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dc.contributor.authorBremdal, Bernt Arild
dc.contributor.authorTangrand, Kristoffer
dc.date.accessioned2019-11-26T09:42:34Z
dc.date.available2019-11-26T09:42:34Z
dc.date.issued2019
dc.description.abstractThis paper documents research conducted in the Norwegian FLEXNETT project.<br>It describes a new tool that was developed to study the future impact of prosumers with PV panels on the grid in Norway and the potential energy flexibility that lies with residential prosumers. Systematic use of energy flexibility can be an important instrument for managing peak loads and voltage problems in weak power grids. The influx of distributed energy resources can amplify this problem, but also help to resolve it. Self-balancing neighborhoods can be very attractive.<br> This implies that loads related to energy demands can be curtailed and leveled out by different controllable devices or managed by using local energy production in the area to reduce the impact on the general distribution grid. The simulation tool is GIS based and can be applied to study the situation related to a single household, a neighborhood or in a specific transformer area. Unlike similar tools that address production yields over a period, the FLEXNETT Simulator addresses production and energy dynamics down to every 10 minutes. Due to the relatively low solar angle in Norway and rapidly changing weather these dynamics can be very prominent and induce local impact that is specific to a house or a neighborhood. <br>The paper further describes how a recurrent neural network has been used as an engine to produce realistic values for the simulator.en_US
dc.descriptionPublished version, available at <a href=http://dx.doi.org/10.1088/1755-1315/352/1/012005>http://dx.doi.org/10.1088/1755-1315/352/1/012005</a>, by the license <a href=http://creativecommons.org/licenses/by/3.0>Creative Commons Attribution 3.0 </a>en_US
dc.identifier.citationBremdal, B.A., Tangran, K.(2019) The FlexNett Simulator.<i> IOP Conference Series: Earth and Environmental Science (EES), 352</i>, 1-8. http://dx.doi.org/10.1088/1755-1315/352/1/012005en_US
dc.identifier.cristinIDFRIDAID 1747944
dc.identifier.doi10.1088/1755-1315/352/1/012005
dc.identifier.issn1755-1307
dc.identifier.issn1755-1315
dc.identifier.urihttps://hdl.handle.net/10037/16729
dc.language.isoengen_US
dc.publisherIOP Publishingen_US
dc.relation.ispartofTangrand, K.M. (2023). Some new Contributions to Neural Networks and Wavelets with Applications. (Doctoral thesis). <a href=https://hdl.handle.net/10037/28699>https://hdl.handle.net/10037/28699</a>.
dc.relation.journalIOP Conference Series: Earth and Environmental Science (EES)
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/ENERGIX/en_US
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Technology: 500::Environmental engineering: 610en_US
dc.subjectVDP::Teknologi: 500::Miljøteknologi: 610en_US
dc.titleThe FlexNett Simulatoren_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US


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