ANN-based city heat demand forecast

摘要

This paper discusses the importance of accurate forecasting tools in solving power system planning, modelling and optimization tasks. While artificial neural networks are widely considered to be one of the best prediction methods, their accuracy can vary greatly depending on the network structure and parameters. A method of experimentally finding the best ANN parameters has been offered and tested on heat demand forecasting. Some value of the benefits of increased prediction accuracy on the operation of CHP plants has been identified.