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dc.contributor.authorBirgen, Cansu
dc.contributor.authorMagnanelli, Elisa
dc.contributor.authorCarlsson, Per
dc.contributor.authorBecidan, Michael
dc.date.accessioned2021-07-19T10:57:53Z
dc.date.available2021-07-19T10:57:53Z
dc.date.created2021-01-07T09:36:16Z
dc.date.issued2021
dc.identifier.issn0360-5442
dc.identifier.urihttps://hdl.handle.net/11250/2764755
dc.description.abstractThe aim of this study was to develop a data analysis method which could provide operational insights and guidelines waste-to-energy (WtE) plant operators. A method to filter outliers with changing properties was combined with a cross-correlation analysis method that can capture nonlinearity and quantify time lags between variables. The method was applied to a dataset obtained from a commercial WtE plant. The method was able to detect already established correlations such as the influence of combustion conditions on NOx and CO emissions, which both had positive correlation with O2 concentration in the flue gas, while the effect of combustion conditions was unnoticeable for HCl emissions. Furthermore, the method could detect that NOx and SO2 emissions exhibited positive correlations with the furnace temperature. Time lags provided additional information about the sensor locations and plant dynamics. This methodology can be used especially when process data is available while good process models are not immediately accessible for determining non-obvious process phenomena not only for WtE sector but also for process industry in general.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleOperational guidelines for emissions control using cross-correlation analysis of waste-to-energy process dataen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holderThe Authorsen_US
dc.source.volume220en_US
dc.source.journalEnergyen_US
dc.identifier.doihttps://doi.org/10.1016/j.energy.2020.119733
dc.identifier.cristin1866765
dc.relation.projectNorges forskningsråd: 280949en_US
dc.source.articlenumber119733en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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