Forcasting Evolving Time Series of Energy Demand and Supply View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Lars Dannecker , Matthias Böhm , Wolfgang Lehner , Gregor Hackenbroich

ABSTRACT

Real-time balancing of energy demand and supply requires accurate and efficient forecasting in order to take future consumption and production into account. These balancing capabilities are reasoned by emerging energy market developments, which also pose new challenges to forecasting in the energy domain not addressed so far: First, real-time balancing requires accurate forecasts at any point in time. Second, the hierarchical market organization motivates forecasting in a distributed system environment. In this paper, we present an approach that adapts forecasting to the hierarchical organization of today’s energy markets. Furthermore, we introduce a forecasting framework, which allows efficient forecasting and forecast model maintenance of time series that evolve due to continuous streams of measurements. This framework includes model evaluation and adaptation techniques that enhance the model maintenance process by exploiting context knowledge from previous model adaptations. With this approach (1) more accurate forecasts can be produced within the same time budget, or (2) forecasts with similar accuracy can be produced in less time. More... »

PAGES

302-315

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-23737-9_22

DOI

http://dx.doi.org/10.1007/978-3-642-23737-9_22

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021262489


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