Possibilities of Application of Computational Intelligence in Monitoring of Heat Production and Supply

Abstract

The article deals with on-line monitoring of heat sources with application of predictive system equipped with computational intelligence. In particular, an emphasis is given especially on efficiency, optimization of operation, predictability, and synergistic effects. The operation effectiveness will be evaluated from several perspectives such as the thermal properties of the objects, characteristics and properties of resources, and internal air quality. The proposed system based on the analytical/static approaches (e.g. heat loss models of heated objects) and applying the techniques of computational intelligence (e.g. artificial neural networks) creates a dynamic environment that can predict the amount of heat delivered not only on the basis of the energy requirements for the thermal balance of the heated objects and the current weather forecast, but the use of the data base and universal approximators in the field of computational intelligence on the behavior of objects in different operating conditions.