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|Title:||Energy time series forecasting : efficient and accurate forecasting of evolving time Series from the energy domain||Authors:||Lars Dannecker||Keywords:||Energy, energy consumption, electric power consumption, electricity demand||Issue Date:||2015||Publisher:||Springer||Abstract:||Continuous balancing of electric power consumption and production is a fundamental prerequisite for the stability and efﬁciency of electricity grids. This balancing task requires accurate forecasts of future electricity demand and supply at any point in time. For this purpose, today’s energy data management systems (EDMS) typically use quantitative models—called forecast models—that already provide accurate predictions. However, recent developments in the energy domain such as real-time intra-day trading and the integration of more renewable energy sources also require more efﬁcient forecasting calculations and a rapid provisioning of forecasting results. Furthermore, today’s EDMSs fulﬁll a number of different tasks, each exhibiting different requirements for the calculation of forecasts with respect to runtime and accuracy. Thus, it is necessary to ﬂexibly adapt the forecasting process with respect to the needs of the current requests. In contrast, currently employed forecasting approach esare rather time-consuming and inﬂexible.One reason is the very expensive estimation of the forecast model parameters, involving a large number of simulations in a search space that increases exponential with the number of parameters.||URI:||http://dspace.uniten.edu.my/jspui/handle/123456789/13420|
|Appears in Collections:||UNITEN Energy Collection|
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|Energy Time Series Forecasting_ Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain.pdf||6.95 MB||Adobe PDF||View/Open Request a copy|
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