Distributed integrated energy management systems in residential buildings
•A home energy management system with multiple decision-making units (energy managers) is proposed.•Each energy manager represents a household device.•The decision making procedure is based on a discovery-and-negotiation-mechanism.•Load shifting schedules within user specified periods is the outcome...
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Veröffentlicht in: | Applied thermal engineering 2017-03, Vol.114, p.1468-1475 |
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creator | Honold, Johannes Kandler, Christian Wimmer, Patrick Schropp, Bernhard Reichle, Roland Gröne, Matthias Bünemann, Mathias Klein, Jens Kufner, Maximilian |
description | •A home energy management system with multiple decision-making units (energy managers) is proposed.•Each energy manager represents a household device.•The decision making procedure is based on a discovery-and-negotiation-mechanism.•Load shifting schedules within user specified periods is the outcome of the system.•The system is able to save operational energy costs of a household.
This paper explains the concept of a distributed integrated energy management (diEM) system for residential buildings. The overall goal of the system is to minimize operational energy costs of the household. This is obtained by load shifting in order to enhance the self-consumption rate of the on-site renewable electricity production. The crucial difference to centralized energy management systems (where data from household devices must be gathered and evaluated centrally) is the presence of multiple smart energy managers that negotiate with each other on the switch-on times of their dedicated electric devices. The major benefit is that devices of various manufacturers can be incorporated in the same home energy management system with open standards and open protocols without any additional decision-making unit. The basic procedure of the diEM is divided into a discovering phase and a negotiation phase. Best practice parameter settings are deduced from realistic scenarios with constant and variable electricity tariffs, and a run-time analysis indicates that up to seven devices can run simultaneously with a one minute renegotiation frequency. The monetary evaluation shows that the diEM can reduce the operational energy costs at a rate dependent on user behavior and tariff structures. |
doi_str_mv | 10.1016/j.applthermaleng.2016.10.158 |
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This paper explains the concept of a distributed integrated energy management (diEM) system for residential buildings. The overall goal of the system is to minimize operational energy costs of the household. This is obtained by load shifting in order to enhance the self-consumption rate of the on-site renewable electricity production. The crucial difference to centralized energy management systems (where data from household devices must be gathered and evaluated centrally) is the presence of multiple smart energy managers that negotiate with each other on the switch-on times of their dedicated electric devices. The major benefit is that devices of various manufacturers can be incorporated in the same home energy management system with open standards and open protocols without any additional decision-making unit. The basic procedure of the diEM is divided into a discovering phase and a negotiation phase. Best practice parameter settings are deduced from realistic scenarios with constant and variable electricity tariffs, and a run-time analysis indicates that up to seven devices can run simultaneously with a one minute renegotiation frequency. The monetary evaluation shows that the diEM can reduce the operational energy costs at a rate dependent on user behavior and tariff structures.</description><identifier>ISSN: 1359-4311</identifier><identifier>EISSN: 1873-5606</identifier><identifier>DOI: 10.1016/j.applthermaleng.2016.10.158</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Alternative energy ; Best practice ; Cost engineering ; Decentralized energy management ; Decision making ; Demand-side-management ; Distributed energy management ; Electric devices ; Electrical loads ; Electricity ; Electricity consumption ; Electricity generation ; Electricity pricing ; Electronic devices ; Energy conservation ; Energy costs ; Energy management ; Energy management systems ; Home energy management ; Housing ; Multi-agent system ; Residential buildings ; Residential energy ; Run time (computers) ; Studies</subject><ispartof>Applied thermal engineering, 2017-03, Vol.114, p.1468-1475</ispartof><rights>2016 Elsevier Ltd</rights><rights>Copyright Elsevier BV Mar 5, 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c358t-a92d9a801e8990f38c31c9d501e1dfd743e5705fb98d727f42f4c43dadf759ff3</citedby><cites>FETCH-LOGICAL-c358t-a92d9a801e8990f38c31c9d501e1dfd743e5705fb98d727f42f4c43dadf759ff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.applthermaleng.2016.10.158$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Honold, Johannes</creatorcontrib><creatorcontrib>Kandler, Christian</creatorcontrib><creatorcontrib>Wimmer, Patrick</creatorcontrib><creatorcontrib>Schropp, Bernhard</creatorcontrib><creatorcontrib>Reichle, Roland</creatorcontrib><creatorcontrib>Gröne, Matthias</creatorcontrib><creatorcontrib>Bünemann, Mathias</creatorcontrib><creatorcontrib>Klein, Jens</creatorcontrib><creatorcontrib>Kufner, Maximilian</creatorcontrib><title>Distributed integrated energy management systems in residential buildings</title><title>Applied thermal engineering</title><description>•A home energy management system with multiple decision-making units (energy managers) is proposed.•Each energy manager represents a household device.•The decision making procedure is based on a discovery-and-negotiation-mechanism.•Load shifting schedules within user specified periods is the outcome of the system.•The system is able to save operational energy costs of a household.
