Wiki Introduction

• Welcome page

Data sets

• Hotmaps data set: Method of data collection
• Hotmaps open data repositories

General tool functionalities & structure

• Introduction to user interface
• Layers section in the Hotmaps toolbox
• Select a region in the Hotmaps toolbox
• Retrieve indicators of a selected area
• Access to calculation modules
• Database behind the Hotmaps toolbox
• Data upload functionalities
• Data export functionalities

Calculation modules (CM)

• CM - Customized heat and gross floor area density maps
• CM - Scale heat and cool density maps
• CM - Demand projection
• CM - Heat load profiles
• CM - District heating potential areas: user-defined thresholds
• CM - District heating potential: economic assessment
• CM - District heating supply dispatch
• CM - Decentral heating supply
  
• CM - Solar thermal and PV potential
• CM - Shallow geothermal potential
• CM - Heat source potential
• CM - Biomass potential
• CM - Wind potential
• CM - Excess heat transport potential
• CM - Scenario assessment
• CM - Add industry plant
• CM - Vehicle stock at NUTS 2 level

How to apply Hotmaps toolbox

• Guideline: Hotmaps toolbox on local level
• Guideline: Hotmaps toolbox on national level
• Concept for using Hotmaps for district cooling
• Training material

For Developers

• Developers section
• Guidelines for defining indicators
• Guidelines for writing a Hotmaps Wiki page

Step 1: Analysis of current heat demand and available resource potentials

The steps to analyse the potentials for excess heat and renewable energy are highlighted above.

Analysis of potentials for excess heat and renewable energy in the identified regions with potential interest for district heating

In the next step, the potentials for excess heat and renewable energy in the regions that have been identified as potentially interesting for district heating can be analysed. These data together with the data on heat demand and heat demand density in the regions collected in the previous step can then be used to characterise representative district heating areas for further analysis steps. The following list gives an overview of the heat sources that should be taken into account and links to the default data for the respective energy source, which is available in the Hotmaps database:

• Renewable energy sources:
  • Waste water treatment plants:
    • DB - Wastewater treatment plants power
    • DB - Wastewater treatment plants capacity
  • Agricultural biomass:
    • DB - Agricultural residues
    • DB - Livestock effluents
  • Forestal biomass:
    • DB - Forest residues
  • Waste:
    • DB - Municipal solid waste
  • Geothermal energy:
    • DB - Geothermal potential heat conductivity
  • Solar thermal energy:
    • DB - Potential solar thermal collectors - rooftop
    • DB - Potential solar thermal collectors open - field
• Excess heat:
  • Large industrial sites:
    • DB - Industrial sites excess heat
  • Other excess heat sources:
    • Information on other excess heat sources like power plants, further industrial plants, low-temperature heat sources like river water, data centers, etc. can be uploaded into the toolbox. A guide on how to do this can be found here.

The following figure shows this procedure graphically and shows the various data sources and calculation modules that can be used.

Identification of different representative, typical cases for district heating (Step 1).

To the Scenario Toolchain Steps To the next step