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Energy Time Series Forecasting

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

Lars Dannecker

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Springer Fachmedien Wiesbaden GmbH img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

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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Schlagwörter

Electric Power Consumption, Erneuerbarre Energien, Elektrizitätsverbrauch, The European Electricity Market, Energy Data Management and Forecasting, Renewable Energy Sources, Der Europäische Strommarkt, Energiebedarf in der Zukunft, Future Demand in Electricity, Energiemanagement und -prognose