Stammdaten

Titel: Optimal Residential Load Scheduling Based on Time Varying Pricing Scheme
Untertitel:
Kurzfassung:

Demand response (DR) has been getting widespread attention for smart grids to manage the required power demand with the available power supply resources. The recent integration of information and communication technology (ICT) systems has presented new opportunities for residential load scheduling systems to improve energy consumption by shifting or curtailing the demand required with respect to price change or emergency cases. In this paper, an optimal residential load scheduling system (ORLS) is proposed for dynamic scheduling of household appliances on the basis of a time of use (TOU) pricing scheme using iterative optimization method. The proposed load scheduling system encourages customers to manage their energy consumption to achieve lower energy bills and balance load consumption. Simulation results show that employing the proposed ORLS system benefits the customers by reducing their energy bill and the utility companies by decreasing the peak load of required customer load demand. The proposed residential load scheduling system based on TOU allows customers to reduce their energy bills by up to 31% and to decrease the peak load by up to 35%.

Schlagworte:
Publikationstyp: Beitrag in Sammelwerk (Autorenschaft)
Erscheinungsdatum: 11.12.2015 (Ton-, Bild- oder Datenträger)
Erschienen in: IEEE Student Conference on Research and Development (SCOReD)
IEEE Student Conference on Research and Development (SCOReD)
zur Publikation
 ( IEEE; )
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Seite: S. 210 - 214

Versionen

Keine Version vorhanden
Erscheinungsdatum: 11.12.2015
ISBN:
  • 978-1-4673-9572-4
DOI: http://dx.doi.org/10.1109/SCORED.2015.7449326
Homepage: -

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Vernetzte und Eingebettete Systeme
Universitätsstraße 65-67
9020 Klagenfurt am Wörthersee
Österreich
  -993640
   kornelia.lienbacher@aau.at
https://nes.aau.at/
zur Organisation
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 211909 - Energietechnik
  • 202022 - Informationstechnik
Forschungscluster
  • Energiemanagement und -technik
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Smart Grids Group

Kooperationen

Organisation Adresse
University of Al-Mustansiriyah
Baghdad
Irak
IQ  Baghdad
Universiti Tenaga Nasional
Kajang
Malaysia
MY  Kajang

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