Installed capacity optimization of distributed energy resource systems for residential buildings
•A methodology is presented for integration and optimization.•An integrated model is developed on the basis of the operation strategies.•A genetic algorithm is applied for optimizing the installed capacities.•The methodology that we propose is shown by computer simulations. Our work aims to reduce r...
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Veröffentlicht in: | Energy and buildings 2014-02, Vol.69, p.307-317 |
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creator | Gao, Xiangxiang Akashi, Yasunori Sumiyoshi, Daisuke |
description | •A methodology is presented for integration and optimization.•An integrated model is developed on the basis of the operation strategies.•A genetic algorithm is applied for optimizing the installed capacities.•The methodology that we propose is shown by computer simulations.
Our work aims to reduce residential energy consumption and expense by presenting a methodology for integrating electricity and hot water supply, and determining the optimum installed capacities of the selected distributed energy resource systems, which consist of a photovoltaic system, a solar water heating system and a fuel cell system. Initially, we build the dynamic model respectively for every individual system on the basis of their respective working principles. Then we propose operation strategies of electric power and hot water separately for the integration of the models. Followed, we apply a genetic algorithm to optimize the installed capacities of the systems, aiming at reducing the conventional energy consumption and the life cycle costs. With a complete database, the integration and optimization methodology are finally applied to a typical building located in Fukuoka City in Japan. It is shown by the computer simulation that the methodology which we propose can help to reduce considerable quantity of residential energy consumption and expense. |
doi_str_mv | 10.1016/j.enbuild.2013.11.026 |
format | Article |
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Our work aims to reduce residential energy consumption and expense by presenting a methodology for integrating electricity and hot water supply, and determining the optimum installed capacities of the selected distributed energy resource systems, which consist of a photovoltaic system, a solar water heating system and a fuel cell system. Initially, we build the dynamic model respectively for every individual system on the basis of their respective working principles. Then we propose operation strategies of electric power and hot water separately for the integration of the models. Followed, we apply a genetic algorithm to optimize the installed capacities of the systems, aiming at reducing the conventional energy consumption and the life cycle costs. With a complete database, the integration and optimization methodology are finally applied to a typical building located in Fukuoka City in Japan. It is shown by the computer simulation that the methodology which we propose can help to reduce considerable quantity of residential energy consumption and expense.</description><identifier>ISSN: 0378-7788</identifier><identifier>DOI: 10.1016/j.enbuild.2013.11.026</identifier><identifier>CODEN: ENEBDR</identifier><language>eng</language><publisher>Oxford: Elsevier B.V</publisher><subject>Applied sciences ; Building technical equipments ; Buildings ; Buildings. Public works ; Computation methods. Tables. Charts ; Construction ; Distributed energy resource ; Distributed generation ; Dynamical systems ; Dynamics ; Energy management and energy conservation in building ; Environmental engineering ; Exact sciences and technology ; Expenses ; Fuel cell ; Methodology ; Optimization ; Photovoltaic ; Residential building ; Residential energy ; Solar water heating ; Structural analysis. Stresses ; Types of buildings</subject><ispartof>Energy and buildings, 2014-02, Vol.69, p.307-317</ispartof><rights>2013 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c372t-f0c994122095c79fcf6a81451eba38207f8e1022fad5ecc14f66ec91e7be9d403</citedby><cites>FETCH-LOGICAL-c372t-f0c994122095c79fcf6a81451eba38207f8e1022fad5ecc14f66ec91e7be9d403</cites><orcidid>0000-0001-9173-9414</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.enbuild.2013.11.026$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27907,27908,45978</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28313443$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Gao, Xiangxiang</creatorcontrib><creatorcontrib>Akashi, Yasunori</creatorcontrib><creatorcontrib>Sumiyoshi, Daisuke</creatorcontrib><title>Installed capacity optimization of distributed energy resource systems for residential buildings</title><title>Energy and buildings</title><description>•A methodology is presented for integration and optimization.•An integrated model is developed on the basis of the operation strategies.•A genetic algorithm is applied for optimizing the installed capacities.•The methodology that we propose is shown by computer simulations.
