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Nature-inspired solutions for energy sustainability using novel optimization methods
This research centres on developing a Home Electricity Management (HEM) system, a pivotal component within the modern supply chain for home electrical power. The system optimizes the scheduling of intelligent home gadgets through advanced meta-heuristics, specifically the Social Spider Algorithm (SS...
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Published in: | PloS one 2023-11, Vol.18 (11), p.e0288490-e0288490 |
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description | This research centres on developing a Home Electricity Management (HEM) system, a pivotal component within the modern supply chain for home electrical power. The system optimizes the scheduling of intelligent home gadgets through advanced meta-heuristics, specifically the Social Spider Algorithm (SSA) and Strawberry Algorithm (SWA), to efficiently manage home energy consumption. Within the supply chain context, HEM acts as a crucial link in the distribution and utilization of electricity within households, akin to optimizing resource allocation and demand balancing within a supply chain for efficient operation and cost-effectiveness. Simulations and comparisons demonstrate that SWA excels in cost savings, while SSA is more effective in reducing peak-to-average power ratios. The proposed solution reduces costs for residences by up to 3.5 percent, highlighting the potential for significant cost savings and efficiency improvements within the home electricity supply chain. It also surpasses existing cost and Peak Average (PAR) ratio meta-heuristics, indicating superior performance within the overall energy supply and consumption framework. Moreover, implementing the HEM system contributes to reducing carbon emissions, aligning with sustainability goals in the energy supply chain. It promotes energy efficiency, integrates renewable sources, and facilitates demand response, mirroring the emphasis on sustainability in supply chain practices. Overall, this research offers a practical and sustainable approach to home energy management, bringing substantial cost savings and environmental benefits to the modern supply chain for residential electricity. |
doi_str_mv | 10.1371/journal.pone.0288490 |
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The system optimizes the scheduling of intelligent home gadgets through advanced meta-heuristics, specifically the Social Spider Algorithm (SSA) and Strawberry Algorithm (SWA), to efficiently manage home energy consumption. Within the supply chain context, HEM acts as a crucial link in the distribution and utilization of electricity within households, akin to optimizing resource allocation and demand balancing within a supply chain for efficient operation and cost-effectiveness. Simulations and comparisons demonstrate that SWA excels in cost savings, while SSA is more effective in reducing peak-to-average power ratios. The proposed solution reduces costs for residences by up to 3.5 percent, highlighting the potential for significant cost savings and efficiency improvements within the home electricity supply chain. It also surpasses existing cost and Peak Average (PAR) ratio meta-heuristics, indicating superior performance within the overall energy supply and consumption framework. Moreover, implementing the HEM system contributes to reducing carbon emissions, aligning with sustainability goals in the energy supply chain. It promotes energy efficiency, integrates renewable sources, and facilitates demand response, mirroring the emphasis on sustainability in supply chain practices. Overall, this research offers a practical and sustainable approach to home energy management, bringing substantial cost savings and environmental benefits to the modern supply chain for residential electricity.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0288490</identifier><language>eng</language><publisher>Public Library of Science</publisher><subject>Air quality management ; Algorithms ; Alternative energy sources ; Architecture and energy conservation ; Emissions (Pollution) ; Energy efficiency ; Environmental aspects ; Evaluation ; Home appliances ; Methods ; Sustainable development</subject><ispartof>PloS one, 2023-11, Vol.18 (11), p.e0288490-e0288490</ispartof><rights>COPYRIGHT 2023 Public Library of Science</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c511t-620a046263fcf8b0874c59811dbaa0670e14fb83fddb31609ecfaa6254d63db93</cites><orcidid>0000-0001-7181-2100</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902,36990</link.rule.ids></links><search><contributor>Abba, Sani Isah</contributor><creatorcontrib>Almazroi, Abdulwahab Ali</creatorcontrib><creatorcontrib>Ul Hassan, Ch Anwar</creatorcontrib><title>Nature-inspired solutions for energy sustainability using novel optimization methods</title><title>PloS one</title><description>This research centres on developing a Home Electricity Management (HEM) system, a pivotal component within the modern supply chain for home electrical power. 