(untitled) (Hungarian Journal of Industry and Chemistry, 2009)
The various governmental policies aimed at reducing the dependence on fossil fuels for space heating and the reduction in its associated emission of greenhouse gases such as CO2 demands innovative measures. District heating systems using residual industrial waste heats could provide such an efficient method for house and space heating. In such systems, heat is produced and/or thermally upgraded in a central plant and then distributed to the ﬁnal consumers through a pipeline network. In this work two main objectives will be considered: the first is to create a dynamic model which can represent the main characteristics of a district heating network and the second one is to design a non-linear model predictive controller (NLMPC) to satisfy the heat demands of the consumers in the heat exchanger network. As the model predictive controller is based on minimizing an objective function, it is totally perfect to find the way to reduce the superfluous energy consumption and make the best of using the freely applicable industrial waste heats. Beside this environmental aspect, reducing the invested energy consumption can reduce the operational costs.