By Oliver Feindt, IAT, University of Bremen
Regenerative energies are increasingly being used to generate heat in district heating networks. This conversion requires an increasingly decentralized heat supply with smalle generating units and increases the complexity of the operation and the controls nets. Hereby, the optimal mode for the operation of the heat generation and distribution systems poses a great challenge.
Together with the utility Munich, the University of Bremen is developing a control concept with the aim of optimal operation of the increasigliy complex district heating netwok. Currently, a common Optimization of generator performance and flow temperatures with respect to economic aspects is utilized. A heat load forecast is carried out and the optimal distribution of the heat load is proposed subsequently, whereby the district heating network itself is only considered in a simplified way. The determined setpoint suggestions are then implemented as far as possible by operating personnel. As an extension of this approach, a model predictive control (MPC) using a network simulation is applied. The regulation should verify all relevant hydraulic and thermal boundary conditions of the network. In case economically optimized setpoints cannot be implemented, the new approoach generates new setpoints as close as possible to the given economic optimum.
Both physical network models and methods such as machine learning and system identification are used for the formulation of the proposed simulation. Different methods are also compared for the realization of MPC. In this work, the results of analyzing district heating networks with various complexity are presented and open points, advantages and disadvantages of the proposed concept are discussed.