Control assessment in coupled local district heating and electrical distribution grids: Model predictive control of electric booster heaters

Abstract Intelligent control schemes are essential for the implementation of smart energy systems, where district heating and electric networks are tightly interconnected. The increasing complexity of such networked infrastructure has resulted in the need to test and assess control algorithms before field deployment. This work presents a method to assess advanced control schemes for thermal-electric appliances with explicit consideration of coupled heat and power networks. It is based on closed loop simulation of high-fidelity physical system models, using dynamic thermal-hydraulic district heating and electric distribution network models, and low-fidelity time-discrete advanced control models. Co-simulation is used to perform coupled simulations of the different involved domains and tools. A test case is presented where a model predictive control scheme for grid friendly operation of domestic hot water electric booster heaters is implemented in a low-temperature district heating and low-voltage electric distribution network. Test case results show that the control is able to reduce peaks in district heating and electric networks compared to a simple reference controller. A comparison between using perfect and naive forecasts shows that control performance highly depends on the availability of accurate predictions. The results underline the versatility of the method to assess different control schemes in integrated networks.

[1]  Andreas Junghanns,et al.  The Functional Mockup Interface for Tool independent Exchange of Simulation Models , 2011 .

[2]  Bernd Möller,et al.  Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system , 2014 .

[3]  Wolfgang Gawlik,et al.  A method for technical assessment of power-to-heat use cases to couple local district heating and electrical distribution grids , 2019, Energy.

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

[5]  C F Colebrook,et al.  TURBULENT FLOW IN PIPES, WITH PARTICULAR REFERENCE TO THE TRANSITION REGION BETWEEN THE SMOOTH AND ROUGH PIPE LAWS. , 1939 .

[6]  Nikos D. Hatziargyriou,et al.  Optimal operation of smart distribution networks: A review of models, methods and future research , 2016 .

[7]  Dirk Müller,et al.  Bidirectional low temperature district energy systems with agent-based control: Performance comparison and operation optimization , 2018 .

[8]  David Connolly,et al.  Smart energy and smart energy systems , 2017 .

[9]  M. Alary,et al.  Risk factors for contamination of domestic hot water systems by legionellae , 1991, Applied and environmental microbiology.

[10]  Daniele Basciotti,et al.  Simulation of multi-domain energy systems based on the functional mock-up interface specification , 2015, 2015 International Symposium on Smart Electric Distribution Systems and Technologies (EDST).

[11]  Michael Knudsen,et al.  Model predictive control for demand response of domestic hot water preparation in ultra-low temperature district heating systems , 2017 .

[12]  Klaus Vajen,et al.  DHWcalc: PROGRAM TO GENERATE DOMESTIC HOT WATER PROFILES WITH STATISTICAL MEANS FOR USER DEFINED CONDITIONS , 2005 .

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

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

[15]  Yang Wang,et al.  A Review of Active Management for Distribution Networks: Current Status and Future Development Trends , 2014 .

[16]  Michael Wetter,et al.  A framework for simulation-based real-time whole building performance assessment , 2012 .

[17]  Henrik W. Bindner,et al.  Technical assessment of electric heat boosters in low-temperature district heating based on combined heat and power analysis , 2018 .

[18]  Lieve Helsen,et al.  Controlling district heating and cooling networks to unlock flexibility: A review , 2018 .

[19]  Peter Palensky,et al.  FMI-based co-simulation of hybrid closed-loop control system models , 2015, 2015 International Conference on Complex Systems Engineering (ICCSE).

[20]  M. Chertkov,et al.  Towards future infrastructures for sustainable multi-energy systems: A review , 2019, Energy.

[21]  R. Bavière,et al.  Storage influence in a combined biomass and power-to-heat district heating production plant , 2019, Energy.

[22]  Niels Kjølstad Poulsen,et al.  Model Predictive Control for a Smart Solar Tank Based on Weather and Consumption Forecasts , 2012 .

[23]  William A. Beckman,et al.  Performance study of one-dimensional models for stratified thermal storage tanks , 1993 .

[24]  Frank P. Incropera,et al.  Fundamentals of Heat and Mass Transfer , 1981 .