Erschienen: 14.08.2015 Abbildung von Dannecker | Energy Time Series Forecasting | 1. Auflage | 2015 | beck-shop.de

Dannecker

Energy Time Series Forecasting

Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain

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74,89 €

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auch verfügbar als eBook (PDF) für 74.89 €

Fachbuch

Buch. Softcover

1st ed. 2015. 2015

xix, 249 S. 73 s/w-Abbildungen, 19 Farbabbildungen, 8 s/w-Tabelle, Bibliographien.

In englischer Sprache

Springer Vieweg. ISBN 978-3-658-11038-3

Format (B x L): 14,8 x 21 cm

Gewicht: 3301 g

Produktbeschreibung

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. Contents - 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-AwareStorage Target Groups - 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 The Author Lars Dannecker holds a diploma in media computer science from the Technische Universität Dresden and is pursuing a doctorate as a member of the Database Technology Group led by Prof. Dr.-Ing. Wolfgang Lehner.

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