The proposed method is validated in several test cases using experimental data from a plant in Nyk√∂ping. The optimizations demonstrate the feasibility and the high economic potential of the proposed approach when comparing with measurement data and the standard optimization techniques. The optimized planning schedules result in a balance between produced and consumed heat; priority to low-cost boilers and maximization plant revenue. Compared to measurement data; the optimizations result in a significantly lower supply temperature; a more extensive usage of the external cooler for higher efficiency and higher electricity production; fewer starts of units as well as an appropriate use of the accumulator tank.
The high-level description of optimization problems using JModelica.org provides useful means to specify flexible optimization problems including con-straints on arbitrary process variables such as heat load of the production units; supply temperature and flow rate; pressures.
Keywords: Production planning; nonlinear optimization; district heating; physical modeling; unit commitment
Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden
 C. Cervantes and L. T. Biegler,"Optimization strategies for dynamic systems," in C. Floudas, P. Pardalos (Eds), Encyclopedia of Optimization, 2000.
 J. √Ökesson, C. Laird, G. Lavedan, K. Pr√∂lss, H. Tummesheit, S. Velut and Y. Zhu,"Nonlinear Model Predictive Control of a CO2 post-combustion unit," Chemical Engineerging Technology, 2011.
 Ipopt homepage, coinor, http://projects.coinor.org/Ipopt/wiki/IpoptPapers.
 S. Mitchell, A. Mason, M. O’Sullivan and A. Phillips, "PuLP: a linear programming toolkit for python," http://www.coin-or.org/PuLP/.
 CBC Team, "CBC home page," 2013. [Online]. Available: https://projects.coinor.org/Cbc. [Accessed 12 August 2013].
 L. Saarinen, "Model-based control of district heating supply temperature," V√§rmeforsk P08-819, 2010.
 L. Saarinen and K. Boman, "Optimized district heating supply temperature for large networks," V√§rmeforsk P08-830, 2012.
 L. Saarinen, "Modeling and control of a district heating system," Master thesis, Uppsala University, 2008.
 Dassault Systemes, "Dassault Systemes Home Page," 2013. [Online]. Available: http://www.3ds.com/products/catia/portfolio/dymola. [Accessed 6 August 2013].
 The Modelica Association, "The Modelica Association Home Page," 2013. [Online]. Available: http://www.modelica.org. [Accessed 6 August 2013].
 J. Arroyo and A. Conejo, "Modeling of startup and shut-down power trajectories of thermal units," IEEE Transactions on power systems, vol. 19, no. 3, 2004.
 A. W√§chter and L. T. Biegler, "On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming," Mathematical Programming, vol. 196, no. 1, pp. 25-68, 2006.
 HSL, "A collection of Fortran codes for large scale scientific computation," 2013. [Online]. Available: http://www.hsl.rl.ac.uk. [Accessed 13 August 2013].
 P.-O. Larsson, PhD thesis: Optimization of Low-Level Controllers and High-Level Polymer Grade Changes, Lund, 2011.
 E. Dotzauer, "Algorithms for Short-Term Production planning of Cogeneration Plant," Lic. Thesis, Link√∂ping University, 1997.
 "www.jmodelica.org," Modelon AB, 2013. [Online]. Available: www.jmodelica.org. [Accessed 2013].
 Bauer, O. Modelling of Two-Phase Flows with Modelica, Master‚Äôs Thesis, Lund University, Department of Automatic Control, 1999.
 S. Velut, P.O. Larsson, J. Windahl, L. Saarinen, K. Boman, Non-linear and Dynamic Optimization for Short-term Production Planning. V√§rmeforsk report, 2013.