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Robust Planning for Hydrogen‐Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage
Since renewable energy is rapidly growing in the active distribution networks, the integrated energy system coupled with energy storage is a promising way to address the intermittent issues of renewable sources. This paper proposes an optimal planning model for the hydrogen‐based integrated energy s...
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Published in: | International transactions on electrical energy systems 2024-01, Vol.2024 (1) |
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description | Since renewable energy is rapidly growing in the active distribution networks, the integrated energy system coupled with energy storage is a promising way to address the intermittent issues of renewable sources. This paper proposes an optimal planning model for the hydrogen‐based integrated energy system (HIES) considering power to heat and hydrogen (P2HH) and seasonal hydrogen storage (SHS) to take full advantage of multienergy complementarity. To tackle the unstable factors introduced by renewable sources and varying loads, we apply robust optimization and stochastic programming theory to improve the robustness of the planning results. Meanwhile, we also consider the N‐1 contingency constraints to make the technology selection, capacity allocation, and economic operation more reliable. The complex constraints resulting from producing two independent binary variables are converted into mixed integer linear constraints, which can be solved effectively using the nested column‐and‐constraint generation algorithm. Numerical simulation demonstrates the effectiveness of the P2HH and SHS in reducing the total cost of the HIES planning. |
doi_str_mv | 10.1155/2024/1156761 |
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This paper proposes an optimal planning model for the hydrogen‐based integrated energy system (HIES) considering power to heat and hydrogen (P2HH) and seasonal hydrogen storage (SHS) to take full advantage of multienergy complementarity. To tackle the unstable factors introduced by renewable sources and varying loads, we apply robust optimization and stochastic programming theory to improve the robustness of the planning results. Meanwhile, we also consider the N‐1 contingency constraints to make the technology selection, capacity allocation, and economic operation more reliable. The complex constraints resulting from producing two independent binary variables are converted into mixed integer linear constraints, which can be solved effectively using the nested column‐and‐constraint generation algorithm. Numerical simulation demonstrates the effectiveness of the P2HH and SHS in reducing the total cost of the HIES planning.</description><identifier>ISSN: 2050-7038</identifier><identifier>EISSN: 2050-7038</identifier><identifier>DOI: 10.1155/2024/1156761</identifier><language>eng</language><publisher>Hoboken: Hindawi Limited</publisher><subject>Algorithms ; Alternative energy sources ; Carbon dioxide ; Complex variables ; Compressed natural gas ; Constraints ; Contingency ; Electricity ; Electricity distribution ; Energy distribution ; Energy industry ; Energy storage ; Flexibility ; Fossil fuels ; Heat ; Hydrogen ; Hydrogen production ; Hydrogen storage ; Independent variables ; Integrated energy systems ; Mathematical programming ; Mixed integer ; Renewable energy ; Renewable resources ; Robustness ; Stochastic programming</subject><ispartof>International transactions on electrical energy systems, 2024-01, Vol.2024 (1)</ispartof><rights>Copyright © 2024 Shufan Wang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c254t-f99f7534837adf24e811e7f128887051cbc3c4af975a2774503627afc95987293</cites><orcidid>0009-0003-3425-5618</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27898,27899</link.rule.ids></links><search><contributor>Xiaoqing Bai</contributor><creatorcontrib>Wang, Shufan</creatorcontrib><creatorcontrib>Yang, Dong</creatorcontrib><creatorcontrib>Zhang, Linglu</creatorcontrib><creatorcontrib>Chenmei, Lingzhi</creatorcontrib><title>Robust Planning for Hydrogen‐Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage</title><title>International transactions on electrical energy systems</title><description>Since renewable energy is rapidly growing in the active distribution networks, the integrated energy system coupled with energy storage is a promising way to address the intermittent issues of renewable sources. 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Yang, Dong ; Zhang, Linglu ; Chenmei, Lingzhi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c254t-f99f7534837adf24e811e7f128887051cbc3c4af975a2774503627afc95987293</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Alternative energy sources</topic><topic>Carbon dioxide</topic><topic>Complex variables</topic><topic>Compressed natural gas</topic><topic>Constraints</topic><topic>Contingency</topic><topic>Electricity</topic><topic>Electricity distribution</topic><topic>Energy distribution</topic><topic>Energy industry</topic><topic>Energy storage</topic><topic>Flexibility</topic><topic>Fossil fuels</topic><topic>Heat</topic><topic>Hydrogen</topic><topic>Hydrogen production</topic><topic>Hydrogen storage</topic><topic>Independent variables</topic><topic>Integrated energy systems</topic><topic>Mathematical programming</topic><topic>Mixed integer</topic><topic>Renewable energy</topic><topic>Renewable resources</topic><topic>Robustness</topic><topic>Stochastic programming</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Shufan</creatorcontrib><creatorcontrib>Yang, Dong</creatorcontrib><creatorcontrib>Zhang, Linglu</creatorcontrib><creatorcontrib>Chenmei, Lingzhi</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>International transactions on electrical energy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Shufan</au><au>Yang, Dong</au><au>Zhang, Linglu</au><au>Chenmei, Lingzhi</au><au>Xiaoqing Bai</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Robust Planning for Hydrogen‐Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage</atitle><jtitle>International transactions on electrical energy systems</jtitle><date>2024-01-01</date><risdate>2024</risdate><volume>2024</volume><issue>1</issue><issn>2050-7038</issn><eissn>2050-7038</eissn><abstract>Since renewable energy is rapidly growing in the active distribution networks, the integrated energy system coupled with energy storage is a promising way to address the intermittent issues of renewable sources. This paper proposes an optimal planning model for the hydrogen‐based integrated energy system (HIES) considering power to heat and hydrogen (P2HH) and seasonal hydrogen storage (SHS) to take full advantage of multienergy complementarity. To tackle the unstable factors introduced by renewable sources and varying loads, we apply robust optimization and stochastic programming theory to improve the robustness of the planning results. Meanwhile, we also consider the N‐1 contingency constraints to make the technology selection, capacity allocation, and economic operation more reliable. The complex constraints resulting from producing two independent binary variables are converted into mixed integer linear constraints, which can be solved effectively using the nested column‐and‐constraint generation algorithm. Numerical simulation demonstrates the effectiveness of the P2HH and SHS in reducing the total cost of the HIES planning.</abstract><cop>Hoboken</cop><pub>Hindawi Limited</pub><doi>10.1155/2024/1156761</doi><orcidid>https://orcid.org/0009-0003-3425-5618</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Alternative energy sources Carbon dioxide Complex variables Compressed natural gas Constraints Contingency Electricity Electricity distribution Energy distribution Energy industry Energy storage Flexibility Fossil fuels Heat Hydrogen Hydrogen production Hydrogen storage Independent variables Integrated energy systems Mathematical programming Mixed integer Renewable energy Renewable resources Robustness Stochastic programming |
title | Robust Planning for Hydrogen‐Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage |
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