A new optimization approach to energy network modeling: anthropogenic CO2 capture coupled with enhanced oil recovery
SUMMARY To meet next generation energy needs such as wind‐ and solar‐generated electricity, enhanced oil recovery (EOR), CO2 capture and storage (CCS), and biofuels, the US will have to construct tens to hundreds of thousands of kilometers of new transmission lines and pipelines. Energy network mode...
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To meet next generation energy needs such as wind‐ and solar‐generated electricity, enhanced oil recovery (EOR), CO2 capture and storage (CCS), and biofuels, the US will have to construct tens to hundreds of thousands of kilometers of new transmission lines and pipelines. Energy network models are central to optimizing these energy resources, including how best to produce, transport, and deliver energy‐related products such as oil, natural gas, electricity, and CO2. Consequently, understanding how to model new transmission lines and pipelines is central to this process. However, current energy models use simplifying assumptions for deploying pipelines and transmission lines, leading to the design of more costly and inefficient energy networks. In this paper, we introduce a two‐stage optimization approach for modeling CCS infrastructure. We show how CO2 pipelines with discrete capacities can be ‘linearized’ without loss of information and accuracy, therefore allowing necessarily complex energy models to be solved. We demonstrate the new approach by designing a CCS network that collects large volumes of anthropogenic CO2 (up to 45 million tonnes of CO2 per year) from ethylene production facilities and delivers the CO2 to depleted oil fields to stimulate recovery through EOR. Utilization of anthropogenic CO2 has great potential to jumpstart commercial‐scale CCS while simultaneously reducing the carbon footprint of domestic oil production. Model outputs illustrate the engineering challenge and spatial extent of CCS infrastructure, as well as the costs (or profits) of deploying CCS technology. We show that the new linearized approach is able to offer insights that other network approaches cannot reveal and how the approach can change how we develop future energy systems including transporting massive volumes of shale gas and biofuels as well as electricity transmission for wind and solar energy. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.
Next generation energy needs‐such as unconventional gas, biofuels, wind and solar energy, and CO2 capture and storage (CCS) will require tens to hundreds of thousands of kilometers of new transmission lines and pipelines. We present a new two‐stage optimization approach for modeling large‐scale energy networks. We demonstrate the approach using CCS infrastructure. Specifically, we design infrastructure to capture anthropogenic CO2 from ethylene production, transport th |
doi_str_mv | 10.1002/er.2993 |
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To meet next generation energy needs such as wind‐ and solar‐generated electricity, enhanced oil recovery (EOR), CO2 capture and storage (CCS), and biofuels, the US will have to construct tens to hundreds of thousands of kilometers of new transmission lines and pipelines. Energy network models are central to optimizing these energy resources, including how best to produce, transport, and deliver energy‐related products such as oil, natural gas, electricity, and CO2. Consequently, understanding how to model new transmission lines and pipelines is central to this process. However, current energy models use simplifying assumptions for deploying pipelines and transmission lines, leading to the design of more costly and inefficient energy networks. In this paper, we introduce a two‐stage optimization approach for modeling CCS infrastructure. We show how CO2 pipelines with discrete capacities can be ‘linearized’ without loss of information and accuracy, therefore allowing necessarily complex energy models to be solved. We demonstrate the new approach by designing a CCS network that collects large volumes of anthropogenic CO2 (up to 45 million tonnes of CO2 per year) from ethylene production facilities and delivers the CO2 to depleted oil fields to stimulate recovery through EOR. Utilization of anthropogenic CO2 has great potential to jumpstart commercial‐scale CCS while simultaneously reducing the carbon footprint of domestic oil production. Model outputs illustrate the engineering challenge and spatial extent of CCS infrastructure, as well as the costs (or profits) of deploying CCS technology. We show that the new linearized approach is able to offer insights that other network approaches cannot reveal and how the approach can change how we develop future energy systems including transporting massive volumes of shale gas and biofuels as well as electricity transmission for wind and solar energy. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.
