District energy systems: Modelling paradigms and general-purpose tools

Abstract District energy systems are a central element in transforming the energy system towards a low-carbon system. Simulation is regarded as key method for concept development and assessment as well as for operational optimization to address the growing complexity of these systems and to derive quantitative feedback e.g., as input for decision-support or operational processes. In this paper we present a comprehensive comparison of four widely used general-purpose modelling tools for district-scale energy systems, including a detailed discussion of modelling paradigms and co-simulation capabilities. This comparison is based on an extensive literature review, a comprehensive questionnaire that was conducted by tool and library developers, as well as a comparison of pipe model behavior of various libraries against measured data. The results including the experimental data are openly available and can support users in academia and industry with the selection of suitable modelling paradigms and associated tools and libraries.

[1]  Graziano Salvalai Implementation and validation of simplified heat pump model in IDA-ICE energy simulation environment , 2012 .

[2]  Sunanda Sinha,et al.  Review of software tools for hybrid renewable energy systems , 2014 .

[3]  François E. Cellier,et al.  Continuous System Simulation , 2006 .

[4]  Ercan Atam,et al.  Current software barriers to advanced model-based control design for energy-efficient buildings , 2017 .

[5]  Goran Strbac,et al.  Demand side management: Benefits and challenges ☆ , 2008 .

[6]  Brian Vad Mathiesen,et al.  From electricity smart grids to smart energy systems – A market operation based approach and understanding , 2012 .

[7]  Michael Wetter,et al.  Comparisons Of Building System Modeling Approaches For Control System Design , 2013, Building Simulation Conference Proceedings.

[8]  B.F. Wollenberg,et al.  Toward a smart grid: power delivery for the 21st century , 2005, IEEE Power and Energy Magazine.

[9]  Roland Baviere,et al.  Presentation, Validation and Application of the DistrictHeating Modelica Library , 2015 .

[10]  Dirk Saelens,et al.  Heat pump and PV impact on residential low-voltage distribution grids as a function of building and district properties , 2017 .

[11]  David Broman,et al.  Co-simulation: State of the art , 2017, ArXiv.

[12]  Gerald Schweiger,et al.  Framework for dynamic optimization of district heating systems using Optimica Compiler Toolkit , 2017, Modelica.

[13]  Jung-Ho Huh,et al.  Development of a method of real-time building energy simulation for efficient predictive control , 2016 .

[14]  Gerald Schweiger,et al.  Validation of dynamic building energy simulation tools based on a real test-box with thermally activated building systems (TABS) , 2018, Energy and Buildings.

[15]  Gerald Schweiger,et al.  author-version of: An empirical survey on co-simulation: Promising standards, challenges and research needs , 2022 .

[16]  Christoph F. Reinhart,et al.  Urban building energy modeling – A review of a nascent field , 2015 .

[17]  Gerhard Schmitz,et al.  Status of the TransiEnt Library: Transient Simulation of Coupled Energy Networks with High Share of Renewable Energy , 2015 .

[18]  Dirk Zimmer Using Artificial States in Modeling Dynamic Systems: Turning Malpractice into Good Practice , 2013, EOOLT.

[19]  Peter A. Fritzson,et al.  Principles of object-oriented modeling and simulation with Modelica 2.1 , 2004 .

[20]  Dirk Zimmer Equation-Based Modeling with Modelica - Principles and Future Challenges , 2016, Simul. Notes Eur..

[21]  Francesco Casella,et al.  Simulation of Large-Scale Models in Modelica: State of the Art and Future Perspectives , 2015 .

[22]  Karl-Erik Årzén,et al.  Modeling and optimization with Optimica and JModelica.org - Languages and tools for solving large-scale dynamic optimization problems , 2010, Comput. Chem. Eng..

[23]  Brian Vad Mathiesen,et al.  4th Generation District Heating (4GDH) Integrating smart thermal grids into future sustainable energy systems , 2014 .

[24]  Thierry S. Nouidui,et al.  Equation-based languages- A new paradigm for building energy modeling, simulation and optimization , 2016 .

[25]  Dirk Müller,et al.  Dynamic equation-based thermo-hydraulic pipe model for district heating and cooling systems , 2017 .

