Heiko Schroeder, Alexander Hobert, M. Zdrallek, Lena Seeger, C. Backhaus, Pascal Biesenbach
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Evaluation of a forecast model to predict electricity demand profiles of urban households considering dynamic incentives
Accurate load forecasting models are required for an efficient operation of energy systems and therefore, they have received increased attention from researches within this field of study. Several mathematical methods have been developed for load forecasting. This work aims at the implementation and evaluation of a modular regression model. Within this study, it is evaluated whether or not the model is suitable to predict different cumulated load profiles and if demand response incentives considered in the model can improve the accuracy.
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