Impact of distribution and transmission investment costs of district heating systems on district heating potential

Fallahnejad, Mostafa; Hartner, Michael; Kranzl, Lukas; Fritz, Sara

doi:10.1016/j.egypro.2018.08.178

Cited by 19 publications

(8 citation statements)

References 14 publications

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“…Here, a similar approach as proposed by Fallahnejad et al [8] is followed to identify potential DH areas. They used a heat demand density map and a heated gross floor area density map (for obtaining plot ratios), both with one-hectare resolution as input data.…”

Section: Identification Of Potential District Heating Areasmentioning

confidence: 99%

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District heating distribution grid costs: a comparison of two approaches

Fallahnejad

Kranzl

Hummel³

2022

IJSEPM

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Since the introduction of the effective width concept for the estimation of the linear heat density, it has been frequently used by researchers to calculate district heating distribution grid costs in pre-feasibility phases. Some researchers however, still prefer using a detailed modelling approach to get reliable results. This paper aims at highlighting advantages, disadvantages and challenges of using effective width concept for calculation of district heating distribution grid costs in comparison to a detailed, optimisation-based modelling approach such as DHMIN. The outcomes of this paper reveal that although there are differences in obtained indicators such as trench length or distribution gird costs, both approaches deliver very similar patterns in different areas with various heat demand densities and plot ratios. Furthermore, it was revealed that for getting reliable results for a given case study, the input parameters and cost components should always be tuned to that case study regardless of the approach that is used.

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Section: Identification Of Potential District Heating Areasmentioning

confidence: 99%

“…Fallahnejad et al proposed an approach based on the effective width concept for the identification of the potential DH areas [8]. In their GIS-based approach, areas with low heat demand densities were excluded.…”

Section: Introductionmentioning

confidence: 99%

District heating distribution grid costs: a comparison of two approaches

Fallahnejad

Kranzl

Hummel³

2022

IJSEPM

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“…We multiplied this CF by the distance between each BEP and heat sink to derive the required pipeline length (Formula 9). However, we did not consider the local distribution and transmission infrastructure that would be required, e.g., for district heating in residential areas [70].…”

Section: Steps 1-3: Assessment Indicatorsmentioning

confidence: 99%

Bioenergy plants’ potential for contributing to heat generation in Germany

et al. 2020

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Background: The Paris Climate Agreement requires a rapid and efficient shift to renewable energies and a decarbonization of the energy system. Combined heat and power provision from biomass is one way to efficiently provide renewable heat. Despite this, many bioenergy plants in Germany are mainly used to generate electricity and the provision of externally usable heat still has untapped potential. In this study, we investigated gross quantities as well as the economically viable potential of Germany's current bioenergy plant stock in supplying renewable heat. Methods:We used a top-down GIS modeling approach to spatially and explicitly assess the heat demand of three different categories of heat sinks at sub-municipal level. These included residential, commercial, and industrial areas, as well as large individual heat consumers. We then calculated the plant-specific heat sales potential for two different district heating network options. In addition, we developed a method for assessing the economic efficiency of the previously identified technical heat sales volume for a set of 20 different clusters of bioenergy plants. Results:The results show that about 50% of the bioenergy plants have potential heat consumers in their immediate proximity. The overall technical heat sales potential for all three categories totals around 150 TWh th /a. However, this potential is not evenly distributed throughout Germany. Certain regions appear to be more favorable for investing in district heating networks powered by heat from biomass. The economically viable heat sales potential related to electrical energy generation ranges from − 0.128 to 0.160 €/kWh th . Conclusion:We concluded that, under certain conditions such as location or supply and demand structure, German bioenergy plants have the potential to provide a significant share to renewable energies in the heating sector. In addition, the heat sales potential is highly relevant for plant operators as the importance of heat as a business segment is set to increase. Furthermore, bioenergy plants could contribute 2.1% (16.3 TWh th /a) to the total demand for space heating in Germany (765 TWh th /a) when considering certain technical and economic constraints.

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“…However, the datasets are not publicly available at the time of the submission of this paper. Moreover, the Heat Roadmap Europe project, a robust body of scientific literature (e.g., [15][16][17][18][19][20][21][22][23][24][25]) on similar yet more locally focused projects, is available. The heat density maps developed in the frame of the comprehensive assessments at the national level also belong to this category.…”

Section: Spacial Levels Of Heating and Cooling Planningmentioning

confidence: 99%

Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28

Müller

Hummel²,

Kranzl

et al. 2019

Energies

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The planning of heating and cooling supply and demand is key to reaching climate and sustainability targets. At the same time, data for planning are scarce for many places in Europe. In this study, we developed an open source dataset of gross floor area and energy demand for space heating and hot water in residential and tertiary buildings at the hectare level for EU28 + Norway, Iceland, and Switzerland. This methodology is based on a top-down approach, starting from a consistent dataset at the country level (NUTS 0), breaking this down to the NUTS 3 level and further to the hectare level by means of a series of regional indicators. We compare this dataset with data from other sources for 20 places in Europe. This process shows that the data for some places fit well, while for others, large differences up to 45% occur. The discussion of these results shows that the other data sources used for this comparison are also subject to considerable uncertainties. A comparison of the developed data with maps based on municipal building stock data for three cities shows that the developed dataset systematically overestimates the gross floor area and heat demand in low density areas and vice versa. We conclude that these data are useful for strategic purposes on aggregated level of larger regions and municipalities. It is especially valuable in locations where no detailed data is available. For detailed planning of heating and cooling infrastructure, local data should be used instead. We believe our work contributes towards a transparent, open source dataset for heating and cooling planning that can be regularly updated and is easily accessible and usable for further research and planning activities.

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Impact of distribution and transmission investment costs of district heating systems on district heating potential

Cited by 19 publications

References 14 publications

District heating distribution grid costs: a comparison of two approaches

District heating distribution grid costs: a comparison of two approaches

Bioenergy plants’ potential for contributing to heat generation in Germany

Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28

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