DEA Methodology

The methodology underlying the Dynamic Energy Atlas makes it into a very flexible and open ended product. In fact, in function of the precise needs, the data available and the size of the study area, the user starting a new application can decide on:

  • Aspects of the energy system to be incorporated: energy demand, installed energy production, potential energy production, …
  • Form of energy: electricity, heat, fuels of various sorts, …
  • Technologies (energy production, producers): carbon based, nuclear, …, wind, solar, biomass, geothermal, hydro power, … , subdivided or aggregated in function of needs and data availability.
  • Sectors (energy demand, consumers): industry, services, commerce, transportation, households, … subdivided or aggregated in function of needs and data availability.
  • Study area, resolution and spatial entities: For each study area, a new application can be set-up. It can vary from areas measuring a few km2 up to a few million km2. The study area is represented as a matrix of square grid cells. Resolutions can vary from tens of meters to tens of kilometres depending on the size of the study area and the details required in the output. All calculations are performed at the grid level and cells can be aggregated to any spatial entity defined by the user.

At any time during the lifetime of an application, the information can be expanded, completed, replaced or deleted.

Although demand and production are dealt with in separate sections of the Dynamic energy Atlas, the same basic methodology is used to represent the various sectors demanding energy and the technologies producing energy. Each in their section, demand and production are organised in a hierarchically nested manner. Five hierarchical levels are supported, evolving from the total demand down to that of a specific activity (industry, commercial, type of household, …) or the total production down to the production by means of a specific technology deployed in a specific constellation, such as ‘small scale photovoltaic panels (< 10 KW) on roofs of residential buildings’.

The base data are entered at the most detailed level of the hierarchical tree. At each hierarchical level results of all computations can be consulted in the form of maps, tables and graphs.

A distinction is made in the Dynamic Energy Atlas between producers/consumers according to (1) the nature of the data available, (2) their distribution in space. It distinguishes between:

  1. Point producers/consumers. Producers/consumers for which the precise location (X,Y-coordinates) are known and the precise production/demand is measured and reported. Most often these are larger production units, such as on-shore wind turbines, and/or bigger (industrial) consumers.
  2. Diffuse producers/consumers. Producers/consumers for which the precise location is not known and has to be estimated as precisely as possible on the basis of geographical proxies, and/or, which production capacity or consumption is not known at the level of the source, rather, has to be estimated on the basis of technical coefficients or data available at a higher level of aggregation. Examples are small production installations like PV panels on roofs of buildings and/or consumption by households which is typically undisclosed information.

For point producers/consumers, the Dynamic Energy Atlas will store information about the individual producer or consumer in the built-in database.

For diffuse producers/consumers, the Dynamic Energy Atlas supports both a bottom-up and top-down allocation of production and consumption for every single technology producing energy or sector consuming energy:

  • The bottom-up allocation will start from an as precise as possible location of the producers/consumers on the map and will compute based on the precise data available, if not best available technical information, the production/demand in the location.
  • The top-down allocation starts from production/demand data available at an aggregate level (national, regional, municipal) and will disaggregate it to grid cells based on the best available geographical proxies and advanced mapping algorithms to generate a map of the producers/consumers.

The Dynamic Energy Atlas is equipped with a complete set of dedicated but generically applicable spatial allocation algorithms ready to be selected by the user in function of the type of proxies and GIS map-layers available. One such algorithm is intended to define areas where a specific technology, such as large scale wind turbines, can be deployed. It enables the user to enter and compile two stacks of map-layers (see illustration), one representing the positive spatial criteria facilitating the deployment of the technology, and, a second representing the negative spatial criteria prohibiting the deployment. Criteria are a selection of physical, environmental, spatial planning or legislative characteristics of the study area, each available as a GIS map-layer.


As a result, the algorithm visualises on a map the areas where the technology is permitted. By means of clicking check-boxes the user can switch on or off a map layer and thus explore the effects of including or excluding a given positive or negative spatial criterion. Similarly, criteria can be weighted individually, and a threshold value can be defined so that ultimately areas will be available or not for the technology depending on the total positive and negative weights of all criteria that apply.