Renewables at >50% in European grids

Since the beginning of 2020, a field test demonstrator was set up at MITNETZ STROM. This demonstrator consists of an innovative grid and data integration functionalities which support more planning options and hence more stable grid operation as well as an improved communication between Transmission System Operator (TSO) and Distribution System Operator (DSO).

In Figure 1, a schematic overview of the different functionalities and the architecture of the demonstrator platform are described. The main input data is in the Common Information Model CIM data model and consists of equipment data, topological data and measurements. In addition, forecast information are also imported and used to build future grid states for the forecast horizon.

Figure 1:Architecture of the EU-SysFlex field test demonstrator running at MITNETZ STROM.

The system is running in parallel mode at the moment, which means that the functionalities within the demonstrator receive frequently the latest grid and forecast information. Based on this data, active and reactive power flexibility bands are computed via the optimization tool. Figure 2 shows an example of those flexibility bands for one of the grid network groups. Since no feedback loop with the grid control center is established by this moment, no optimization results can be applied on the field devices and hence the actual active and reactive power exchange for this network group is not affected. In Figure 2, the upper and lower boundaries are plotted as well as the actual power flow and the proposed power flow after optimization. (More details are presented at CIGRE2020 Paris in the contribution C2/C6 – 326:”Grid control center extension platform for flexibility aggregation of DER in the EU-project “EU-SysFlex”)

Figure 2: Active (left )and reactive (right) power flexibilities from parallel mode of the field test demonstrator in the grid of MITNETZ STROM. The shaded area depicts the flexibility range and the green and blue lines depict OPF results and actual power flow, respectively.

The identical process takes place on forecast data and related grid states (see Figure 3 ). Based on this information, the DSO can now estimate flexibility potentials on all of its grid connection points between TSO and DSO, for the current moment and (in a later stage) up to 72 hours in the future. This supports grid operation strategies and decisions as well as the future Redispatch2.0 process. If the DSO chooses to adjust active or reactive power flow between DSO and TSO at a certain grid connection point, the EU-SysFlex demonstrator computes the desired set points to adjust the individual renewable energy sources which participated in the computation of the flexibility bands.


Figure 3: Active (red) and reactive (blue) power flexibility bands based on forecast data and related grid states.


Written by: Dr. Sebastian Wende-von Berg (University of Kassel/Fraunhofer IEE) working on Grid simulation and Grid optimization of the German Demonstrator of flexibility services from resources connected to the distribution network

The Fraunhofer Institute for “Institute for Energy Economics and Energy System Technology (IEE) has its core competence in energy management and system design. It is concentrated on system modelling and the associated analyses of political and economic options for action. The considered systems cover technical (producers, consumers, storage, grid, etc.) as well as economic components (energy market, business models, etc.). Research topics include among others the integrated simulation of future energy supply structures, system analyses and technology assessment, integration of markets and systems, interaction of the sectors electricity-heat- transport, international, national and regional energy concepts and their evaluation as well as energy solutions for the industry. Fraunhofer IEE consists of about 350 employees and has an annual budget of about 22Mio €. The departments, which are most active in EU SysFlex, are “Department of Grid Planning and Grid Operation” and “Energy Informatics” focus on research and development of new approaches for system operation strategies and solutions as well as of statistical and physical based models for the prediction of energy generation and consumption.

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Disclaimer: blog entries reflect individual views of the author(s) that may not reflect official positions or communication of the project / project consortium.


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