Our work aims to reduce residential energy consumption and expense by presenting a methodology for integrating electricity and hot water supply, and determining the optimum installed capacities of the selected distributed energy resource systems, which consist of a photovoltaic system, a solar water heating system and a fuel cell system. Initially, we build the dynamic model respectively for every individual system on the basis of their respective working principles. Then we propose operation strategies of electric power and hot water separately for the integration of the models. Followed, we apply a genetic algorithm to optimize the installed capacities of the systems, aiming at reducing the conventional energy consumption and the life cycle costs. With a complete database, the integration and optimization methodology are finally applied to a typical building located in Fukuoka City in Japan. It is shown by the computer simulation that the methodology which we propose can help to reduce considerable quantity of residential energy consumption and expense.</description><subject>Applied sciences</subject><subject>Building technical equipments</subject><subject>Buildings</subject><subject>Buildings. Public works</subject><subject>Computation methods. Tables. Charts</subject><subject>Construction</subject><subject>Distributed energy resource</subject><subject>Distributed generation</subject><subject>Dynamical systems</subject><subject>Dynamics</subject><subject>Energy management and energy conservation in building</subject><subject>Environmental engineering</subject><subject>Exact sciences and technology</subject><subject>Expenses</subject><subject>Fuel cell</subject><subject>Methodology</subject><subject>Optimization</subject><subject>Photovoltaic</subject><subject>Residential building</subject><subject>Residential energy</subject><subject>Solar water heating</subject><subject>Structural analysis. Stresses</subject><subject>Types of buildings</subject><issn>0378-7788</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqFkE1rGzEQhvfQQNIkP6Gwl0Iv3mik_TyVEpoPCOSSnFV5dhTGrCVXoy04vz7r2vTa08DwvPPxFMUXUBUoaG82FYX1zNNYaQWmAqiUbj8VF8p0_arr-v68-CyyUUq1TQcXxa_HINlNE40lup1Dzvsy7jJv-d1ljqGMvhxZcuL1nBeIAqW3fZlI4pyQStlLpq2UPqZDk0cKmd1U_r2Bw5tcFWfeTULXp3pZvN79fLl9WD093z_e_nhaoel0XnmFw1CD1mposBs8-tb1UDdAa2d6rTrfEyitvRsbQoTaty3hANStaRhrZS6Lb8e5uxR_zyTZblmQpskFirNYaIwa-ta0ekGbI4opiiTydpd469LegrIHi3ZjTxbtwaIFsIvFJff1tMIJusknF5DlX1j3Bkxdm4X7fuRo-fcPU7KCTAFp5ESY7Rj5P5s-ANqOj3w</recordid><startdate>20140201</startdate><enddate>20140201</enddate><creator>Gao, Xiangxiang</creator><creator>Akashi, Yasunori</creator><creator>Sumiyoshi, Daisuke</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0001-9173-9414</orcidid></search><sort><creationdate>20140201</creationdate><title>Installed capacity optimization of distributed energy resource systems for residential buildings</title><author>Gao, Xiangxiang ; Akashi, Yasunori ; Sumiyoshi, Daisuke</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c372t-f0c994122095c79fcf6a81451eba38207f8e1022fad5ecc14f66ec91e7be9d403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Applied sciences</topic><topic>Building technical equipments</topic><topic>Buildings</topic><topic>Buildings. Public works</topic><topic>Computation methods. Tables. Charts</topic><topic>Construction</topic><topic>Distributed energy resource</topic><topic>Distributed generation</topic><topic>Dynamical systems</topic><topic>Dynamics</topic><topic>Energy management and energy conservation in building</topic><topic>Environmental engineering</topic><topic>Exact sciences and technology</topic><topic>Expenses</topic><topic>Fuel cell</topic><topic>Methodology</topic><topic>Optimization</topic><topic>Photovoltaic</topic><topic>Residential building</topic><topic>Residential energy</topic><topic>Solar water heating</topic><topic>Structural analysis. Stresses</topic><topic>Types of buildings</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gao, Xiangxiang</creatorcontrib><creatorcontrib>Akashi, Yasunori</creatorcontrib><creatorcontrib>Sumiyoshi, Daisuke</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Energy and buildings</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gao, Xiangxiang</au><au>Akashi, Yasunori</au><au>Sumiyoshi, Daisuke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Installed capacity optimization of distributed energy resource systems for residential buildings</atitle><jtitle>Energy and buildings</jtitle><date>2014-02-01</date><risdate>2014</risdate><volume>69</volume><spage>307</spage><epage>317</epage><pages>307-317</pages><issn>0378-7788</issn><coden>ENEBDR</coden><abstract>•A methodology is presented for integration and optimization.•An integrated model is developed on the basis of the operation strategies.•A genetic algorithm is applied for optimizing the installed capacities.•The methodology that we propose is shown by computer simulations.
Our work aims to reduce residential energy consumption and expense by presenting a methodology for integrating electricity and hot water supply, and determining the optimum installed capacities of the selected distributed energy resource systems, which consist of a photovoltaic system, a solar water heating system and a fuel cell system. Initially, we build the dynamic model respectively for every individual system on the basis of their respective working principles. Then we propose operation strategies of electric power and hot water separately for the integration of the models. Followed, we apply a genetic algorithm to optimize the installed capacities of the systems, aiming at reducing the conventional energy consumption and the life cycle costs. With a complete database, the integration and optimization methodology are finally applied to a typical building located in Fukuoka City in Japan. It is shown by the computer simulation that the methodology which we propose can help to reduce considerable quantity of residential energy consumption and expense.</abstract><cop>Oxford</cop><pub>Elsevier B.V</pub><doi>10.1016/j.enbuild.2013.11.026</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-9173-9414</orcidid></addata></record> |
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subjects | Applied sciences Building technical equipments Buildings Buildings. Public works Computation methods. Tables. Charts Construction Distributed energy resource Distributed generation Dynamical systems Dynamics Energy management and energy conservation in building Environmental engineering Exact sciences and technology Expenses Fuel cell Methodology Optimization Photovoltaic Residential building Residential energy Solar water heating Structural analysis. Stresses Types of buildings |
title | Installed capacity optimization of distributed energy resource systems for residential buildings |
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