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Moreover, implementing the HEM system contributes to reducing carbon emissions, aligning with sustainability goals in the energy supply chain. It promotes energy efficiency, integrates renewable sources, and facilitates demand response, mirroring the emphasis on sustainability in supply chain practices. Overall, this research offers a practical and sustainable approach to home energy management, bringing substantial cost savings and environmental benefits to the modern supply chain for residential electricity.</description><subject>Air quality management</subject><subject>Algorithms</subject><subject>Alternative energy sources</subject><subject>Architecture and energy conservation</subject><subject>Emissions (Pollution)</subject><subject>Energy efficiency</subject><subject>Environmental aspects</subject><subject>Evaluation</subject><subject>Home appliances</subject><subject>Methods</subject><subject>Sustainable development</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNqNkl-L1DAUxYMouI5-Ax8KgujDjEmTtsnjsug6sLigq6_hNn86GdqkJqk4fvptnWHZAR8kkFwuv3O45B6EXhO8IbQhH_Zhih76zRi82eCScybwE3RBBC3XdYnp00f1c_QipT3GFeV1fYHuvkCeolk7n0YXjS5S6Kfsgk-FDbEw3sTuUKQpZXAeWte7fCim5HxX-PDL9EUYsxvcH1g0xWDyLuj0Ej2z0Cfz6vSu0PdPH--uPq9vbq-3V5c3a1URkpdxALO6rKlVlreYN0xVghOiWwBcN9gQZltOrdYtJTUWRlmAuqyYrqluBV2h7dFXB9jLMboB4kEGcPJvI8ROQsxO9UZyjJnQuC2ZpUxjCg1psKaVtXOt2mr2enf0GmP4OZmU5eCSMn0P3oQpyZIL1pSE8QV9c0Q7mJ2dtyFHUAsuL5uGUS7EfK_Q5h_UfLQZnJo3Zd3cPxO8PxPMTDa_cwdTSnL77ev_s7c_ztm3j9idgT7vHrZ8DrIjqGJIKRr78KUEyyVo8hQ0uQRNnoJG7wEK28fg</recordid><startdate>20231127</startdate><enddate>20231127</enddate><creator>Almazroi, Abdulwahab Ali</creator><creator>Ul Hassan, Ch Anwar</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>7X8</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7181-2100</orcidid></search><sort><creationdate>20231127</creationdate><title>Nature-inspired solutions for energy sustainability using novel optimization methods</title><author>Almazroi, Abdulwahab Ali ; Ul Hassan, Ch Anwar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c511t-620a046263fcf8b0874c59811dbaa0670e14fb83fddb31609ecfaa6254d63db93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Air quality management</topic><topic>Algorithms</topic><topic>Alternative energy sources</topic><topic>Architecture and energy conservation</topic><topic>Emissions (Pollution)</topic><topic>Energy efficiency</topic><topic>Environmental aspects</topic><topic>Evaluation</topic><topic>Home appliances</topic><topic>Methods</topic><topic>Sustainable development</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Almazroi, Abdulwahab Ali</creatorcontrib><creatorcontrib>Ul Hassan, Ch Anwar</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>MEDLINE - Academic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Almazroi, Abdulwahab Ali</au><au>Ul Hassan, Ch Anwar</au><au>Abba, Sani Isah</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nature-inspired solutions for energy sustainability using novel optimization methods</atitle><jtitle>PloS one</jtitle><date>2023-11-27</date><risdate>2023</risdate><volume>18</volume><issue>11</issue><spage>e0288490</spage><epage>e0288490</epage><pages>e0288490-e0288490</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>This research centres on developing a Home Electricity Management (HEM) system, a pivotal component within the modern supply chain for home electrical power. The system optimizes the scheduling of intelligent home gadgets through advanced meta-heuristics, specifically the Social Spider Algorithm (SSA) and Strawberry Algorithm (SWA), to efficiently manage home energy consumption. Within the supply chain context, HEM acts as a crucial link in the distribution and utilization of electricity within households, akin to optimizing resource allocation and demand balancing within a supply chain for efficient operation and cost-effectiveness. Simulations and comparisons demonstrate that SWA excels in cost savings, while SSA is more effective in reducing peak-to-average power ratios. The proposed solution reduces costs for residences by up to 3.5 percent, highlighting the potential for significant cost savings and efficiency improvements within the home electricity supply chain. It also surpasses existing cost and Peak Average (PAR) ratio meta-heuristics, indicating superior performance within the overall energy supply and consumption framework. Moreover, implementing the HEM system contributes to reducing carbon emissions, aligning with sustainability goals in the energy supply chain. It promotes energy efficiency, integrates renewable sources, and facilitates demand response, mirroring the emphasis on sustainability in supply chain practices. Overall, this research offers a practical and sustainable approach to home energy management, bringing substantial cost savings and environmental benefits to the modern supply chain for residential electricity.</abstract><pub>Public Library of Science</pub><doi>10.1371/journal.pone.0288490</doi><tpages>e0288490</tpages><orcidid>https://orcid.org/0000-0001-7181-2100</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Air quality management Algorithms Alternative energy sources Architecture and energy conservation Emissions (Pollution) Energy efficiency Environmental aspects Evaluation Home appliances Methods Sustainable development |
title | Nature-inspired solutions for energy sustainability using novel optimization methods |
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