The proactive distribution grid

Traffic light concept for more efficient distribution grids

Project state

The project combines energy markets and networks based on the BDEW traffic light. Through a new platform, grid operators can access (load and generation) flexibility, prevent local network congestion and optimise network planning. The distribution networks are thus becoming more efficient and are contributing to an affordable energy transition.

The distribution grids already integrate 97% of the output from renewable energies and a diverse range of new, decentralised actors will be added. The input from wind and photovoltaic energy and their rarely occurring, but exceptionally high feed-in peaks pose considerable challenges for electrical supply grids. On the load side, current developments in the smart meter, electric mobility and storage areas indicate that a direct response to price signals from the market will also result in highly simultaneous grid usage.

However, distribution grid operators, whose tasks include securing network operation, are faced with the challenge of reconciling the national economic benefits from strengthening the grid for rare, high utilisation peaks with the generally disproportionate costs. In these cases, intelligent grid capacity management is necessary owing to the interaction between the network and the market.

Traffic light concept as a solution component

The BDEW (German Federal Association of the Energy and Water Industries) describes a possible approach to solving this with its "traffic light concept for smart grids", which is aimed at also making flexibilities available for distribution grid operators. Compared with today's methods at the transport level, a challenge in utilising the flexibility for distribution grids is the local confinement and the small individual quantities per demand.

Based on the BDEW concept, this research project is developing and testing a technical design with a focus on detecting local congestion in networks with distributed flexibility and suitable communication between the market and network.

Interaction between the network and market

Schematic course of the traffic light concept
Schematic course of the traffic light concept

A fundamental prerequisite for designing a flexibility traffic light concept is the reliable, predictive detection of congestion in the distribution grid. In general, two types of congestion typically occur in distribution grids: equipment overloads and voltage range violations. In order to recognise and evaluate these, methods for determining and forecast the network state are required. Established methods for determining the state, such as state estimation, can usually only be used in the high and extra-high voltage grids. The pronounced measurement infrastructure means that a minimum degree of observability is generally provided in these grids, while less or no measuring infrastructure is available at lower voltage levels. "State estimation" in the transmission grid is characterised by a superordinate system where measurements are primarily validated, whereas in the distribution grid a subordinate system is generally considered with the focus being on the generation of state data. For the development of predictive congestion detection in the distribution grid, three research strands are being mainly pursued in the "proactive distribution grid".

  • The first research strand is concerned with determining a minimal measuring point configuration. The intention is to place the measuring points so cleverly that the minimum necessary observability is achieved for the predictive congestion detection.
  • The second research strand is concerned with generating replacement values for missing measured values from alternative data sources and status data for forecasting tasks.
  • The third research strand is concerned with developing and implementing innovative methods for determining and forecasting the grid state, taking into account unsafe input data.

As a result, grid managers in the control room are provided with a tool that enables them to make a thorough assessment of the network status with partially automated congestion management. When congestion occurs, possible solutions are identified by using flexible producer and load systems that can resolve the congestion and bring the network state into the normal operating range. For this purpose, this information is communicated to a communication and services platform (CSP), which coordinates the non-discriminatory selection of the flexibility options and the further handling of the flexibility fetching.

Local congestion should be solved first by using local flexibility. Which systems are suitable for this purpose can be determined using topological and technical data. With the help of this data, the state forecast can develop non-discriminatory solutions, i.e. in particular without knowledge of the owners and distributors. These potential solutions only use previously known system flexibilities and, by using the flexibilities, constitute flexibility constraints in themselves.


As part of a demonstration in Emsland within the research project, the developed technical concept will be set up and verified within a network area belonging to the Westnetz distribution grid operator. Here the interaction of the individual components in the yellow traffic light phase will be investigated along with the interaction with current processes within the network management. In a parallel simulation, future network variants will also be evaluated with a strong penetration of different flexibility options in order to validate the usefulness and future viability of the concept.


The concept of a flexibility traffic light is particularly promising if its implementation allows a simple, standardised exchange between the grid and market, while providing scope for implementing company-specific processes. In addition, the process integration must be sustainable and innovative to enable further developments and adjustments due to the changing market environment. These aspects and further technical conditions will be investigated within the project demonstration in 2017.

Basic information

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