Quasi-Real Time Individual Customer Based Forecasting of Energy Load Demand Using In Memory Computing

Witold Abramowicz , Monika Kaczmarek , Tomasz Rudny , Wioletta Sokołowska


This report presents the individual customer based approach to energy demand forecasting using the computational power of SAP HANA. The research hypothesis was that demand forecasting can be done in quasi-real time, even if conforming to bottom-up approach, i.e., computing separate forecasts for each customer. The report provides information on the project idea, used HPI Future SOC Lab resources, findings as well as next steps envisioned.
Author Witold Abramowicz (WIiGE / KIE)
Witold Abramowicz,,
- Department of Information Systems
, Monika Kaczmarek (WIiGE / KIE)
Monika Kaczmarek,,
- Department of Information Systems
, Tomasz Rudny (WIiGE / KIE)
Tomasz Rudny,,
- Department of Information Systems
, Wioletta Sokołowska (UEP)
Wioletta Sokołowska,,
- Poznań University of Economics and Business
Publication size in sheets0.5
Book Meinel Christoph, Polze Andreas, Oswald Gerhard, Strotmann Rolf, Seibold Ulrich, Schulzki Bernard (eds.): HPI future SOC lab : proceedings 2013, Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam, no. 88, 2014, Universitätsverlag Potsdam, ISBN 978-3-86956-282-7, 174 p.
Keywords in Englishin-memory computing, forecasting, energy
URL https://publishup.uni-potsdam.de/opus4-ubp/frontdoor/deliver/index/docId/6982/file/tbhpi88.pdf
Languageen angielski
Score (nominal)0
Citation count*
Share Share

Get link to the record

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Are you sure?