Application of a two-level rolling horizon optimization scheme to a solid-oxide fuel cell and compressed air energy storage plant for the optimal supply of zero-emissions peaking power
•A two-level rolling horizon optimization method is formulated and presented.•A coal-fueled SOFC/CAES plant with 100% CCS is simulated using the proposed RHO approach is simulated for one year.•The new two-level RHOimproves load-following of the SOFC/CAES plant by nearly 90% compared to the previous...
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Veröffentlicht in: | Computers & chemical engineering 2016-11, Vol.94, p.235-249 |
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creator | Nease, Jake Monteiro, Nina Adams, Thomas A. |
description | •A two-level rolling horizon optimization method is formulated and presented.•A coal-fueled SOFC/CAES plant with 100% CCS is simulated using the proposed RHO approach is simulated for one year.•The new two-level RHOimproves load-following of the SOFC/CAES plant by nearly 90% compared to the previous method.•Larger CAES volumes lead to better load following, albeit with diminishing returns.•The SOFC/CAES system, when combined with RHO, has potential as a stand-alone peaking plant with zero emissions.
We present a new two-level rolling horizon optimization framework applied to a zero-emissions coal-fueled solid-oxide fuel cell power plant with compressed air energy storage for peaking applications. Simulations are performed where the scaled hourly demand for the year 2014 from the Ontario, Canada market is met as closely as possible. It was found that the proposed two-level strategy, by slowly adjusting the SOFC stack power upstream of the storage section, can improve load-following performance by 86% compared to the single-level optimization method proposed previously. A performance analysis indicates that the proposed approach uses the available storage volume to almost its maximum potential, with little improvement possible without changing the system itself. Further improvement to load-following is possible by increasing storage volumes, but with diminishing returns. Using an economically-focused objective function can improve annual revenue generation by as much as 6.5%, but not without a significant drop-off in load-following performance. |
doi_str_mv | 10.1016/j.compchemeng.2016.08.004 |
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We present a new two-level rolling horizon optimization framework applied to a zero-emissions coal-fueled solid-oxide fuel cell power plant with compressed air energy storage for peaking applications. Simulations are performed where the scaled hourly demand for the year 2014 from the Ontario, Canada market is met as closely as possible. It was found that the proposed two-level strategy, by slowly adjusting the SOFC stack power upstream of the storage section, can improve load-following performance by 86% compared to the single-level optimization method proposed previously. A performance analysis indicates that the proposed approach uses the available storage volume to almost its maximum potential, with little improvement possible without changing the system itself. Further improvement to load-following is possible by increasing storage volumes, but with diminishing returns. Using an economically-focused objective function can improve annual revenue generation by as much as 6.5%, but not without a significant drop-off in load-following performance.</description><identifier>ISSN: 0098-1354</identifier><identifier>EISSN: 1873-4375</identifier><identifier>DOI: 10.1016/j.compchemeng.2016.08.004</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Carbon capture ; Coal ; Compressed air ; Compressed air energy storage ; Computer simulation ; Economics ; Energy storage ; Horizon ; Markets ; Mathematical models ; Optimization ; Peaking power ; Solid oxide fuel cells</subject><ispartof>Computers & chemical engineering, 2016-11, Vol.94, p.235-249</ispartof><rights>2016 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c442t-17b61b25442b63e388452e30fa846681be6f2418d34ad6e661400b6b0e6bb8513</citedby><cites>FETCH-LOGICAL-c442t-17b61b25442b63e388452e30fa846681be6f2418d34ad6e661400b6b0e6bb8513</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0098135416302654$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids></links><search><creatorcontrib>Nease, Jake</creatorcontrib><creatorcontrib>Monteiro, Nina</creatorcontrib><creatorcontrib>Adams, Thomas A.</creatorcontrib><title>Application of a two-level rolling horizon optimization scheme to a solid-oxide fuel cell and compressed air energy storage plant for the optimal supply of zero-emissions peaking power</title><title>Computers & chemical engineering</title><description>•A two-level rolling horizon optimization method is formulated and presented.•A coal-fueled SOFC/CAES plant with 100% CCS is simulated using the proposed RHO approach is simulated for one year.•The new two-level RHOimproves load-following of the SOFC/CAES plant by nearly 90% compared to the previous method.•Larger CAES volumes lead to better load following, albeit with diminishing returns.•The SOFC/CAES system, when combined with RHO, has potential as a stand-alone peaking plant with zero emissions.