This paper explains the concept of a distributed integrated energy management (diEM) system for residential buildings. The overall goal of the system is to minimize operational energy costs of the household. This is obtained by load shifting in order to enhance the self-consumption rate of the on-site renewable electricity production. The crucial difference to centralized energy management systems (where data from household devices must be gathered and evaluated centrally) is the presence of multiple smart energy managers that negotiate with each other on the switch-on times of their dedicated electric devices. The major benefit is that devices of various manufacturers can be incorporated in the same home energy management system with open standards and open protocols without any additional decision-making unit. The basic procedure of the diEM is divided into a discovering phase and a negotiation phase. Best practice parameter settings are deduced from realistic scenarios with constant and variable electricity tariffs, and a run-time analysis indicates that up to seven devices can run simultaneously with a one minute renegotiation frequency. The monetary evaluation shows that the diEM can reduce the operational energy costs at a rate dependent on user behavior and tariff structures.</description><subject>Alternative energy</subject><subject>Best practice</subject><subject>Cost engineering</subject><subject>Decentralized energy management</subject><subject>Decision making</subject><subject>Demand-side-management</subject><subject>Distributed energy management</subject><subject>Electric devices</subject><subject>Electrical loads</subject><subject>Electricity</subject><subject>Electricity consumption</subject><subject>Electricity generation</subject><subject>Electricity pricing</subject><subject>Electronic devices</subject><subject>Energy conservation</subject><subject>Energy costs</subject><subject>Energy management</subject><subject>Energy management systems</subject><subject>Home energy management</subject><subject>Housing</subject><subject>Multi-agent system</subject><subject>Residential buildings</subject><subject>Residential energy</subject><subject>Run time (computers)</subject><subject>Studies</subject><issn>1359-4311</issn><issn>1873-5606</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqNUMtKxDAULaLg-PiHgm5bk6ZpE3Ajo6MDA250HTLJTU3pyyQV5u9NHTfuXN3DedzLPUlyi1GOEa7u2lxOUxc-wPWyg6HJi8jmi0rZSbLCrCYZrVB1GjGhPCsJxufJhfctQrhgdblKto_WB2f3cwCd2iFA4-QCYQDXHNJeDrKBHoaQ-oMP0PtoSh14qyNnZZfuZ9tpOzT-KjkzsvNw_Tsvk_fN09v6Jdu9Pm_XD7tMEcpCJnmhuWQIA-McGcIUwYprGgmsja5LArRG1Ow503VRm7IwpSqJltrUlBtDLpOb497JjZ8z-CDacXZDPCkwLyhmmKMquu6PLuVG7x0YMTnbS3cQGImlPNGKv-WJpbwflbIY3xzjED_5suCEVxYGBdo6UEHo0f5v0TdWFoKS</recordid><startdate>20170305</startdate><enddate>20170305</enddate><creator>Honold, Johannes</creator><creator>Kandler, Christian</creator><creator>Wimmer, Patrick</creator><creator>Schropp, Bernhard</creator><creator>Reichle, Roland</creator><creator>Gröne, Matthias</creator><creator>Bünemann, Mathias</creator><creator>Klein, Jens</creator><creator>Kufner, Maximilian</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>20170305</creationdate><title>Distributed integrated energy management systems in residential buildings</title><author>Honold, Johannes ; Kandler, Christian ; Wimmer, Patrick ; Schropp, Bernhard ; Reichle, Roland ; Gröne, Matthias ; Bünemann, Mathias ; Klein, Jens ; Kufner, Maximilian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c358t-a92d9a801e8990f38c31c9d501e1dfd743e5705fb98d727f42f4c43dadf759ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Alternative energy</topic><topic>Best practice</topic><topic>Cost engineering</topic><topic>Decentralized energy management</topic><topic>Decision making</topic><topic>Demand-side-management</topic><topic>Distributed energy management</topic><topic>Electric devices</topic><topic>Electrical loads</topic><topic>Electricity</topic><topic>Electricity consumption</topic><topic>Electricity generation</topic><topic>Electricity