See also project source code and more recent documentation on: https://github.com/RuudvandenWijngaart/VestaDV



Vesta is a spatially explicit model that matches future projected demand for energy in the built environment to options for local and zonal energy supply. The primary focus for building this model was to assess impacts of different policies for local and regional energy production on non-renewable resource consumption, wealth (re)distribution, CO2 emission, compliance and public finance at the national level.

The demand for energy is modelled geographically specific for: residential objects, business locations and greenhouses. Changes in the built environment are well taken into account by using the results of the Land Use Scanner. Not included are: industrial usage, roofless agriculture, and transportation.


Modelled energy supply and usage reduction options are:

Building specific:

  1. Consumption reduction: thermal building insulation, installation efficiency
  2. Solar PV and Solar water heaters cells
  3. MicroCHP (Dutch: MicroWKK) for the local cogeneration of heat and electric power from gas.
  4. Electrical Heat Pump to turn buildings into inverted refrigerators.


  1. Waste heat (Dutch: restwarmte) for industrial and electrivcity plants. energy price scenarios.
  2. Geothermal energy (Dutch: geothermie)
  3. Cogeneration (bio-fuelled and gas-drive) (Dutch: BMC and wijk WKK) for the zonal cogeneration of heat and electric power
  4. Geothermal heat pump (Dutch: WKO, in combination with a eWP)

Non zonal:

  1. Natural gas (Dutch: aardgas)
  2. Electricity

Vesta first applies user specified building specific options, then allocates zonal supply options that have a positive yield.  Non zonal options are only considered as rest category.

The allocation is performed with iterations for each supply option. If the yield for a supply option for a zone is positive, the zone is allocated to this option. The next iterations only considers unallocated zones. The preference sequence of the supply options can be varied.


Demand calculation and visualisation, now based on 6PPC data of dwellings and non-residential buildings, combined with estimated energy consumption for different building types and construction years and their related average Energy Label.

Adaptations for future demand based on:

  1. options for destruction, renovation and construction of buildings with input from land use change scenario results of the Land Use Scanner (Dutch: RuimteScanner);
  2. energy saving options like thermal insulation, modelled as Energy Label Jumps;
  3. local energy production like solar collectors;

cost calculations of supply options based on variable and investment costs;

cost benefit analysis at zonal (4PPC) level;

indicators for end-user & public costs and carbon dioxide emission on national level.

Technical Aspects

  • Vesta is implemented in the model definition language of the GeoDMS,
  • It now uses GeoMarktProfiel data for localising residential energy usage (on a PC6 level) and LISA data for individual business locations; we are planning to replace these data sources by the Basisregister Adressen en Gebouwen (BAG), which could make Vesta with its Dutch data available under open source conditions (GNU GPL for the software + CC BY SA for the data); for now, the data cannot be distributed.



Vrije Universiteit
De Boelelaan 1085
1081 HV Amsterdam
The Netherlands

tel: +31 (0)20 598 9083
fax:+31 (0)20 598 9904