Design of district heating networks through an integrated thermo-fluid dynamics and reliability modelling approach

Abstract This paper aims to describe a newly developed analysis tool for supporting District Heating Networks (DHNs) grid design and energy-reliability optimization procedures. The tool couples a Thermo-fluid dynamic Module to simulate the energy and physical behaviour of the analysed network, and a Monte Carlo Module to manage grid failure and repair processes: as a consequence, it is able to investigate both the fluid dynamics and the reliability aspects of the entire network, from the production plants to the final users. The tool can also take into account the effect of thermal energy storages (TESs), whose installation along the grid could be beneficial not only to improve the efficiency and the management of the network, but also to increase the quality of the service and its reliability, reducing the number of hours of service disruption in the case of system failures. It thus allows evaluating the effects on both load coverage and overall network availability of different grid configurations assuming alternative size and location of TES systems. The methodology has been applied for testing purposes to a case study representative of a portion of an Italian district heating network, focusing on three different scenarios and several possible alternative grid configurations.

[1]  A. Blokus-Roszkowska,et al.  Probabilistic model of district heating operation process in changeable external conditions , 2015 .

[2]  R. Chacartegui,et al.  District heating systems based on low-carbon energy technologies in Mediterranean areas , 2017 .

[3]  Risto Lahdelma,et al.  Developing a multicriteria decision support framework for CHP based combined district heating systems , 2017 .

[4]  Maurizio Sasso,et al.  Combined cooling, heating and power for small urban districts: An Italian case-study , 2014 .

[5]  Brian Elmegaard,et al.  Integration of large-scale heat pumps in the district heating systems of Greater Copenhagen , 2016 .

[6]  Ali Reza Seifi,et al.  Simultaneous integrated optimal energy flow of electricity, gas, and heat , 2015 .

[7]  Alice E. Smith,et al.  A General Neural Network Model for Estimating Telecommunications Network Reliability , 2009, IEEE Transactions on Reliability.

[8]  Hongbo Ren,et al.  Multi-objective optimization of a distributed energy network integrated with heating interchange , 2016 .

[9]  Ali Reza Seifi,et al.  Considering cost and reliability in electrical and thermal distribution networks reinforcement planning , 2015 .

[10]  Sylvain Serra,et al.  A MINLP optimization of the configuration and the design of a district heating network: Academic study cases , 2016 .

[11]  Kody M. Powell,et al.  Thermal Energy Storage to Minimize Cost and Improve Efficiency of a Polygeneration District Energy System in a Real-time Electricity Market , 2016 .

[12]  Gintautas Dundulis,et al.  Development of approach for reliability assessment of pipeline network systems , 2012 .

[13]  Sebastian Herkel,et al.  Spatial distribution of thermal energy storage systems in urban areas connected to district heating for grid balancing—A techno-economical optimization based on a case study , 2016 .

[14]  Congcong Li,et al.  Reliability assesment of distribution systems with distributed generation based on Bayesian networks , 2014 .

[15]  Ibrahim Dincer,et al.  Thermal Energy Storage , 2004 .

[16]  Risto Lahdelma,et al.  Analysis of the location for peak heating in CHP based combined district heating systems , 2015 .

[17]  Gintautas Dundulis,et al.  Integrated assessment of failure probability of the district heating network , 2015, Reliab. Eng. Syst. Saf..

[18]  Marc A. Rosen,et al.  District heating and cooling: Review of technology and potential enhancements , 2012 .

[19]  Sven Werner,et al.  International review of district heating and cooling , 2017 .

[20]  Fu Xiao,et al.  Robust optimal design of district cooling systems and the impacts of uncertainty and reliability , 2016 .

[21]  M. Lampinen,et al.  Energy efficiency improvements utilising mass flow control and a ring topology in a district heating network , 2014 .

[22]  Helge V. Larsen,et al.  Balmorel: A model for analyses of the electricity and CHP markets in the Baltic Sea region , 2001 .

