Loading…

Capacity optimization allocation method of photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system based on SAO algorithm

The capacity optimization allocation of hybrid micro-energy systems is an important link in micro-energy systems, which can effectively improve the reliability and economy of the power grid. In this paper, the capacity optimization allocation method of a photovoltaic-temperature difference-hydrogen-...

Full description

Saved in:
Bibliographic Details
Published in:Journal of physics. Conference series 2024-03, Vol.2728 (1), p.12014
Main Authors: Pi, Linlin, Tian, Liguo
Format: Article
Language:English
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue 1
container_start_page 12014
container_title Journal of physics. Conference series
container_volume 2728
creator Pi, Linlin
Tian, Liguo
description The capacity optimization allocation of hybrid micro-energy systems is an important link in micro-energy systems, which can effectively improve the reliability and economy of the power grid. In this paper, the capacity optimization allocation method of a photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system is studied. First, a capacity optimization configuration model based on photovoltaic, temperature difference, and hydrogen storage hybrid micro-energy system was established to maximize revenue. Then, the SAO algorithm is used to optimize its strategy. When the strategy does not change, it indicates that the income has been maximized. Finally, concerning the snow ablation mechanism, it can balance development and exploration well and can optimize the global optimal solution even in a more complex environment. The proposed method can ensure the reliability under premise of relatively low cost, and effectively improve the rationality of the power grid capacity allocation method in the photovoltaic thermal power generation scenario.
doi_str_mv 10.1088/1742-6596/2728/1/012014
format article
fullrecord <record><control><sourceid>proquest_iop_j</sourceid><recordid>TN_cdi_proquest_journals_2968934372</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2968934372</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2394-6d888f2d7bc3fc13701f5d9b20ff1611ceaf5e2a734bf9d0374f8d20bade856f3</originalsourceid><addsrcrecordid>eNqFkE1LxDAQhosoqKu_wYDnuvnoNulRFr9A8KCeQ5pMtpFtU5OsUP-F_9gsFT06l5lh5n1neIriguArgoVYEl7Rsl419ZJymtslJhST6qA4-Z0c_tZCHBenMb5hzHLwk-JrrUalXZqQH5Pr3adKzg9Ibbdez2UPqfMGeYvGzif_4bdJOV0m6EcIKu0CIOOshQCDhrKbTPAbGMqYfFAbQN3UBmdQ73TwJQwQNhOKU8xy1KoI2XhAz9dP-eLGB5e6_qw4smob4fwnL4rX25uX9X35-HT3sL5-LDVlTVXWRghhqeGtZlYTxjGxK9O0FFtLakI0KLsCqjirWtsYzHhlhaG4VQbEqrZsUVzOvmPw7zuISb75XRjySUmbWjSsYpzmLT5v5fdjDGDlGFyvwiQJlnv-ck9W7inLPX9J5Mw_K9msdH78s_5P9Q1SbYwi</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2968934372</pqid></control><display><type>article</type><title>Capacity optimization allocation method of photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system based on SAO algorithm</title><source>Publicly Available Content Database</source><source>Free Full-Text Journals in Chemistry</source><creator>Pi, Linlin ; Tian, Liguo</creator><creatorcontrib>Pi, Linlin ; Tian, Liguo</creatorcontrib><description>The capacity optimization allocation of hybrid micro-energy systems is an important link in micro-energy systems, which can effectively improve the reliability and economy of the power grid. In this paper, the capacity optimization allocation method of a photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system is studied. First, a capacity optimization configuration model based on photovoltaic, temperature difference, and hydrogen storage hybrid micro-energy system was established to maximize revenue. Then, the SAO algorithm is used to optimize its strategy. When the strategy does not change, it indicates that the income has been maximized. Finally, concerning the snow ablation mechanism, it can balance development and exploration well and can optimize the global optimal solution even in a more complex environment. The proposed method can ensure the reliability under premise of relatively low cost, and effectively improve the rationality of the power grid capacity allocation method in the photovoltaic thermal power generation scenario.</description><identifier>ISSN: 1742-6588</identifier><identifier>EISSN: 1742-6596</identifier><identifier>DOI: 10.1088/1742-6596/2728/1/012014</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Ablation ; Algorithms ; Energy storage ; Hybrid systems ; Hydrogen storage ; Optimization ; Reliability ; System effectiveness ; Temperature gradients</subject><ispartof>Journal of physics. Conference series, 2024-03, Vol.2728 (1), p.12014</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2968934372?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25752,27923,27924,37011,44589</link.rule.ids></links><search><creatorcontrib>Pi, Linlin</creatorcontrib><creatorcontrib>Tian, Liguo</creatorcontrib><title>Capacity optimization allocation method of photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system based on SAO algorithm</title><title>Journal of physics. Conference series</title><addtitle>J. Phys.: Conf. Ser</addtitle><description>The capacity optimization allocation of hybrid micro-energy systems is an important link in micro-energy systems, which can effectively improve the reliability and economy of the power grid. In this paper, the capacity optimization allocation method of a photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system is studied. First, a capacity optimization configuration model based on photovoltaic, temperature difference, and hydrogen storage hybrid micro-energy system was established to maximize revenue. Then, the SAO algorithm is used to optimize its strategy. When the strategy does not change, it indicates that the income has been maximized. Finally, concerning the snow ablation mechanism, it can balance development and exploration well and can optimize the global optimal solution even in a more complex environment. The proposed method can ensure the reliability under premise of relatively low cost, and effectively improve the rationality of the power grid capacity allocation method in the photovoltaic thermal power generation scenario.