Energy Time Series Forecasting: Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain
Author:   Lars Dannecker
Publisher:   Springer Fachmedien Wiesbaden
Edition:   1st ed. 2015
ISBN:  

9783658110383


Pages:   231
Publication Date:   14 August 2015
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Energy Time Series Forecasting: Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain


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Overview

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.

Full Product Details

Author:   Lars Dannecker
Publisher:   Springer Fachmedien Wiesbaden
Imprint:   Springer Vieweg
Edition:   1st ed. 2015
Dimensions:   Width: 14.80cm , Height: 1.30cm , Length: 21.00cm
Weight:   3.301kg
ISBN:  

9783658110383


ISBN 10:   3658110384
Pages:   231
Publication Date:   14 August 2015
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of 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-Aware Storage.

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Author Information

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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