Economic Evaluation of 4th Generation District Heating Networks

Dear reader,

when we discuss the future role of district heating in the transformation of energy systems away from fossil fuels, it is impossible to ignore the economic incentives that determine the decision-making of district heating operators. In this context, we are excited to present a paper on the economic benefits of 4th generation district heating networks for this 8th issue of our heatbeat Research Newsletter. Interestingly, the main cause for these economic benefits is not that lower network temperatures lead to a reduction of heat losses. Instead, the paper argues that the effect of lower heat supply costs is more significant. Furthermore, the research results can offer a possible explanation for both hesitation to lower network temperatures in existing networks and for large potential of lower temperatures in future networks.

The short version

For this issue 8 of our newsletter, we have selected the paper Economic benefits of fourth generation district heating by Helge Averfalk and Sven Werner at Halmstad University in Sweden.

For this study, the authors model a medium sized network at two different temperature levels to evaluate the economic benefits of a 4th generation district heating network (4GDH) with lower network temperatures compared to a 3rd generation district heating network (3GDH) at higher temperatures. The results show that on the one hand, traditional combustion-based heat supply options like combined heat and power plants (CHP) fueled by waste or biomass have a comparably low cost sensitivity with regards to lower network temperatures. On the other hand, renewable heat sources like geothermal energy, industrial waste heat, and large-scale heat pumps show a high cost sensitivity and therefore are more strongly affected by lower network temperatures.

These results help explain the low economic motivation to reduce network temperatures in district heating networks which today are supplied by traditional combustion-based heat sources. Yet, assuming the requirement to use other renewable heat sources in future district heating systems, the paper shows a very high economic benefit of lower network temperatures. While these results support common perceptions of the challenges for 4GDH where many renewable heat sources benefit from lower network temperatures, we think that this analysis adds a very valuable perspective to help understand these challenges in detail. Furthermore, the paper demonstrates that the costs benefits of lower temperatures in future district heating networks are mainly driven by lower heat supply costs and less by reduced network heat losses, which may be contrary to some readers' expectations.

Our full summary

We chose the paper Economic benefits of fourth generation district heating by Helge Averfalk and Sven Werner for this issue of our newsletter because we think it contains important contributions to better understand the economic challenges for future district heating networks.

In this paper, the authors define a medium sized network for which they compare a 4th generation district district heating case with a 3rd generation district heating reference case. The main difference between the two cases is that the 4GDH case assumes lower network temperatures (55 - 60 °C supply, 25 °C return) than the 3GDH case (80 - 100 °C suppy, 40 - 60 °C return). For the analysis of the economic benefits of the 4GDH case over the 3GDH benchmark, the paper uses the Cost Reduction Gradient as the key metric. The Cost Reduction Gradient is defined as the annual economic benefit of a network temperature reduction in EUR divided by the total annual heat delivery to the network and by the average reduction in network temperature¹.

To give a simple example, a Cost Reduction Gradient of 0.50 EUR/(MWh*K) therefore means that for a given district heating system, reducing the average network temperature by 1 Kelvin leads to an economic benefit of 0.50 EUR for each MWh supplied to the network. In a network with an annual heat delivery of 200 GWh, reducing the network temperature by 20 K thus would lead to a total annual economic benefit of 2 Mio. EUR. In this context, a higher Cost Reduction Gradient can be seen as an indicator that lowering network temperatures has a large economic benefit while a low Cost Reduction Gradient indicates that lower network temperatures lead to only little economic benefit.

One important aspect of the study is that the paper investigates a future district heating scenario without any fossil fuel input and thus only considers renewable and recycled heat sources for both the 3GDH and the 4GDH options. These renewable heat sources include CHP plants fired with waste or biomass, geothermal heat, industrial waste heat, large-scale heat pumps, and solar-thermal heat. In each investigated variant, the authors assume that one primary renewable heat source from these options provides 90 % of the annual heat delivery to the network. The remaining 10 % are then supplied by a peak load boiler fired with bio-oil. As a result, most options require larger supply plant capacities for the 3DGH case, leading to higher costs for higher network temperatures.

While this study design of course has some limitations (which are comprehensively explained by the authors in the original paper), the authors achieve very interesting results by calculating the Cost Reduction Gradient for each of the investigated heat supply technologies. Furthermore, they explain the different shares of reduced heat losses, the heat source's main fuel costs, the peak load unit's fuel costs, and the electricity consumption or generation of the main heat source on the Cost Reduction Gradient. And in addition to this depth of the analysis, they compare their findings to Cost Reduction Gradients determined in previous studies, which rounds up a comprehensive comparison of the different heat sources and their economic benefits in 4GDH networks.

Comparing the final results of the study shows that the combustion-based heat sources that include waste and biomass CHPs and biomass boilers arrive at relatively low Cost Reduction Gradiants. The values range between 0.06 EUR/(MWh*K) for the waste-fired CHP and 0.17 EUR/(MWh*K) for the biomass-fired CHP. In comparison, the other renewable heat sources geothermal heat, industrial waste heat, large-scale heat pumps, and solar thermal range between around 0.35 and 0.7 EUR/(MWh*K) for both their operation and their investment. These values give a good indication on how sensitive different heat sources' costs react on lower network temperatures. Furthermore, the results go into more detail and illustrate how the lower heat losses in 4GDH are only a minor factor in the cost reductions compared to the cost benefits of the supply plants.

We think that this approach and the Cost Reduction Gradient metric can support future energy system design processes and help to better understand how to find environmentally friendly solutions that are also economically feasible. Our project experience at heatbeat confirms that the best energy system designs often require to evaluate heat supply options and network operation, including network temperatures, in a holistic way. For this task, we think that the presented paper contributes to building a good foundation with an interesting analysis of how sensitive different heat supply technologies react to changes in the network temperature.

¹The authors originally define the Cost Reduction Gradient based on the annual heat delivery in TJ. In our project work at heatbeat, we usually use the unit MWh for the heat delivery. Therefore, in this newsletter, we have converted all values for the Cost Reduction Gradient to EUR/(MWh*K).

Further information

You can find the original research paper at which is available as open access. We highly recommend the paper as it not only includes the interesting results we summarized above, a very comprehensive overview of the literature, and a discussion of the limitations of the study, but also more details on each of the investigated variants.

The next issue of our newsletter will be published on July 7.

Best regards,
your heatbeat team