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About this book
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.
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Table of contents (7 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
About 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.
Bibliographic Information
Book Title: Energy Time Series Forecasting
Book Subtitle: Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain
Authors: Lars Dannecker
DOI: https://doi.org/10.1007/978-3-658-11039-0
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Fachmedien Wiesbaden 2015
Softcover ISBN: 978-3-658-11038-3Published: 14 August 2015
eBook ISBN: 978-3-658-11039-0Published: 06 August 2015
Edition Number: 1
Number of Pages: XIX, 231
Number of Illustrations: 73 b/w illustrations, 19 illustrations in colour
Topics: Data Structures and Information Theory, Theory of Computation, Information Systems and Communication Service