[23]  Yi Liu,et al.  Monte-Carlo Simulation for the Reliability Analysis of Multi-status Network System Based on Breadth First Search , 2009, 2009 Second International Conference on Information and Computing Science.

[24]  Frank Pettersson,et al.  A model for structural and operational optimization of distributed energy systems , 2014 .

[25]  Daniele Vigo,et al.  An optimization approach for district heating strategic network design , 2016, Eur. J. Oper. Res..

[26]  Michael T. Todinov Flow Networks: Analysis and optimization of repairable flow networks, networks with disturbed flows, static flow networks and reliability networks , 2013 .

[27]  Risto Lahdelma,et al.  Modelling and optimization of CHP based district heating system with renewable energy production and energy storage , 2015 .

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

[29]  Paul L. Younger,et al.  Towards the increased utilisation of geothermal energy in a district heating network through the use of a heat storage , 2016 .

[30]  Andrea Carpignano,et al.  Reliability and availability evaluation for highly meshed network systems: status of the art and new perspectives , 2002, Annual Reliability and Maintainability Symposium. 2002 Proceedings (Cat. No.02CH37318).

[31]  V. Miranda,et al.  Composite Reliability Assessment Based on Monte Carlo Simulation and Artificial Neural Networks , 2007, IEEE Transactions on Power Systems.

[32]  Marcelo Masera,et al.  Probabilistic modelling of security of supply in gas networks and evaluation of new infrastructure , 2015, Reliab. Eng. Syst. Saf..

[33]  Enrico Zio,et al.  Solving advanced network reliability problems by means of cellular automata and Monte Carlo sampling , 2005, Reliab. Eng. Syst. Saf..

[34]  Fredrik Wallin,et al.  Heat demand profiles of energy conservation measures in buildings and their impact on a district heating system , 2016 .

[35]  Neven Duić,et al.  Hourly optimization and sizing of district heating systems considering building refurbishment – Case study for the city of Zagreb , 2017 .

[36]  David J Smith,et al.  Reliability, Maintainability and Risk , 2013 .

[37]  Risto Lahdelma,et al.  A fuzzy-grey multicriteria decision making model for district heating system , 2018 .

[38]  Luca Podofillini,et al.  A combination of Monte Carlo simulation and cellular automata for computing the availability of complex network systems , 2006, Reliab. Eng. Syst. Saf..

[39]  Sven Werner,et al.  Thermal energy storage systems for district heating and cooling , 2021, Advances in Thermal Energy Storage Systems.

[40]  Pavel Praks,et al.  Monte-Carlo Based Reliability Modelling of a Gas Network Using Graph Theory Approach , 2014, 2014 Ninth International Conference on Availability, Reliability and Security.

[41]  Richard E. Rosenthal,et al.  GAMS -- A User's Guide , 2004 .

[42]  Jianing Zhao,et al.  A method for the steady-state thermal simulation of district heating systems and model parameters calibration , 2016 .

[43]  Patrick Lauenburg,et al.  Smart district heating networks – A simulation study of prosumers’ impact on technical parameters in distribution networks , 2014 .

[44]  Helge V. Larsen,et al.  A comparison of aggregated models for simulation and operational optimisation of district heating networks , 2004 .

[45]  Andrea Toffolo,et al.  Simulation and analysis of a meshed district heating network , 2016 .

[46]  Jan Dahl,et al.  A method for the simulation and optimization of district heating systems with meshed networks , 2015 .

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

[48]  Andrea Carpignano,et al.  Monte Carlo Method Application for Reliability and Availability Analysis of Highly Meshed Network Systems , 2004 .

[49]  Gabriele Comodi,et al.  Criticalities of district heating in Southern Europe: Lesson learned from a CHP-DH in Central Italy , 2017 .

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

[51]  Vida N. Sharifi,et al.  Optimisation of combined heat and power production for buildings using heat storage , 2014 .

[52]  Enrico Zio,et al.  A multi-state model for the reliability assessment of a distributed generation system via universal generating function , 2012, Reliab. Eng. Syst. Saf..