Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain
Buch, Englisch, 231 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 3301 g
ISBN: 978-3-658-11038-3
Verlag: Springer
Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing the process to adapt to different situations and applications. Improving the forecasting efficiency is a key pre-requisite for ensuring stable electricity grids in the face of an increasing amount of renewable energy sources. It is also important to facilitate the move from static day ahead electricity trading towards more dynamic real-time marketplaces. The online forecasting process is realized by a number of approaches on the logical as well as on the physical layer that we introduce in the course of this book.
Nominated for the Georg-Helm-Preis 2015 awarded by the Technische Universität Dresden.
Zielgruppe
- Lecturers and Students of Computer Science, especially in the Field of Database Technology, Data Analytics, Time Series Analysis, and Data Mining
- Data Analysts, Energy Time Series Modeling, Transmission System Operators, Software Developers
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
- Technische Wissenschaften Energietechnik | Elektrotechnik Energietechnik & Elektrotechnik
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
Weitere Infos & Material
The European Electricity Market: A Market Study.- The Current State of Energy Data Management and Forecasting.- The Online Forecasting Process: Efficiently Providing Accurate Predictions.- Optimizations on the Logical Layer: Context-Aware Forecasting.- Optimizations on the Physical Layer: A Forecast-Model-Aware Storage.