pricing</topic><topic>Electronic devices</topic><topic>Energy conservation</topic><topic>Energy costs</topic><topic>Energy management</topic><topic>Energy management systems</topic><topic>Home energy management</topic><topic>Housing</topic><topic>Multi-agent system</topic><topic>Residential buildings</topic><topic>Residential energy</topic><topic>Run time (computers)</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Honold, Johannes</creatorcontrib><creatorcontrib>Kandler, Christian</creatorcontrib><creatorcontrib>Wimmer, Patrick</creatorcontrib><creatorcontrib>Schropp, Bernhard</creatorcontrib><creatorcontrib>Reichle, Roland</creatorcontrib><creatorcontrib>Gröne, Matthias</creatorcontrib><creatorcontrib>Bünemann, Mathias</creatorcontrib><creatorcontrib>Klein, Jens</creatorcontrib><creatorcontrib>Kufner, Maximilian</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Applied thermal engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Honold, Johannes</au><au>Kandler, Christian</au><au>Wimmer, Patrick</au><au>Schropp, Bernhard</au><au>Reichle, Roland</au><au>Gröne, Matthias</au><au>Bünemann, Mathias</au><au>Klein, Jens</au><au>Kufner, Maximilian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distributed integrated energy management systems in residential buildings</atitle><jtitle>Applied thermal engineering</jtitle><date>2017-03-05</date><risdate>2017</risdate><volume>114</volume><spage>1468</spage><epage>1475</epage><pages>1468-1475</pages><issn>1359-4311</issn><eissn>1873-5606</eissn><abstract>•A home energy management system with multiple decision-making units (energy managers) is proposed.•Each energy manager represents a household device.•The decision making procedure is based on a discovery-and-negotiation-mechanism.•Load shifting schedules within user specified periods is the outcome of the system.•The system is able to save operational energy costs of a household.
This paper explains the concept of a distributed integrated energy management (diEM) system for residential buildings. The overall goal of the system is to minimize operational energy costs of the household. This is obtained by load shifting in order to enhance the self-consumption rate of the on-site renewable electricity production. The crucial difference to centralized energy management systems (where data from household devices must be gathered and evaluated centrally) is the presence of multiple smart energy managers that negotiate with each other on the switch-on times of their dedicated electric devices. The major benefit is that devices of various manufacturers can be incorporated in the same home energy management system with open standards and open protocols without any additional decision-making unit. The basic procedure of the diEM is divided into a discovering phase and a negotiation phase. Best practice parameter settings are deduced from realistic scenarios with constant and variable electricity tariffs, and a run-time analysis indicates that up to seven devices can run simultaneously with a one minute renegotiation frequency. The monetary evaluation shows that the diEM can reduce the operational energy costs at a rate dependent on user behavior and tariff structures.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.applthermaleng.2016.10.158</doi><tpages>8</tpages></addata></record> |
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subjects | Alternative energy Best practice Cost engineering Decentralized energy management Decision making Demand-side-management Distributed energy management Electric devices Electrical loads Electricity Electricity consumption Electricity generation Electricity pricing Electronic devices Energy conservation Energy costs Energy management Energy management systems Home energy management Housing Multi-agent system Residential buildings Residential energy Run time (computers) Studies |
title | Distributed integrated energy management systems in residential buildings |
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