, privacy and security considerations become paramount. This leads to a re-thinking of implementation and deployment aspects of common components of the current Grid architecture. This paper describes the impact of privacy and security considerations on the Grid Infrastructure design, and enumerates trust aspects which must underpin the design of Grid technology to support medical applications. We propose a novel security framework for securely handling privacy sensitive information on the Grid.
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CCGRID - A Trusted Data Storage Infrastructure for Grid-Based Medical Applications
2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGRID), 2008Co-Authors: Guido J. Van 't Noordende, Silvia D. Olabarriaga, Matthijs R. Koot, Cees Th.a.m. De LaatAbstract:Most existing Grid technology has been foremost designed with performance and scalability in mind. When using Grid Infrastructure for medical applications, privacy and security considerations become paramount. This leads to a re-thinking of implementation and deployment aspects of common components of the current Grid architecture. This paper describes the impact of privacy and security considerations on the Grid Infrastructure design, and enumerates trust aspects which must underpin the design of Grid technology to support medical applications. We propose a novel security framework for securely handling privacy sensitive information on the Grid.
Kevin Ellett - One of the best experts on this subject based on the ideXlab platform.
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simccs an open source tool for optimizing co2 capture transport and Storage Infrastructure
Environmental Modelling and Software, 2020Co-Authors: Richard S Middleton, Brendan A. Hoover, Kevin EllettAbstract:Abstract Commercial-scale carbon capture and Storage (CCS) technology will involve deploying Infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, Storage sites, and the dedicated CO2 distribution pipelines are selected in a robust and cost-effective manner. Introduced in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS Infrastructure networks. SimCCS2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO2 source, sink, and transportation data, SimCCS2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is then solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.
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e-Energy - Efficient Design of CO2 Capture and Storage Infrastructure
Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019Co-Authors: Caleb Whitman, Richard S Middleton, Brendan A. Hoover, Kevin EllettAbstract:CO2 capture and Storage (CCS) is a climate change mitigation strategy that aims to reduce the amount of CO2 vented into the atmosphere from industrial processes. Designing cost-effective CCS Infrastructure is critical to meet CO2 emission reduction targets and is a computationally challenging problem. We outline this challenge and present a novel algorithm to generate high quality CCS Infrastructure designs.
Rajesh J Pawar - One of the best experts on this subject based on the ideXlab platform.
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a dynamic model for optimally phasing in co2 capture and Storage Infrastructure
Environmental Modelling and Software, 2012Co-Authors: Richard S Middleton, Gordon N Keating, Michael Kuby, Rajesh J PawarAbstract:CO"2 capture and Storage (CCS) is a climate-change mitigation strategy that requires an investment of many billions of dollars and tens of thousands of miles of dedicated CO"2 pipelines. To be effective, scientists, stakeholders, and policy makers will have to understand how as well as when to deploy large-scale CCS Infrastructure. This will require comprehensive modeling that takes into account detailed costs, engineering, and environmental concerns. We introduce a new and comprehensive model, SimCCS^T^I^M^E, that is capable of spatially and temporally optimizing CO"2 management-capture, transport, and Storage of large quantities of CO"2. The model minimizes CCS Infrastructure costs while simultaneously deciding where, how much, and when to capture, transport, and store CO"2. We demonstrate the SimCCS^T^I^M^E model using real data from the Texas panhandle. Results show that the model minimizes CCS costs, while meeting rising demand to capture and store CO"2, by gradually expanding the CCS network. The model identifies non-intuitive cost savings by overbuilding Infrastructure in early time periods, and then fully utilizing this Infrastructure in later years. Further, results show that there is significant benefit for planning a cooperative and integrated CCS system. Finally, we show how SimCCS^T^I^M^E offers significant advantages over myopic models that cannot integrate Infrastructure through time.
-
effects of geologic reservoir uncertainty on co2 transport and Storage Infrastructure
International Journal of Greenhouse Gas Control, 2012Co-Authors: Richard S Middleton, Gordon N Keating, Hari S Viswanathan, Philip H Stauffer, Rajesh J PawarAbstract:CO2 capture and Storage (CCS) is a climate-change mitigation technology that can significantly reduce greenhouse gas emissions in the near future. To have a meaningful impact, CCS Infrastructure will have to be deployed on a massive scale; in the U.S. this will require capturing CO2 from hundreds of fossil fuel power plants and building a dedicated pipeline network to transport a volume of CO2 greater than domestic oil consumption. In this paper, we analyze the effect of geologic reservoir uncertainty on constructing CCS Infrastructure—geologic uncertainty can impact reservoir cost and capacity estimates by as much as an order of magnitude. This uncertainty propagates through the capture–transport–Storage system, influencing decisions including where and how much CO2 should be captured. We demonstrate the effect of geologic uncertainty using a proposed oil shale industry that could generate tens of millions of tonnes of CO2 each year. We show that uncertainty can make transport and Storage costs deviate by over 100% and that CCS Infrastructure, particularly the optimal pipeline network, can considerably diverge spatially. Finally, we draw conclusions on how geologic uncertainty may end up being a driving factor on how major industries decide to manage produced CO2.
