EnDAT – Energy Data Analysis Tool

Overview on the EnDAT model.

EnDAT (Energy Data Analysis Tool) is a modular program for spatially and temporally resolved analysis of energy system data, written in Python. It provides capacity and power generation potentials of variable renewable energy technologies as well as power and heat demand profiles for energy systems modelling and energy scenario analyses.

Input data are meteorological data (e.g. wind speed, solar irradiance), geodata (e.g. land cover, terrain inclination and orientation, protected areas, population density), energy demand scenarios, technical and economic parameters of power plants and statistical information. Data processing includes the following technology-specific steps:

  • Area analysis and application of exclusion and area competition criteria
  • Application of a power plant model based on the meteorological data
  • Temporal aggregation of the results to annual totals (displayable in map form)
  • Spatial aggregation of the results to regional time series.

​​​Spatial and temporal resolution are variable. In Europe, the input data allow for an hourly resolution temporally, and spatially for approx. 1x1 - 10x10 sqm. At the global scale, hourly data with 31x31 sqm can pe provided. User-defined aggregation to regions (e.g. counties, federal states, states) and to time steps (e.g. hours, months, years) is an important prerequisite for energy system modeling and scenario analysis with changing study areas and topics.

The content analysis is embedded in a parallelized program structure, which can optionally be activated if large amounts of data are to be processed in a short time.

Departments, research groups and challenges related to the EnDAT model:

Department

Energy Systems Analysis

The Energy Systems Analysis department generates system-analytical knowledge, which we provide across sectors up to the global level and based in part on methods and modelling tools developed in-house.

Research Group

Energy System Modelling

The Energy System Modelling research group is developing methods and solutions for the planning and operation of future energy infrastructures. The primary focus lies in examining how various technologies can contribute to creating energy systems that are sustainable, reliable, and cost-effective.

Challenge

Strategies for sustainable energy systems

Energy transition is a dynamic process that must be continuously adapted to new influences such as technical innovations or socially negotiated framework conditions.

Contact

Energy System Modelling

Research Group
Institute of Networked Energy Systems