Daily Temperature Profile Prediction for the District Heating Application

Abstract

We show an application of artificial neural networks for local weather prediction. By employment of appropriate network structure and proper selection of input/output signals, solid results can be achieved. Our system was implemented in the local district heating company, where it was used to predict daily temperature profile with period of 15 minutes. Further, weekly and yearly profiles were predicted, and also heat consumption profiles. Whole prediction system consists of several chained neural networks and data processing modules. Training data for neural networks were collected from meteorological stations around the Košice city. Additional training data were collected by web-robots from internet from several weather forecast agencies. © Springer International Publishing Switzerland 2013.