We present a new two-level rolling horizon optimization framework applied to a zero-emissions coal-fueled solid-oxide fuel cell power plant with compressed air energy storage for peaking applications. Simulations are performed where the scaled hourly demand for the year 2014 from the Ontario, Canada market is met as closely as possible. It was found that the proposed two-level strategy, by slowly adjusting the SOFC stack power upstream of the storage section, can improve load-following performance by 86% compared to the single-level optimization method proposed previously. A performance analysis indicates that the proposed approach uses the available storage volume to almost its maximum potential, with little improvement possible without changing the system itself. Further improvement to load-following is possible by increasing storage volumes, but with diminishing returns. Using an economically-focused objective function can improve annual revenue generation by as much as 6.5%, but not without a significant drop-off in load-following performance.</description><subject>Carbon capture</subject><subject>Coal</subject><subject>Compressed air</subject><subject>Compressed air energy storage</subject><subject>Computer simulation</subject><subject>Economics</subject><subject>Energy storage</subject><subject>Horizon</subject><subject>Markets</subject><subject>Mathematical models</subject><subject>Optimization</subject><subject>Peaking power</subject><subject>Solid oxide fuel cells</subject><issn>0098-1354</issn><issn>1873-4375</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqNUcFuGyEURFUj1Un6D_TWy25gYTE-RlabRIqUS3JGLPvWxsULBZzE_rJ8XtlsDjn29MRjZt6MBqEflNSUUHG1q43fB7OFPYybuimrmsiaEP4FLahcsoqzZfsVLQhZyYqyln9D5yntCCENl3KB3q5DcNbobP2I_YA1zi--cvAMDkfvnB03eOujPU3fIdu9Pc3Y9H4TZ18oyTvbV_7V9oCHQ2EacA7rsceTuQgpQY-1jRhGiJsjTtlHvQEcnB4zHnzEeQuzvHY4HYql42TmBNFXsLcplYsJB9B_Jj_Bv0C8RGeDdgm-f8wL9PT71-P6trp_uLlbX99XhvMmV3TZCdo1bXl0ggGTkrcNMDJoyYWQtAMxNJzKnnHdCxCCckI60REQXSdbyi7Qz1k3RP_3ACmr4mfKp0fwh6RoEZQNW5G2QFcz1ESfUoRBhVgSxaOiRE1tqZ361Jaa2lJEqtJW4a5nLpQszxaiSsbCaKC3EUxWvbf_ofIPOSioeg</recordid><startdate>20161102</startdate><enddate>20161102</enddate><creator>Nease, Jake</creator><creator>Monteiro, Nina</creator><creator>Adams, Thomas A.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7U5</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20161102</creationdate><title>Application of a two-level rolling horizon optimization scheme to a solid-oxide fuel cell and compressed air energy storage plant for the optimal supply of zero-emissions peaking power</title><author>Nease, Jake ; Monteiro, Nina ; Adams, Thomas A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-17b61b25442b63e388452e30fa846681be6f2418d34ad6e661400b6b0e6bb8513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Carbon capture</topic><topic>Coal</topic><topic>Compressed air</topic><topic>Compressed air energy storage</topic><topic>Computer simulation</topic><topic>Economics</topic><topic>Energy storage</topic><topic>Horizon</topic><topic>Markets</topic><topic>Mathematical models</topic><topic>Optimization</topic><topic>Peaking power</topic><topic>Solid oxide fuel cells</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nease, Jake</creatorcontrib><creatorcontrib>Monteiro, Nina</creatorcontrib><creatorcontrib>Adams, Thomas A.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & chemical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nease, Jake</au><au>Monteiro, Nina</au><au>Adams, Thomas A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of a two-level rolling horizon optimization scheme to a solid-oxide fuel cell and compressed air energy storage plant for the optimal supply of zero-emissions peaking power</atitle><jtitle>Computers & chemical engineering</jtitle><date>2016-11-02</date><risdate>2016</risdate><volume>94</volume><spage>235</spage><epage>249</epage><pages>235-249</pages><issn>0098-1354</issn><eissn>1873-4375</eissn><abstract>•A two-level rolling horizon optimization method is formulated and presented.•A coal-fueled SOFC/CAES plant with 100% CCS is simulated using the proposed RHO approach is simulated for one year.•The new two-level RHOimproves load-following of the SOFC/CAES plant by nearly 90% compared to the previous method.•Larger CAES volumes lead to better load following, albeit with diminishing returns.•The SOFC/CAES system, when combined with RHO, has potential as a stand-alone peaking plant with zero emissions.
We present a new two-level rolling horizon optimization framework applied to a zero-emissions coal-fueled solid-oxide fuel cell power plant with compressed air energy storage for peaking applications. Simulations are performed where the scaled hourly demand for the year 2014 from the Ontario, Canada market is met as closely as possible. It was found that the proposed two-level strategy, by slowly adjusting the SOFC stack power upstream of the storage section, can improve load-following performance by 86% compared to the single-level optimization method proposed previously. A performance analysis indicates that the proposed approach uses the available storage volume to almost its maximum potential, with little improvement possible without changing the system itself. Further improvement to load-following is possible by increasing storage volumes, but with diminishing returns. Using an economically-focused objective function can improve annual revenue generation by as much as 6.5%, but not without a significant drop-off in load-following performance.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.compchemeng.2016.08.004</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Carbon capture Coal Compressed air Compressed air energy storage Computer simulation Economics Energy storage Horizon Markets Mathematical models Optimization Peaking power Solid oxide fuel cells |
title | Application of a two-level rolling horizon optimization scheme to a solid-oxide fuel cell and compressed air energy storage plant for the optimal supply of zero-emissions peaking power |
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