</description><subject>Ablation</subject><subject>Algorithms</subject><subject>Energy storage</subject><subject>Hybrid systems</subject><subject>Hydrogen storage</subject><subject>Optimization</subject><subject>Reliability</subject><subject>System effectiveness</subject><subject>Temperature gradients</subject><issn>1742-6588</issn><issn>1742-6596</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqFkE1LxDAQhosoqKu_wYDnuvnoNulRFr9A8KCeQ5pMtpFtU5OsUP-F_9gsFT06l5lh5n1neIriguArgoVYEl7Rsl419ZJymtslJhST6qA4-Z0c_tZCHBenMb5hzHLwk-JrrUalXZqQH5Pr3adKzg9Ibbdez2UPqfMGeYvGzif_4bdJOV0m6EcIKu0CIOOshQCDhrKbTPAbGMqYfFAbQN3UBmdQ73TwJQwQNhOKU8xy1KoI2XhAz9dP-eLGB5e6_qw4smob4fwnL4rX25uX9X35-HT3sL5-LDVlTVXWRghhqeGtZlYTxjGxK9O0FFtLakI0KLsCqjirWtsYzHhlhaG4VQbEqrZsUVzOvmPw7zuISb75XRjySUmbWjSsYpzmLT5v5fdjDGDlGFyvwiQJlnv-ck9W7inLPX9J5Mw_K9msdH78s_5P9Q1SbYwi</recordid><startdate>20240301</startdate><enddate>20240301</enddate><creator>Pi, Linlin</creator><creator>Tian, Liguo</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20240301</creationdate><title>Capacity optimization allocation method of photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system based on SAO algorithm</title><author>Pi, Linlin ; Tian, Liguo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2394-6d888f2d7bc3fc13701f5d9b20ff1611ceaf5e2a734bf9d0374f8d20bade856f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Ablation</topic><topic>Algorithms</topic><topic>Energy storage</topic><topic>Hybrid systems</topic><topic>Hydrogen storage</topic><topic>Optimization</topic><topic>Reliability</topic><topic>System effectiveness</topic><topic>Temperature gradients</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pi, Linlin</creatorcontrib><creatorcontrib>Tian, Liguo</creatorcontrib><collection>Institute of Physics Open Access Journal Titles</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Journal of physics. Conference series</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pi, Linlin</au><au>Tian, Liguo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Capacity optimization allocation method of photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system based on SAO algorithm</atitle><jtitle>Journal of physics. Conference series</jtitle><addtitle>J. Phys.: Conf. Ser</addtitle><date>2024-03-01</date><risdate>2024</risdate><volume>2728</volume><issue>1</issue><spage>12014</spage><pages>12014-</pages><issn>1742-6588</issn><eissn>1742-6596</eissn><abstract>The capacity optimization allocation of hybrid micro-energy systems is an important link in micro-energy systems, which can effectively improve the reliability and economy of the power grid. In this paper, the capacity optimization allocation method of a photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system is studied. First, a capacity optimization configuration model based on photovoltaic, temperature difference, and hydrogen storage hybrid micro-energy system was established to maximize revenue. Then, the SAO algorithm is used to optimize its strategy. When the strategy does not change, it indicates that the income has been maximized. Finally, concerning the snow ablation mechanism, it can balance development and exploration well and can optimize the global optimal solution even in a more complex environment. The proposed method can ensure the reliability under premise of relatively low cost, and effectively improve the rationality of the power grid capacity allocation method in the photovoltaic thermal power generation scenario.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1742-6596/2728/1/012014</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1742-6588
ispartof Journal of physics. Conference series, 2024-03, Vol.2728 (1), p.12014
issn 1742-6588
1742-6596
language eng
recordid cdi_proquest_journals_2968934372
source Publicly Available Content Database; Free Full-Text Journals in Chemistry
subjects Ablation
Algorithms
Energy storage
Hybrid systems
Hydrogen storage
Optimization
Reliability
System effectiveness
Temperature gradients
title Capacity optimization allocation method of photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system based on SAO algorithm
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T17%3A06%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_iop_j&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Capacity%20optimization%20allocation%20method%20of%20photovoltaic-temperature%20difference-hydrogen-storage%20hybrid%20micro-energy%20system%20based%20on%20SAO%20algorithm&rft.jtitle=Journal%20of%20physics.%20Conference%20series&rft.au=Pi,%20Linlin&rft.date=2024-03-01&rft.volume=2728&rft.issue=1&rft.spage=12014&rft.pages=12014-&rft.issn=1742-6588&rft.eissn=1742-6596&rft_id=info:doi/10.1088/1742-6596/2728/1/012014&rft_dat=%3Cproquest_iop_j%3E2968934372%3C/proquest_iop_j%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c2394-6d888f2d7bc3fc13701f5d9b20ff1611ceaf5e2a734bf9d0374f8d20bade856f3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2968934372&rft_id=info:pmid/&rfr_iscdi=true