Stage-oe-small.jpg

Inproceedings3404: Unterschied zwischen den Versionen

Aus Aifbportal
Wechseln zu:Navigation, Suche
(Die Seite wurde neu angelegt: „{{Publikation Erster Autor |ErsterAutorNachname=Gitte |ErsterAutorVorname=Christian }} {{Publikation Author |Rank=2 |Author=Nicolas Renkamp }} {{Publikation Autho…“)
 
Zeile 26: Zeile 26:
 
|Abstract=In future smart grid scenarios, a greater involvement and active participation of customers are desirable in order to integrate renewable energy. Based on today’s electricity tariff schemes an evolutionary process could lead to real-time pricing and a significantly higher frequency of supplier changes. If this becomes reality, the business-to-business processes and the corresponding data exchange processes require most likely adjustments. In this paper it is investigated if current data exchange processes for supplier change are suitable for application to shorter cancellation periods and much shorter contract period for final customer’s energy contracts than today in Germany. Market actors and exchange processes are modelled as a multi-agent simulation and three different scenarios of aforementioned future contractual characteristics at the final customers’ site are examined. Main focus is given to the processes at the business-to-business level; final customers only act as triggers by contracting new suppliers.
 
|Abstract=In future smart grid scenarios, a greater involvement and active participation of customers are desirable in order to integrate renewable energy. Based on today’s electricity tariff schemes an evolutionary process could lead to real-time pricing and a significantly higher frequency of supplier changes. If this becomes reality, the business-to-business processes and the corresponding data exchange processes require most likely adjustments. In this paper it is investigated if current data exchange processes for supplier change are suitable for application to shorter cancellation periods and much shorter contract period for final customer’s energy contracts than today in Germany. Market actors and exchange processes are modelled as a multi-agent simulation and three different scenarios of aforementioned future contractual characteristics at the final customers’ site are examined. Main focus is given to the processes at the business-to-business level; final customers only act as triggers by contracting new suppliers.
 
|Forschungsgruppe=Effiziente Algorithmen
 
|Forschungsgruppe=Effiziente Algorithmen
 +
}}
 +
{{Forschungsgebiet Auswahl
 +
|Forschungsgebiet=Energieinformatik
 
}}
 
}}

Version vom 18. März 2014, 10:38 Uhr


Investigation of Data Exchange Processes for Electricity Supplier Change in German Smart Grid Scenarios


Investigation of Data Exchange Processes for Electricity Supplier Change in German Smart Grid Scenarios



Published: 2014 Februar

Buchtitel: Smarter Europe 2014, E-World Energy & Water 2014
Seiten: 6
Verlag: BDEW
Erscheinungsort: Essen
Organisation: BDEW

Nicht-referierte Veröffentlichung
Note: Accepted.

BibTeX

Kurzfassung
In future smart grid scenarios, a greater involvement and active participation of customers are desirable in order to integrate renewable energy. Based on today’s electricity tariff schemes an evolutionary process could lead to real-time pricing and a significantly higher frequency of supplier changes. If this becomes reality, the business-to-business processes and the corresponding data exchange processes require most likely adjustments. In this paper it is investigated if current data exchange processes for supplier change are suitable for application to shorter cancellation periods and much shorter contract period for final customer’s energy contracts than today in Germany. Market actors and exchange processes are modelled as a multi-agent simulation and three different scenarios of aforementioned future contractual characteristics at the final customers’ site are examined. Main focus is given to the processes at the business-to-business level; final customers only act as triggers by contracting new suppliers.



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet

Energieinformatik