Dynamic modeling of local district heating grids with prosumers: A case study for Norway
Introduction
District heating (DH) is an important technology in that it enables efficient and economical utilization of energy sources, that would otherwise be wasted, to cover buildings' heating demands [1]. DH will play an important role in the future fossil-free energy systems by enabling increased utilization of waste heat and renewable heat sources; however, a prerequisite for this is a reduction in the distribution temperatures and shift towards decentralized heat production [[2], [3], [4]]. With this, DH will allow reducing the load from the electric grid by utilizing DH for heating purposes instead of electricity wherever possible, hence promoting the utilization of electricity for other purposes where high-quality energy is needed, such as transport.
Reduced supply temperature level in DH provides a number of advantages. These include: (i) Reduction in the distribution heat losses [[5], [6], [7]]; (ii) Improved utilization of low-temperature waste heat sources from buildings and industry [3,8]; and (iii) Improved efficiency and production capacity for solar thermal and higher COP for heat pumps [9]. Highlighting the new era of district heating, the concept of 4th generation district heating (4GDH) has been introduced by Lund et al. [3]. 4GDH refers to low-temperature DH systems with waste heat utilization, integration of renewable heat and an ability to be an integrated part of smart energy systems, including thermal, electric and gas grids.
Conventionally, DH systems have been based on large, centralized combustion plants or utilization of industrial waste heat sources, characterized by high capacities and temperature levels. Potential for utilization of industrial waste heat sources is enormous, in particular in central Europe [10]. Such waste heat sources are however often placed outside cities and require high heat demand densities in order to justify the investments required for the heat distribution system. In Norway, heavy industries with high availability of surplus heat are often located in remote places in the coast due to availability of large hydro power resources and easy access by ships.
Potential surplus heat suppliers present in urban environments are buildings with large chiller and refrigeration facilities, such as data centers, office buildings or food retail stores. Such buildings may have a demand for heat at low ambient temperatures and surplus heat available otherwise, and are thus referred to as heat prosumers. Urban waste heat recovery with prosumers is already practiced in for instance Stockholm under the Open District Heating Concept [11]. The impact of including prosumers in a DH grid has also been studied by the scientific community, considering the energy balance and environmental impact [8], as well as the technical challenges [12,13]. Brange et al. [8] studied the potential of prosumers for a building area in Sweden with a high number of prosumers, including e.g. supermarkets and an indoor ice skating rink, concluding that the prosumers could potentially cover the entire heating demand of the area. Electricity would however be needed to obtain the required temperature levels, either with heat pumps or direct electric heating, and the environmental impact of the DH system with prosumers hence depends on the source of the electricity. Lennermo et al. [12] and Brand et al. [13] have reported on problems with differential pressure in the DH network, resulting from decentralized heat supply by solar collectors at a lower temperature level, and rapidly varying heat demand. This calls for proper control strategies when introducing decentralized heat suppliers in DH systems.
Due to the high investment costs related to DH systems, there is a great interest in simulation and planning software to find the most optimal solutions regarding production and distribution of heat [14]. Such tools will become increasingly important with the increased complexity of 4GDH grids including decentralized heat production by prosumers, often in combination with thermal storage and an advanced control system. There are many software tools available for simulation of DH systems; a comprehensive overview has been given in Ref. [15]. For detailed physical modeling of DH systems, the dynamic simulation program Dymola using the object-oriented modeling language Modelica has been proven to be a flexible and efficient tool [6,14,[16], [17], [18]].
In a previous study [7], a component library for modeling local DH grids was created in Dymola in order to study and compare different scenarios with various supply temperature levels for the local DH grid. For the present study, the component library has been improved and extended to study the impact of including prosumers in a local low-temperature DH grid. Two types of prosumers were included, a data center and food retail stores, each with different, dynamic characteristics for the surplus heat delivery as well as different placement in the local DH grid. This enabled detailed investigation of the fluid flow in different parts of the grid during varying amounts of surplus heat delivery. The remaining heat demand was covered by a heat central, assumed to have the same energy mix as the DH supplier in Trondheim. The heating grid with prosumers was compared with two baseline cases, a high- and a low-temperature heating grid, in which the heat demand was entirely supplied by the heat central.
The objectives of this study are to (i) demonstrate dynamic modeling of a heating grid with prosumers; (ii) investigate the technical challenges related to inclusion of prosumers; and (iii) study the energetic and environmental benefits of surplus heat delivery.
Section snippets
Methodology
The methodology consisted of the following primary steps:
- 1.
Collecting data for DH demand profiles for modern buildings representing different building categories, located in Trondheim (see Ref. [7]).
- 2.
Upgrading the Dymola model for a local DH grid from the previous study [7], including new and improved components.
- 3.
Simulating different scenarios for a local low-temperature grid with and without prosumers, and comparing the results to a reference, high-temperature scenario representing the current
Overall comparison
Table 3 summarizes the results for total annual delivered heat by the heat central and the prosumers, as well as the total annual heat losses and pump work for the four simulated scenarios. For the LT scenario, the reduction in heat delivered by the heat central is only 1% with respect to the reference (HT) scenario, and this is solely due to the reduction in heat losses. For the LTP1 and LTP2 scenarios with surplus heat delivery, the reduction is 13 and 25%, respectively. The heat losses are
Discussions and conclusions
There is a high potential for utilization of local low-temperature surplus heat in small-scale DH grids. In the present simulation case study, considering a building area with two retail stores and a data center as the surplus heat suppliers, a reduction of up to 25% in the demand for delivered heat was obtained as compared to a high-temperature reference scenario. Regarding the environmental impact, a considerable reduction in CO2 equivalent emissions was obtained when considering the total
Acknowledgements
The authors greatly acknowledge support from the Research Council of Norway (RCN) under projects Development of Smart Thermal Grids (grant agreement (GA) number 245355), INTERACT (GA number 228656) and FME HighEFF (GA number 257632).
References (30)
- et al.
Energy efficiency improvements utilising mass flow control and a ring topology in a district heating network
Appl Therm Eng
(2014) - et al.
Heat Roadmap Europe: combining district heating with heat savings to decarbonise the EU energy system
Energy Pol
(2014) - et al.
4th Generation District Heating (4GDH): integrating smart thermal grids into future sustainable energy systems
Energy
(2014) - et al.
Low temperature district heating for future energy systems
Energy Proced
(2017) - et al.
Low-energy district heating in energy-efficient building areas
Energy
(2011) - et al.
Low temperature district heating in Austria: energetic, ecologic and economic comparison of four case studies
Energy
(2016) - et al.
Dynamic modelling of local low-temperature heating grids: a case study for Norway
Energy
(2017) - et al.
Prosumers in district heating networks - A Swedish case study
Appl Energy
(2016) - et al.
Lowering district heating temperatures - Impact to system performance in current and future Danish energy scenarios
Energy
(2016) - et al.
Heat Roadmap Europe: identifying strategic heat synergy regions
Energy Pol
(2014)
Smart district heating networks - A simulation study of prosumers impact on technical parameters in distribution networks
Appl Energy
Integration of storage and renewable energy into district heating systems: a review of modelling and optimization
Sol Energy
District heating and cooling systems - Framework for Modelica-based simulation and dynamic optimization
Energy
Equation-based languages - A new paradigm for building energy modeling, simulation and optimization
Energy Build
Method for optimal design of pipes for low-energy district heating, with focus on heat losses
Energy
Cited by (67)
Key district heating technologies for building energy flexibility: A review
2024, Renewable and Sustainable Energy ReviewsNetwork-aware P2P multi-energy trading in decentralized electric-heat systems
2023, Applied Energy