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Time Series Optimization-Based Characteristic Curve Calculation for Local Reactive Power Control Using Pandapower-PowerModels Interface

dc.date.accessioned2023-06-30T07:23:26Z
dc.date.available2023-06-30T07:23:26Z
dc.date.issued2023-05-29
dc.identifierdoi:10.17170/kobra-202306278298
dc.identifier.urihttp://hdl.handle.net/123456789/14861
dc.description.sponsorshipGefördert durch den Publikationsfonds der Universität Kassel
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectcharacteristic curveeng
dc.subjectoptimal power floweng
dc.subjectdistribution gridseng
dc.subjectvoltage stabilityeng
dc.subjectreactive power flexibilityeng
dc.subject.ddc333eng
dc.subject.ddc600
dc.titleTime Series Optimization-Based Characteristic Curve Calculation for Local Reactive Power Control Using Pandapower-PowerModels Interfaceeng
dc.typeAufsatz
dcterms.abstractLocal reactive power control in distribution grids with a high penetration of distributed energy resources (DERs) will be essential in future power system operation. Appropriate control characteristic curves for DERs support stable and efficient distribution grid operation. However, the current practice is to configure local controllers collectively with constant characteristic curves that may not be efficient for volatile grid conditions or the desired targets of grid operators. To address this issue, this paper proposes a time series optimization-based method to calculate control parameters, which enables each DER to be independently controlled by an exclusive characteristic curve for optimizing its reactive power provision. To realize time series reactive power optimizations, the open-source tools pandapower and PowerModels are interconnected functionally. Based on the optimization results, Q(V)- and Q(P)-characteristic curves can be individually calculated using linear decision tree regression to support voltage stability, provide reactive power flexibility and potentially reduce grid losses and component loadings. In this paper, the newly calculated characteristic curves are applied in two representative case studies, and the results demonstrate that the proposed method outperforms the reference methods suggested by grid codes.eng
dcterms.accessRightsopen access
dcterms.creatorLiu, Zheng
dcterms.creatorMajidi, Maryam
dcterms.creatorWang, Hanoan
dcterms.creatorMende, Denis
dcterms.creatorBraun, Martin
dc.relation.doidoi:10.3390/en16114385
dc.subject.swdBlindleistungger
dc.subject.swdBlindleistungsregelungger
dc.subject.swdSpannungsstabilisierungger
dc.subject.swdVerteilungsnetzger
dc.subject.swdFlexibilitätger
dc.type.versionpublishedVersion
dcterms.source.identifiereissn:1996-1073
dcterms.source.issueIssue 11
dcterms.source.journalEnergieseng
dcterms.source.volumeVolume 16
kup.iskupfalse
dcterms.source.articlenumber4385


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