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AuthorBernal Alzate, Efraindc.contributor.author
Date of accession2017-12-12T08:59:28Zdc.date.accessioned
Available in OPARU since2017-12-12T08:59:28Zdc.date.available
Year of creation2017-09-21dc.date.created
Date of first publication2017-12-12dc.date.issued
AbstractDue to the high penetration of renewable distributed energy resources (DERs) into low-voltage distribution grids, particularly residential photovoltaic (PV) systems, a renewed interest in voltagecontrol strategies arises in the recent years. Although voltage-control strategies based on reactive power produced by smart PV inverters are a well developed technique, the use of central control strategies for LV distributed grids remains a challenging procedure because of the characteristics of these grids and the limitations of telecommunication networks, including the low measurement redundancy of low-voltage (LV) distribution system compared to power transmission systems. However, with the inclusion of Information and Communication Technology (ICT) components into the LV distribution grid, measurement data from smart meters are available for the control of these networks. This dissertation undertakes a central voltage-control strategy for smart LV distribution networks, using a novel optimal power flow (OPF) methodology in conjunction with the information collected from smart meters for the power flow calculation. The proposed strategy can simultaneously mitigate the PV reactive power fluctuations, as well as minimize the voltage rise and power losses. Moreover, a novel distribution power system state estimation method (DSE) based on the information provided by smart meters is developed to support central voltage-control strategies in real-time in case of telecommunication failure. In order to analyze the developed techniques, a more realistic scenario of smart LV distribution networks is designed, including high-resolved home power demand models and a novel approach for the power flow formulation of LV distribution systems. Comparison studies to validate the developed methodologies are presented for IEEE 30-bus, 57-bus system and a 30 smart home LV distribution system, showing the robustness of proposed methods compared with traditional approaches. The results are promising as voltage control is achieved fast and accurately, the reactive power is smoothed in reference to the typical optimization techniques and local control strategies. Furthermore, using the information provided by the smart meters in combination with the developed power flow formulation, the proposed central control system is able to mitigate the effects of temporal communication link failure from smart meters to utility company. To illustrate the applicability of the proposed method, a real-time digital simulator for smart distribution power grids with a central voltage-control system are used. The results show that the proposed method is effective to estimate the missing values in the case of communication problems between smart meters and the central control system, even for ill-conditioned systems.dc.description.abstract
Languageen_USdc.language.iso
PublisherUniversität Ulmdc.publisher
LicenseStandarddc.rights
Link to license texthttps://oparu.uni-ulm.de/xmlui/license_v3dc.rights.uri
KeywordRTDSdc.subject
KeywordPhotovoltaicdc.subject
KeywordReal-time digital simulatordc.subject
KeywordSmart griddc.subject
KeywordReactive power controldc.subject
Dewey Decimal GroupDDC 620 / Engineering & allied operationsdc.subject.ddc
LCSHSmart power gridsdc.subject.lcsh
LCSHReactive powerdc.subject.lcsh
LCSHPhotovoltaic power system (Engineering)dc.subject.lcsh
TitleCentral reactive power control for smart low-voltage distribution gridsdc.title
Resource typeDissertationdc.type
Date of acceptance2017-09-21dcterms.dateAccepted
RefereeXie, Jiandc.contributor.referee
RefereeStrunz, Kaidc.contributor.referee
DOIhttp://dx.doi.org/10.18725/OPARU-4782dc.identifier.doi
PPN1010227033dc.identifier.ppn
URNhttp://nbn-resolving.de/urn:nbn:de:bsz:289-oparu-4839-8dc.identifier.urn
GNDIntelligentes Stromnetzdc.subject.gnd
GNDBlindleistungdc.subject.gnd
GNDFotovoltaikdc.subject.gnd
FacultyFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.affiliationGeneral
InstitutionInstitut für Energiewandlung und -speicherunguulm.affiliationSpecific
Shelfmark print versionW: W-H 15.353uulm.shelfmark
Grantor of degreeFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.thesisGrantor
DCMI TypeTextuulm.typeDCMI
CategoryPublikationenuulm.category
Bibliographyuulmuulm.bibliographie


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