- Titel
- pEDM
- Untertitel
- Online-Forecasting for Smart Energy Analytics
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-806438
- Konferenz
- CIKM'13: 22nd ACM International Conference on Information and Knowledge Management. San Francisco, 27. Oktober - 01. November 2013
- Quellenangabe
- CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management
Herausgeber: Qi He
Herausgeber: Arun Iyengar
Herausgeber: Wolfgang Nejdl
Herausgeber: Jian Pei
Herausgeber: Rajeev Rastogi
Erscheinungsort: New York
Verlag: ACM
Erscheinungsjahr: 2013
Seiten: 2411-2416
ISBN: 978-1-4503-2263-8 - Erstveröffentlichung
- 2013
- Abstract (EN)
- Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability of energy grids and requires accurate forecasts of electricity consumption and production at any point in time. Today's Energy Data Management (EDM) systems already provide accurate predictions, but typically employ a very time-consuming and inflexible forecasting process. However, emerging trends such as intra-day trading and an increasing share of renewable energy sources need a higher forecasting efficiency. Additionally, the wide variety of applications in the energy domain pose different requirements with respect to runtime and accuracy and thus, require flexible control of the forecasting process. To solve this issue, we introduce our novel online forecasting process as part of our EDM system called pEDM. The online forecasting process rapidly provides forecasting results and iteratively refines them over time. Thus, we avoid long calculation times and allow applications to adapt the process to their needs. Our evaluation shows that our online forecasting process offers a very efficient and flexible way of providing forecasts to the requesting applications.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der ACM Digital Library erschienen ist
DOI: 10.1145/2505515.2505588 - Freie Schlagwörter (DE)
- Vorhersage, Optimierung, Online-Berechnung, Wartung
- Freie Schlagwörter (EN)
- Forecasting, Optimization, Online Computation, Maintenance
- Klassifikation (DDC)
- 004
- Verlag
- ACM, New York
- Förder- / Projektangaben
- European Commission (EC)
FP7 | SP1 | ICT
Micro-Request-Based Aggregation, Forecasting and Scheduling of Energy Demand, Supply and Distribution
(MIRABEL)
ID: 248195 - Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-806438
- Veröffentlichungsdatum Qucosa
- 16.09.2022
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
