District Heating Expansion Potential with Low-Temperature and End-Use Heat Savings
Steffen Nielsen, Lars Grundahl
2018
Energies
District heating has the potential to play a key role in the transition towards a renewable energy system. However, the development towards reduced heat demands threatens the feasibility of district heating. Despite this challenge, opportunity exists in the form of fourth generation district heating, which operates at lower temperatures and enables better renewable integration. This article investigates this challenge by examining the district heating potential within three scenarios: The first
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... is a reference scenario with current heat demand and temperatures, the second includes heat demand savings and the third includes reduced grid temperatures in addition to heat savings. To examine the scenarios, two models are developed. The first is a heat atlas model, in which heat demands are mapped on an address level. The second model assesses district heating expansion potentials based on economic costs. The models are applied using an example case of The Northern Region of Denmark. The article concludes that the district heating potential is highest in the reference scenario. When heat savings are introduced, district heating expansions, in most cases, will not be feasible. Introducing low-temperature district heating modestly increases the feasible expansion potential. This general conclusion is highly dependent on the specific system examined. Energies 2018, 11, 277 2 of 17 the high temperature level in current systems, which have a typical forward temperature of around 80 • C. The heat distribution loss is important because most future scenarios implement large heat savings in existing buildings [9,10], while the requirements for new buildings are approaching near zero energy standards [11, 12] , resulting in a relatively higher share of network losses in the future if the same system properties are kept. Moreover, the temperature level is important because it hinders an efficient implementation of some renewable energy technologies that only supply heat at much lower temperatures, such as geothermal and solar thermal energy, or technologies like large-scale heat pumps [13] that benefit from lower supply temperatures. Therefore, considerable research efforts are being spent investigating the next generation of district heating, the so-called fourth generation [14] . The characteristics of fourth generation district heating are that the system temperatures are lower and a large variety of supply sources, mainly based on renewable energies, can be included. Much of the research examines new district heating concepts, with considerable focus given to the application of different system temperature levels, including low-temperature (55 • C) and even ultra-low temperature (35 • C) [15, 16] . These studies conclude that switching to ultra-low temperature reduces the grid losses but adds to the general system costs, and is therefore not an attractive solution. Thus, the best option for most systems seems to be low-temperature district heating. The potential for low-temperature district heating has primarily been assessed in energy systems analysis models, which show the synergies of the technology with the potential energy supply in renewable energy scenarios. However, an important aspect of district heating is the investment cost of the heating networks. The investment costs of district heating networks relate to the geographic placement of the buildings and associated heat demands. The closer the buildings are situated, the smaller the network need be, thereby reducing investment costs. Thus, a mapping of heat demands is required to determine if a location is suitable for district heating. Typically, the mapping of heat demands is done in a heat atlas for the location in question. Heat atlases come in all shapes and forms and are used for various purposes. Some are used to illustrate the geographic location of heat demands, with some recent examples including Paris [17] and London [18] . Others use heat atlases to estimate heat demands in energy strategies for cities or communities [19] [20] [21] [22] , countries [23, 24] or even on a European level [25, 26] . Recently, the authors of this article have used heat atlases to develop inputs for the planning of district heating expansions [27] [28] [29] [30] . The primary aim of these plans is to serve as inputs for local policymakers and utilities when making decisions on new heating infrastructure. The heat atlas used for these plans is called The Danish Heat Atlas and includes all buildings in Denmark. The Danish Heat Atlas exists in several versions, in which the heat demand models have been developed and improved over time [31, 32] . Since 2010, Danish legislation requires all suppliers of oil, natural gas, and district heating to send information regarding annual energy consumption to a central database named FIE, which is a Danish abbreviation for The Supply Companies Reporting Model for Energy Consumption. At present, the FIE database includes around half of all Danish buildings. This provides a quite comprehensive dataset, and offers the ability to improve the heat consumption models for Danish buildings that have been used to establish previous heat atlases [33]. Aim of the Article The aim of this article is twofold: The first part is to analyse the registered heat demands of buildings from the FIE database and to create a heat atlas based on these demands. The second part is to show the application of the heat atlas by assessing the district heating potential in a specific case. The case used is the northern region of Denmark, which consists of around 368 thousand buildings, of which 153 thousand already have district heating. The expansion potential of district heating in this case will be analysed with both standard and low-temperature district heating options. This is done to examine the challenges arising if the considerable renovations to the building stock included in many long-term energy plans are realised.
doi:10.3390/en11020277
fatcat:6k2fycwfbbh2jnpr5u4f2ef2a4