[26]  Yacine Rezgui,et al.  Holistic modelling techniques for the operational optimisation of multi-vector energy systems , 2018, Energy and Buildings.

[27]  Rita Streblow,et al.  Workflow automation for combined modeling of buildings and district energy systems , 2016 .

[28]  Jonas Allegrini,et al.  A review of modelling approaches and tools for the simulation of district-scale energy systems , 2015 .

[29]  Bernhard Bachmann,et al.  Solving large-scale Modelica models: new approaches and experimental results using OpenModelica , 2017, Modelica.

[30]  Steven Beyerlein,et al.  Review of district heating and cooling systems for a sustainable future , 2017 .

[31]  H. Torio,et al.  Development of system concepts for improving the performance of a waste heat district heating network with exergy analysis , 2010 .

[32]  Brian Vad Mathiesen,et al.  A review of computer tools for analysing the integration of renewable energy into various energy systems , 2010 .

[33]  Per Sahlin,et al.  IDA Simulation Environment a tool for Modelica based end-user application deployment , 2003 .

[34]  Karl Johan Åström,et al.  Evolution of Continuous-Time Modeling and Simulation , 1998, ESM.

[35]  Miika Rämä,et al.  Models for fast modelling of district heating and cooling networks , 2018 .

[36]  Vincent Lemort,et al.  ThermoCycle: A Modelica library for the simulation of thermodynamic systems , 2014 .

[37]  Gerald Schweiger,et al.  District heating and cooling systems – Framework for Modelica-based simulation and dynamic optimization , 2017 .

[38]  Christoph Hochenauer,et al.  Novel validated method for GIS based automated dynamic urban building energy simulations , 2017 .

[39]  W Wim Zeiler,et al.  An assessment methodology of sustainable energy transition scenarios for realizing energy neutral neighborhoods , 2018, Applied Energy.

[40]  Gerald Schweiger,et al.  Functional Mock-up Interface: An empirical survey identifies research challenges and current barriers , 2019, Proceedings of The American Modelica Conference 2018, October 9-10, Somberg Conference Center, Cambridge MA, USA.

[41]  Dirk Saelens,et al.  Coupling of dynamic building simulation with stochastic modelling of occupant behaviour in offices – a review-based integrated methodology , 2011 .

[42]  Dirk Müller,et al.  Iea Ebc Annex 60 Modelica Library – An International Collaboration to Develop A Free Open-Source Model Library for Buildings And Community Energy Systems , 2015, Building Simulation Conference Proceedings.

[43]  Michael Wetter,et al.  Co-simulation of building energy and control systems with the Building Controls Virtual Test Bed , 2011 .

[44]  Karl Thomaseth,et al.  Multidisciplinary modelling of biomedical systems , 2003, Comput. Methods Programs Biomed..

[45]  Mark Jennings,et al.  A review of urban energy system models: Approaches, challenges and opportunities , 2012 .

[46]  Peng Xu,et al.  Demand reduction in building energy systems based on economic model predictive control , 2012 .

[47]  Hilding Elmqvist,et al.  Modeling from Physical Principles , 1996 .

[48]  van Awm Jos Schijndel,et al.  Integrated Heat, Air and Moisture Modeling and Simulation in Hamlab, Reference: A41-T3-NL-05-2 , 2005 .

[49]  Michael Wetter,et al.  MODELICA VERSUS TRNSYS – A COMPARISON BETWEEN AN EQUATION-BASED AND A PROCEDURAL MODELING LANGUAGE FOR BUILDING ENERGY SIMULATION , 2006 .

[50]  Rüdiger Franke Flexible modeling of electrical power systems -- the Modelica PowerSystems library , 2014 .

[51]  Hilding Elmqvist,et al.  Transformation of Differential Algebraic Array Equations to Index One Form , 2017, Modelica.

[52]  Luigi Vanfretti,et al.  iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations , 2016, SoftwareX.

[53]  L. Lamarre Heating and cooling , 1998 .

[54]  Dirk Saelens,et al.  OpenIDEAS – An Open Framework for integrated District Energy Simulations , 2015, Building Simulation Conference Proceedings.