Next generation energy needs‐such as unconventional gas, biofuels, wind and solar energy, and CO2 capture and storage (CCS) will require tens to hundreds of thousands of kilometers of new transmission lines and pipelines. We present a new two‐stage optimization approach for modeling large‐scale energy networks. We demonstrate the approach using CCS infrastructure. Specifically, we design infrastructure to capture anthropogenic CO2 from ethylene production, transport the CO2 in a dedicated pipeline network, and store the CO2 in the subsurface while stimulating oil production through enhanced oil recovery.</description><identifier>ISSN: 0363-907X</identifier><identifier>EISSN: 1099-114X</identifier><identifier>DOI: 10.1002/er.2993</identifier><identifier>CODEN: IJERDN</identifier><language>eng</language><publisher>Chichester: Blackwell Publishing Ltd</publisher><subject>Applied sciences ; Biodiesel fuels ; climate change policy ; CO2 capture and storage (CCS) ; Energy ; energy network modeling ; Energy policy ; enhanced oil recovery (EOR) ; Exact sciences and technology ; Optimization ; Petroleum industry ; Petroleum production ; pipeline optimization ; Pipelines ; SimCCS ; Studies</subject><ispartof>International journal of energy research, 2013-11, Vol.37 (14), p.1794-1810</ispartof><rights>Published 2012. This article is a U.S. Government work and is in the public domain in the USA.</rights><rights>2014 INIST-CNRS</rights><rights>Published 2013. This article is a U.S. Government work and is in the public domain in the USA.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fer.2993$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fer.2993$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27854520$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Middleton, Richard S.</creatorcontrib><title>A new optimization approach to energy network modeling: anthropogenic CO2 capture coupled with enhanced oil recovery</title><title>International journal of energy research</title><addtitle>Int. J. Energy Res</addtitle><description>SUMMARY
To meet next generation energy needs such as wind‐ and solar‐generated electricity, enhanced oil recovery (EOR), CO2 capture and storage (CCS), and biofuels, the US will have to construct tens to hundreds of thousands of kilometers of new transmission lines and pipelines. Energy network models are central to optimizing these energy resources, including how best to produce, transport, and deliver energy‐related products such as oil, natural gas, electricity, and CO2. Consequently, understanding how to model new transmission lines and pipelines is central to this process. However, current energy models use simplifying assumptions for deploying pipelines and transmission lines, leading to the design of more costly and inefficient energy networks. In this paper, we introduce a two‐stage optimization approach for modeling CCS infrastructure. We show how CO2 pipelines with discrete capacities can be ‘linearized’ without loss of information and accuracy, therefore allowing necessarily complex energy models to be solved. We demonstrate the new approach by designing a CCS network that collects large volumes of anthropogenic CO2 (up to 45 million tonnes of CO2 per year) from ethylene production facilities and delivers the CO2 to depleted oil fields to stimulate recovery through EOR. Utilization of anthropogenic CO2 has great potential to jumpstart commercial‐scale CCS while simultaneously reducing the carbon footprint of domestic oil production. Model outputs illustrate the engineering challenge and spatial extent of CCS infrastructure, as well as the costs (or profits) of deploying CCS technology. We show that the new linearized approach is able to offer insights that other network approaches cannot reveal and how the approach can change how we develop future energy systems including transporting massive volumes of shale gas and biofuels as well as electricity transmission for wind and solar energy. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.
Next generation energy needs‐such as unconventional gas, biofuels, wind and solar energy, and CO2 capture and storage (CCS) will require tens to hundreds of thousands of kilometers of new transmission lines and pipelines. We present a new two‐stage optimization approach for modeling large‐scale energy networks. We demonstrate the approach using CCS infrastructure. Specifically, we design infrastructure to capture anthropogenic CO2 from ethylene production, transport the CO2 in a dedicated pipeline network, and store the CO2 in the subsurface while stimulating oil production through enhanced oil recovery.</description><subject>Applied sciences</subject><subject>Biodiesel fuels</subject><subject>climate change policy</subject><subject>CO2 capture and storage (CCS)</subject><subject>Energy</subject><subject>energy network modeling</subject><subject>Energy policy</subject><subject>enhanced oil recovery (EOR)</subject><subject>Exact sciences and technology</subject><subject>Optimization</subject><subject>Petroleum industry</subject><subject>Petroleum production</subject><subject>pipeline optimization</subject><subject>Pipelines</subject><subject>SimCCS</subject><subject>Studies</subject><issn>0363-907X</issn><issn>1099-114X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNo9kF1PwjAUhhujiYjGv9DEeGWG7bp1m3eEIJqgGCWRu6Z0Z1AY6-yKE3-9JRjOzZuT85z3fCB0TUmPEhLeg-2FWcZOUIeSLAsojWanqEMYZ0FGktk5umiaFSG-RpMOcn1cQYtN7fRG_0qnTYVlXVsj1RI7g6ECu9h5xrXGrvHG5FDqavGAZeWW1tRmAZVWeDAJsZK121rAymzrEnLcarf0_UtZKZ8ZXWILynyD3V2is0KWDVz9axd9PA6ng6dgPBk9D_rjYMHCiAURgzxO_E0ki3lKqUxSkjPI5qwgRVgAz-V8zpViMoqBFz5owRUtCEmlJKyLbg6u_pqvLTROrMzWVn6goFHEOE1Dlnrq9p-SjZJlYf26uhG11RtpdyJM0jiKw73b3YFrdQm7Y50Ssf-6ACv2XxfD9714OjjQunHwc6SlXQuesCQWn68jwaej2Rt9mQnC_gDNc4b7</recordid><startdate>201311</startdate><enddate>201311</enddate><creator>Middleton, Richard S.