District heating and cooling systems - Framework for Modelica-based simulation and dynamic optimization
(2017) In Energy 137. p.566-578- Abstract
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 thermo-hydraulic simulation and optimization of district heating and cooling systems. We describe physically precise and numerically robust models for simulation and continuous optimization. Furthermore, 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... (More)
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 thermo-hydraulic simulation and optimization of district heating and cooling systems. We describe physically precise and numerically robust models for simulation and continuous optimization. Furthermore, 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.
(Less)
- author
- Schweiger, Gerald LU ; Larsson, Per Ola LU ; Magnusson, Fredrik LU ; Lauenburg, Patrick LU and Velut, Stéphane LU
- organization
- publishing date
- 2017-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- District cooling, District heating, Dynamic optimization, Dynamic simulation, Mixed-integer-optimal control, Modelica, Smart energy systems
- in
- Energy
- volume
- 137
- pages
- 566 - 578
- publisher
- Elsevier
- external identifiers
-
- scopus:85019674003
- wos:000414879400051
- ISSN
- 0360-5442
- DOI
- 10.1016/j.energy.2017.05.115
- language
- English
- LU publication?
- yes
- id
- a552eda0-aebe-473f-a5a3-2b5a6266c4cb
- date added to LUP
- 2017-06-09 14:51:50
- date last changed
- 2024-04-14 12:17:11
@article{a552eda0-aebe-473f-a5a3-2b5a6266c4cb,
abstract = {{<p>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 thermo-hydraulic simulation and optimization of district heating and cooling systems. We describe physically precise and numerically robust models for simulation and continuous optimization. Furthermore, 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.</p>}},
author = {{Schweiger, Gerald and Larsson, Per Ola and Magnusson, Fredrik and Lauenburg, Patrick and Velut, Stéphane}},
issn = {{0360-5442}},
keywords = {{District cooling; District heating; Dynamic optimization; Dynamic simulation; Mixed-integer-optimal control; Modelica; Smart energy systems}},
language = {{eng}},
pages = {{566--578}},
publisher = {{Elsevier}},
series = {{Energy}},
title = {{District heating and cooling systems - Framework for Modelica-based simulation and dynamic optimization}},
url = {{http://dx.doi.org/10.1016/j.energy.2017.05.115}},
doi = {{10.1016/j.energy.2017.05.115}},
volume = {{137}},
year = {{2017}},
}