Predictive control of district heating network using fuzzy DMC

This paper presents a concept for controlling the supply temperature in district heating networks (DHN) using model predictive control. Due to the inherent nonlinearity in the response characteristics caused by varying flow rates the use of Fuzzy Direct Matrix Control (DMC) is proposed. The fuzzy regions of the local Finite Impulse Response (FIR) models are determined by an axis-orthogonal, incremental partitioning scheme. It is demonstrated that the Fuzzy DMC performs well for the case study considered. In addition, different set point strategies are applied and the results are evaluated with respect to operational cost. In this context it is shown that the trade-off between pumping and heat loss cost plays an important role in minimizing overall cost.

[1]  Eduardo F. Camacho,et al.  Model Predictive Controllers , 2007 .

[2]  Bronislav Chramcov,et al.  Strategy evolution of control of extensive district heating systems , 2007, 2007 International Conference on Power Engineering, Energy and Electrical Drives.

[3]  O. Nelles.  Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models , 2000 .

[4]  Piotr Tatjewski,et al.  Advanced Control of Industrial Processes: Structures and Algorithms , 2006 .

[5]  C. Mondon,et al.  Predictive Control of a Complex District Heating Network , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[6]  Martin Kozek,et al.  Linear Finite-Difference Schemes for Energy Transport in District Heating Networks , 2011 .

[7]  Niels Kjølstad Poulsen,et al.  Temperature prediction at critical points in district heating systems , 2009, Eur. J. Oper. Res..

[8]  Martin Kozek,et al.  Efficient Physical Modelling of District Heating Networks , 2011 .

[9]  Benny Bøhm,et al.  Operational optimization in a district heating system , 1995 .

[10]  Henrik Madsen,et al.  Control of Supply Temperature in District Heating Systems , 1997 .

[11]  Helge V. Larsen,et al.  Simple models for operational optimisation , 2002 .

[12]  J. Holst,et al.  Tracking Time-Varying Coefficient-Functions , 2000 .

[13]  Helge V. Larsen,et al.  Aggregated dynamic simulation model of district heating networks , 2002 .

[14]  Andrew Wirth,et al.  Control period selection for improved operating performance in district heating networks , 2011 .

[15]  W. Cleveland.  Coplots, nonparametric regression, and conditionally parametric fits , 1994 .

[16]  R. Tibshirani,et al.  Varying‐Coefficient Models , 1993 .

[17]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .