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This module generates a shapefile of potential district heating areas based on an assessment of the heat distribution costs. Inputs to the module are heat demand and gross floor area density maps, costs of network expansion, development of heat demand and connection rates, depreciation time, interest rate and a threshold for the accepted heat distribution costs. Furthermore, it calculates the costs of transmission lines between identified district heating areas.
This calculation module uses the European heat density map (EHDM) and a European gross floor area map (EGFAM), both of which were developed in course of the Hotmaps project, to propose a GIS-based method for determining potential DH areas with specific focus on district heating (DH) grid costs. The DH areas are determined via performing sensitivity analyses on the EHDM under consideration of predefined upper bound of the average distribution costs. The approach additionally allows for the estimation of length and diameter of transmission lines and their associated costs. The outputs are GIS layers that illustrate areas that are economically viable for construction of DH as well as the cost-minimal transmission lines connecting these regions to each other. The calculation module can be used to study the impact of parameters like grid costs ceiling and market share on potential and on expansion and extension of the DH systems.
The input parameters and layers, as well as output layers and parameters, are as follows.
Input layers and parameters are:
Output layers and parameters are:
The aim of the calculation module is to find regions in which DH system can be built without exceeding a user-defined average specific cost ceiling in EUR/MWh. This is done under the following assumptions:
The determination of economic DH areas is done in three steps. For more details refer to the provided test runs.
STEP 1: Calculation of distribution grid costs based on heat demand and plot ratio using EHDM and EGFAM
STEP 2: Determination of potential DH areas
STEP 3: Determination of economic DH areas and transmission line capacities and configuration required to connect these areas to each other.
This calculation module uses Gurobi solver for solving the optimization problem. In order to guarantee a stable functionality of the calculation module, we have introduced several options for solving the optimization problem. These options are as follows:
Here you get the bleeding-edge development for this calculation module.
Here, the calculation module is run for the case study of Vienna, Austria. First, use the "Go To Place" bar to navigate to Vienna and select the city. Click on the "Layers" button to open the "Layers" window and then click on the "CALCULATION MODULE" tab. In the list of calculation modules, select "CM - District heating potential: economic assessment".
The provided default values in the toolbox are basically suitable for Vienna, i.e. it may not suit for other regions and should be adapted depending on your case study. The calculation is done for the period from 2018 to 2030 (2018 is the year 0 and 2030 is the year 12 and the investment period will be 12 years). The expected accumulated energy saving ratio shows the reduction of heat demand compared to the beginning of the investment period (year 2018). The DH market share refers to the market share within the DH areas. Its value at the beginning of the investment period (year 2018), shows the actual market share (usually known). The expected market share at the investment period is what you expect to reach. This value comes from road maps, scenarios, policies and etc. For the default case, we consider the interest rate of 5 per cent. The DH grid cost ceiling is multiplied by ~95% to get a cost ceiling for the distribution grid. Using this value, the potential DH areas are obtained. Within the potential areas, the average distribution grid cost may not exceed the distribution grid cost ceiling. The value of full load hours is used to estimate the peak load and find a suitable dimension for the transmission grid.
The construction cost constant and the construction cost coefficient originate from reference . The obtained regions are very sensitive to these values. Therefore, as a general comment, we suggest to calculate with these values first and only if you think these values lead to an over- or underestimation of your results, then modify them.
By default, the heat density map and the gross floor area density map that are provided by the toolbox are used for the calculation. You can use your own uploaded layers for running the calculation. Here, we use default layers.
Now, press the run button and wait until the calculation is finished.
IMPORTANT NOTE: Please note that this calculation module may take several minutes to find the final solution. If your calculation takes very long (more than 10 minutes), select a smaller region for your calculation. Also, using arbitrary values can lead to a long calculation time. Therefore, make sure that your provided values are suitable for the selected region.
The following figure shows the obtained results for the given input parameters in Vienna. The most important indicators are demonstrated in the RESULTS window. Additionally, you can get some indicators by pressing on each single potential areas on the map
The output layers will appear in the LAYERS window under the Calculation module section.
. Fallahnejad M, Hartner M, Kranzl L, Fritz S. Impact of distribution and transmission investment costs of district heating systems on district heating potential. Energy Procedia 2018;149:141–50. doi:10.1016/j.egypro.2018.08.178.
. Persson U, Werner S. Heat distribution and the future competitiveness of district heating. Appl Energy 2011;88:568–76. doi:10.1016/j.apenergy.2010.09.020.
Mostafa Fallahnejad, in Hotmaps-Wiki, CM-District-heating-grid-costs (April 2019)
This page is written by Mostafa Fallahnejad*.
* Energy Economics Group - TU Wien Institute of Energy Systems and Electrical Drives Gusshausstrasse 27-29/370 1040 Wien
Copyright © 2016-2019: Mostafa Fallahnejad
Creative Commons Attribution 4.0 International License This work is licensed under a Creative Commons CC BY 4.0 International License.
We would like to convey our deepest appreciation to the Horizon 2020 Hotmaps Project (Grant Agreement number 723677), which provided the funding to carry out the present investigation.
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* machine translated
Last edited by GiuliaConforto, 2020-09-02 08:43:55