Advanced Search

Show simple item record

dc.contributor.authorYükseltan, Ergün
dc.contributor.authorYücekaya, Ahmet
dc.contributor.authorBilge, Ayşe Hümeyra
dc.contributor.authorAğca Aktunç, Esra
dc.date.accessioned2020-12-24T09:10:23Z
dc.date.available2020-12-24T09:10:23Z
dc.date.issued2020
dc.identifier.issn0038-0121en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/3640
dc.identifier.urihttps://doi.org/10.1016/j.seps.2020.100937
dc.description.abstractDue to expensive infrastructure and the difficulties in storage, supply conditions of natural gas are different from those of other traditional energy sources like petroleum or coal. To overcome these challenges, supplier countries require take-or-pay agreements for requested natural gas quantities. These contracts have many pre-clauses; even if they are not met due to low/high consumption or other external factors, buyers must completely fulfill them. A similar contract is then imposed on distributors and wholesale consumers. It is, thus, important for all parties to forecast their daily, monthly, and annual natural gas demand to minimize their risk. In this paper, a model consisting of a modulated expansion in Fourier series, supplemented by deviations from comfortable temperatures as a regressor is proposed for the forecast of monthly and weekly consumption over a one-year horizon. This model is supplemented by a day-ahead feedback mechanism for the forecast of daily consumption. The method is applied to the study of natural gas consumption for major residential areas in Turkey, on a yearly, monthly, weekly, and daily basis. It is shown that residential heating dominates winter consumption and masks all other variations. On the other hand, weekend and holiday effects are visible in summer consumption and provide an estimate for residential and industrial use. The advantage of the proposed method is the capability of long term projections, reflecting causality, and providing accurate forecasts even with minimal information.en_US
dc.language.isoengen_US
dc.publisherElsevier Ltden_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFeedbacken_US
dc.subjectForecastingen_US
dc.subjectFourier seriesen_US
dc.subjectModulationen_US
dc.subjectNatural gas consumptionen_US
dc.subjectTime series analysisen_US
dc.titleForecasting Models For Daily Natural Gas Consumption Considering Periodic Variations And Demand Segregationen_US
dc.typearticleen_US
dc.relation.journalSocio-Economic Planning Sciencesen_US
dc.identifier.volume2020en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000630128700001en_US
dc.identifier.doi10.1016/j.seps.2020.100937en_US
dc.identifier.scopus2-s2.0-85090215008en_US
dc.institutionauthorYükseltan, Ergünen_US
dc.institutionauthorYücekaya, Ahmeten_US
dc.institutionauthorBilge, Ayşe Hümeyraen_US
dc.institutionauthorAğca Aktunç, Esraen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record