District heating and cooling systems - Framework for Modelica-based simulation and dynamic optimization

被引:101
作者
Schweiger, Gerald [1 ]
Larsson, Per-Ola [2 ]
Magnusson, Fredrik [2 ]
Lauenburg, Patrick [3 ]
Velut, Stephane [2 ]
机构
[1] AEE Inst Sustainable Technol, A-8200 Gleisdorf, Austria
[2] Modelon AB, SE-22370 Lund, Sweden
[3] Lund Univ, Dept Energy Sci, SE-22100 Lund, Sweden
关键词
District heating; District cooling; Smart energy systems; Modelica; Dynamic optimization; Dynamic simulation; Mixed-integer-optimal control; ENERGY-SYSTEMS; RENEWABLE ENERGY; OPERATION; INTEGRATION; NETWORKS; STORAGE;
D O I
10.1016/j.energy.2017.05.115
中图分类号
O414.1 [热力学];
学科分类号
摘要
Future district heating systems (so called 4th Generation District Heating (4GDH) systems) have to address challenges such as integration of (de)centralized renewable energy sources and storage, low system temperatures and high fluctuation of the supply temperature. This paper presents a novel framework for representing and simplifying on-grid energy systems as well as for dynamic thermohydraulic simulation and optimization of district heating and cooling systems. We describe physically precise and numerically robust models for simulation and continuous optimization. Futthermore, we propose a novel method to decompose a mixed-integer-optimal control problem into two sub-problems, separating the discrete part from the continuous. Two use cases show the applicability of the framework. An existing district heating system, with more than 100 consumers is adapted to test the framework based on simulation requirements of 4GDH systems. The second case presents the continuous optimization of a district heating system in a virtual city district. A main advantage of combining equation based modelling and nonlinear optimization is the possibility of including model coherences based on physical laws into the optimization formulation. Results show that the framework is well-suited for simulating larger scale 4GDH systems and that the solution time of the continuous optimization problem is sufficiently low for real-time applications. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:566 / 578
页数:13
相关论文
共 65 条
[1]   Modeling and optimization with Optimica and JModelica.org-Languages and tools for solving large-scale dynamic optimization problems [J].
Akesson, J. ;
Arzen, K-E. ;
Gafvert, M. ;
Bergdahl, T. ;
Tummescheit, H. .
COMPUTERS & CHEMICAL ENGINEERING, 2010, 34 (11) :1737-1749
[2]   A review of modelling approaches and tools for the simulation of district-scale energy systems [J].
Allegrini, Jonas ;
Orehounig, Kristina ;
Mavromatidis, Georgios ;
Ruesch, Florian ;
Dorer, Viktor ;
Evins, Ralph .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2015, 52 :1391-1404
[3]  
Andersson J., 2013, A General-Purpose Software Framework for Dynamic Optimization
[4]  
Andresen L., 2015, P 11 INT MOD C VERS, P695, DOI [10.3384/ecp15118695, DOI 10.3384/ECP15118695]
[5]  
[Anonymous], 2014, MOD UN OBJ OR LANG S
[6]  
[Anonymous], 2014, SSB2014 9 INT C SYST
[7]  
[Anonymous], 2005, POWER SYST COMPUT C
[8]  
[Anonymous], 2010, NONLINEAR PROGRAMMIN
[9]  
[Anonymous], THESIS
[10]  
[Anonymous], 2008, P 7 PYTHON SCI C