</creator><general>Blackwell Publishing Ltd</general><general>Wiley</general><general>Hindawi Limited</general><scope>BSCLL</scope><scope>IQODW</scope><scope>7SP</scope><scope>7ST</scope><scope>7TB</scope><scope>7TN</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>F28</scope><scope>FR3</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>SOI</scope></search><sort><creationdate>201311</creationdate><title>A new optimization approach to energy network modeling: anthropogenic CO2 capture coupled with enhanced oil recovery</title><author>Middleton, Richard S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g3243-43ed570020956811a780d3e9b3f0f2fe6dabb6cc3a45e6ffff1f6c1f008aa03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Applied sciences</topic><topic>Biodiesel fuels</topic><topic>climate change policy</topic><topic>CO2 capture and storage (CCS)</topic><topic>Energy</topic><topic>energy network modeling</topic><topic>Energy policy</topic><topic>enhanced oil recovery (EOR)</topic><topic>Exact sciences and technology</topic><topic>Optimization</topic><topic>Petroleum industry</topic><topic>Petroleum production</topic><topic>pipeline optimization</topic><topic>Pipelines</topic><topic>SimCCS</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Middleton, Richard S.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>International journal of energy research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Middleton, Richard S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new optimization approach to energy network modeling: anthropogenic CO2 capture coupled with enhanced oil recovery</atitle><jtitle>International journal of energy research</jtitle><addtitle>Int. J. Energy Res</addtitle><date>2013-11</date><risdate>2013</risdate><volume>37</volume><issue>14</issue><spage>1794</spage><epage>1810</epage><pages>1794-1810</pages><issn>0363-907X</issn><eissn>1099-114X</eissn><coden>IJERDN</coden><abstract>SUMMARY
To meet next generation energy needs such as wind‐ and solar‐generated electricity, enhanced oil recovery (EOR), CO2 capture and storage (CCS), and biofuels, the US will have to construct tens to hundreds of thousands of kilometers of new transmission lines and pipelines. Energy network models are central to optimizing these energy resources, including how best to produce, transport, and deliver energy‐related products such as oil, natural gas, electricity, and CO2. Consequently, understanding how to model new transmission lines and pipelines is central to this process. However, current energy models use simplifying assumptions for deploying pipelines and transmission lines, leading to the design of more costly and inefficient energy networks. In this paper, we introduce a two‐stage optimization approach for modeling CCS infrastructure. We show how CO2 pipelines with discrete capacities can be ‘linearized’ without loss of information and accuracy, therefore allowing necessarily complex energy models to be solved. We demonstrate the new approach by designing a CCS network that collects large volumes of anthropogenic CO2 (up to 45 million tonnes of CO2 per year) from ethylene production facilities and delivers the CO2 to depleted oil fields to stimulate recovery through EOR. Utilization of anthropogenic CO2 has great potential to jumpstart commercial‐scale CCS while simultaneously reducing the carbon footprint of domestic oil production. Model outputs illustrate the engineering challenge and spatial extent of CCS infrastructure, as well as the costs (or profits) of deploying CCS technology. We show that the new linearized approach is able to offer insights that other network approaches cannot reveal and how the approach can change how we develop future energy systems including transporting massive volumes of shale gas and biofuels as well as electricity transmission for wind and solar energy. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.
Next generation energy needs‐such as unconventional gas, biofuels, wind and solar energy, and CO2 capture and storage (CCS) will require tens to hundreds of thousands of kilometers of new transmission lines and pipelines. We present a new two‐stage optimization approach for modeling large‐scale energy networks. We demonstrate the approach using CCS infrastructure. Specifically, we design infrastructure to capture anthropogenic CO2 from ethylene production, transport the CO2 in a dedicated pipeline network, and store the CO2 in the subsurface while stimulating oil production through enhanced oil recovery.</abstract><cop>Chichester</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/er.2993</doi><tpages>17</tpages></addata></record> |
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subjects | Applied sciences Biodiesel fuels climate change policy CO2 capture and storage (CCS) Energy energy network modeling Energy policy enhanced oil recovery (EOR) Exact sciences and technology Optimization Petroleum industry Petroleum production pipeline optimization Pipelines SimCCS Studies |
title | A new optimization approach to energy network modeling: anthropogenic CO2 capture coupled with enhanced oil recovery |
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