Memory-based prediction of district heating temperature using GPGPU

Abstract

The paper presents application of the memory-based prediction to the problem of the return water temperature prognosis in a district heating network. CHP (Combined Heating Plant) problem is defined as well as the algorithm based on the memory of the historical process realizations together with its novel, parallel implementation using CUDA on GPGPU. The use of the calculation extensive methods from one side enables to get good and reliable predictions, but in opposite the prognosis evaluation is done at high cost. An alternative application of the massively parallel version of the Memory-based time series prediction algorithm has been implemented and tested. The paper shows very good and promising improvement in comparison to the common applications. The algorithm is tested on the real process data.